fix(tool): support zod 3 plugin schemas

fix(session): reject tool schemas with zod internals
test(opencode): cover native reasoning continuation (#28683 )
2026-05-21 17:26:53 -04:00 · 2026-05-21 16:39:56 -04:00 · 2026-05-21 14:50:37 -04:00 · 2026-05-21 14:25:43 -04:00 · 2026-05-21 13:55:31 -04:00 · 2026-05-21 17:27:59 +00:00
52 changed files with 2221 additions and 982 deletions
@@ -21,15 +21,6 @@ jobs:
        with:
          node-version: "24"

-      # Workaround for Pulumi version conflict:
-      # GitHub runners have Pulumi 3.212.0+ pre-installed, which removed the -root flag
-      # from pulumi-language-nodejs (see https://github.com/pulumi/pulumi/pull/21065).
-      # SST 3.17.x uses Pulumi SDK 3.210.0 which still passes -root, causing a conflict.
-      # Removing the system language plugin forces SST to use its bundled compatible version.
-      # TODO: Remove when sst supports Pulumi >3.210.0
-      - name: Fix Pulumi version conflict
-        run: sudo rm -f /usr/local/bin/pulumi-language-nodejs
-
      - run: bun sst deploy --stage=${{ github.ref_name }}
        env:
          CLOUDFLARE_API_TOKEN: ${{ secrets.CLOUDFLARE_API_TOKEN }}
@@ -23,13 +23,13 @@
        "oxlint-tsgolint": "0.21.0",
        "prettier": "3.6.2",
        "semver": "^7.6.0",
-        "sst": "3.18.10",
+        "sst": "4.13.1",
        "turbo": "2.8.13",
      },
    },
    "packages/app": {
      "name": "@opencode-ai/app",
-      "version": "1.15.6",
+      "version": "1.15.7",
      "dependencies": {
        "@kobalte/core": "catalog:",
        "@opencode-ai/core": "workspace:*",
@@ -84,7 +84,7 @@
    },
    "packages/console/app": {
      "name": "@opencode-ai/console-app",
-      "version": "1.15.6",
+      "version": "1.15.7",
      "dependencies": {
        "@cloudflare/vite-plugin": "1.15.2",
        "@ibm/plex": "6.4.1",
@@ -119,7 +119,7 @@
    },
    "packages/console/core": {
      "name": "@opencode-ai/console-core",
-      "version": "1.15.6",
+      "version": "1.15.7",
      "dependencies": {
        "@aws-sdk/client-sts": "3.782.0",
        "@jsx-email/render": "1.1.1",
@@ -146,7 +146,7 @@
    },
    "packages/console/function": {
      "name": "@opencode-ai/console-function",
-      "version": "1.15.6",
+      "version": "1.15.7",
      "dependencies": {
        "@ai-sdk/anthropic": "3.0.64",
        "@ai-sdk/openai": "3.0.48",
@@ -168,7 +168,7 @@
    },
    "packages/console/mail": {
      "name": "@opencode-ai/console-mail",
-      "version": "1.15.6",
+      "version": "1.15.7",
      "dependencies": {
        "@jsx-email/all": "2.2.3",
        "@jsx-email/cli": "1.4.3",
@@ -192,7 +192,7 @@
    },
    "packages/core": {
      "name": "@opencode-ai/core",
-      "version": "1.15.6",
+      "version": "1.15.7",
      "bin": {
        "opencode": "./bin/opencode",
      },
@@ -230,7 +230,7 @@
        "ai-gateway-provider": "3.1.2",
        "cross-spawn": "catalog:",
        "effect": "catalog:",
-        "gitlab-ai-provider": "6.6.0",
+        "gitlab-ai-provider": "6.7.0",
        "glob": "13.0.5",
        "google-auth-library": "10.5.0",
        "immer": "11.1.4",
@@ -253,7 +253,7 @@
    },
    "packages/desktop": {
      "name": "@opencode-ai/desktop",
-      "version": "1.15.6",
+      "version": "1.15.7",
      "dependencies": {
        "@zip.js/zip.js": "2.7.62",
        "drizzle-orm": "catalog:",
@@ -308,7 +308,7 @@
    },
    "packages/effect-drizzle-sqlite": {
      "name": "@opencode-ai/effect-drizzle-sqlite",
-      "version": "1.15.5",
+      "version": "1.15.7",
      "dependencies": {
        "drizzle-orm": "catalog:",
        "effect": "catalog:",
@@ -322,7 +322,7 @@
    },
    "packages/enterprise": {
      "name": "@opencode-ai/enterprise",
-      "version": "1.15.6",
+      "version": "1.15.7",
      "dependencies": {
        "@opencode-ai/core": "workspace:*",
        "@opencode-ai/ui": "workspace:*",
@@ -352,7 +352,7 @@
    },
    "packages/function": {
      "name": "@opencode-ai/function",
-      "version": "1.15.6",
+      "version": "1.15.7",
      "dependencies": {
        "@octokit/auth-app": "8.0.1",
        "@octokit/rest": "catalog:",
@@ -368,7 +368,7 @@
    },
    "packages/http-recorder": {
      "name": "@opencode-ai/http-recorder",
-      "version": "1.15.6",
+      "version": "1.15.7",
      "dependencies": {
        "@effect/platform-node": "catalog:",
        "effect": "catalog:",
@@ -381,7 +381,7 @@
    },
    "packages/llm": {
      "name": "@opencode-ai/llm",
-      "version": "1.15.6",
+      "version": "1.15.7",
      "dependencies": {
        "@smithy/eventstream-codec": "4.2.14",
        "@smithy/util-utf8": "4.2.2",
@@ -399,7 +399,7 @@
    },
    "packages/opencode": {
      "name": "opencode",
-      "version": "1.15.6",
+      "version": "1.15.7",
      "bin": {
        "opencode": "./bin/opencode",
      },
@@ -469,7 +469,7 @@
        "drizzle-orm": "catalog:",
        "effect": "catalog:",
        "fuzzysort": "3.1.0",
-        "gitlab-ai-provider": "6.6.0",
+        "gitlab-ai-provider": "6.7.0",
        "glob": "13.0.5",
        "google-auth-library": "10.5.0",
        "gray-matter": "4.0.3",
@@ -537,7 +537,7 @@
    },
    "packages/plugin": {
      "name": "@opencode-ai/plugin",
-      "version": "1.15.6",
+      "version": "1.15.7",
      "dependencies": {
        "@opencode-ai/sdk": "workspace:*",
        "effect": "catalog:",
@@ -575,7 +575,7 @@
    },
    "packages/sdk/js": {
      "name": "@opencode-ai/sdk",
-      "version": "1.15.6",
+      "version": "1.15.7",
      "dependencies": {
        "cross-spawn": "catalog:",
      },
@@ -590,7 +590,7 @@
    },
    "packages/slack": {
      "name": "@opencode-ai/slack",
-      "version": "1.15.6",
+      "version": "1.15.7",
      "dependencies": {
        "@opencode-ai/sdk": "workspace:*",
        "@slack/bolt": "^3.17.1",
@@ -625,7 +625,7 @@
    },
    "packages/ui": {
      "name": "@opencode-ai/ui",
-      "version": "1.15.6",
+      "version": "1.15.7",
      "dependencies": {
        "@kobalte/core": "catalog:",
        "@opencode-ai/core": "workspace:*",
@@ -674,7 +674,7 @@
    },
    "packages/web": {
      "name": "@opencode-ai/web",
-      "version": "1.15.6",
+      "version": "1.15.7",
      "dependencies": {
        "@astrojs/cloudflare": "12.6.3",
        "@astrojs/markdown-remark": "6.3.1",
@@ -907,6 +907,8 @@

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@@ -977,6 +979,8 @@

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+    "@aws/durable-execution-sdk-js": ["@aws/durable-execution-sdk-js@1.0.2", "", { "dependencies": { "@aws-sdk/client-lambda": "^3.943.0" } }, "sha512-KIYBVqV9gArkWdPEDYOjJqLlO+NecmCXOXadNBlOspJTmqztwuiyb6aZc468bYWSGuL4Me/gyTIK97ubkwFNCw=="],
+
    "@aws/lambda-invoke-store": ["@aws/lambda-invoke-store@0.2.4", "", {}, "sha512-iY8yvjE0y651BixKNPgmv1WrQc+GZ142sb0z4gYnChDDY2YqI4P/jsSopBWrKfAt7LOJAkOXt7rC/hms+WclQQ=="],

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@@ -1463,6 +1467,8 @@

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+    "@nodable/entities": ["@nodable/entities@2.1.0", "", {}, "sha512-nyT7T3nbMyBI/lvr6L5TyWbFJAI9FTgVRakNoBqCD+PmID8DzFrrNdLLtHMwMszOtqZa8PAOV24ZqDnQrhQINA=="],
+
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-
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@@ -4075,8 +4077,6 @@

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@@ -4273,7 +4273,7 @@

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@@ -4283,8 +4283,6 @@

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@@ -4469,7 +4467,7 @@

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@@ -4597,23 +4595,23 @@

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@@ -4893,8 +4891,6 @@

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-
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    "use-sidecar": ["use-sidecar@1.1.3", "", { "dependencies": { "detect-node-es": "^1.1.0", "tslib": "^2.0.0" }, "peerDependencies": { "@types/react": "*", "react": "^16.8.0 || ^17.0.0 || ^18.0.0 || ^19.0.0 || ^19.0.0-rc" }, "optionalPeers": ["@types/react"] }, "sha512-Fedw0aZvkhynoPYlA5WXrMCAMm+nSWdZt6lzJQ7Ok8S6Q+VsHmHpRWndVRJ8Be0ZbkfPc5LRYH+5XrzXcEeLRQ=="],
@@ -4903,8 +4899,6 @@

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-    "util": ["util@0.12.5", "", { "dependencies": { "inherits": "^2.0.3", "is-arguments": "^1.0.4", "is-generator-function": "^1.0.7", "is-typed-array": "^1.1.3", "which-typed-array": "^1.1.2" } }, "sha512-kZf/K6hEIrWHI6XqOFUiiMa+79wE/D8Q+NCNAWclkyg3b4d2k7s0QGepNjiABc+aR3N1PAyHL7p6UcLY6LmrnA=="],
-
    "util-deprecate": ["util-deprecate@1.0.2", "", {}, "sha512-EPD5q1uXyFxJpCrLnCc1nHnq3gOa6DZBocAIiI2TaSCA7VCJ1UJDMagCzIkXNsUYfD1daK//LTEQ8xiIbrHtcw=="],

    "utils-merge": ["utils-merge@1.0.1", "", {}, "sha512-pMZTvIkT1d+TFGvDOqodOclx0QWkkgi6Tdoa8gC8ffGAAqz9pzPTZWAybbsHHoED/ztMtkv/VoYTYyShUn81hA=="],
@@ -5031,6 +5025,8 @@

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+    "xml-naming": ["xml-naming@0.1.0", "", {}, "sha512-k8KO9hrMyNk6tUWqUfkTEZbezRRpONVOzUTnc97VnCvyj6Tf9lyUR9EDAIeiVLv56jsMcoXEwjW8Kv5yPY52lw=="],
+
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@@ -5193,6 +5189,20 @@

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@@ -5993,8 +5971,6 @@

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@@ -6069,6 +6043,36 @@

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@@ -6239,8 +6243,6 @@

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-
    "@azure/core-xml/fast-xml-parser/strnum": ["strnum@2.2.3", "", {}, "sha512-oKx6RUCuHfT3oyVjtnrmn19H1SiCqgJSg+54XqURKp5aCMbrXrhLjRN9TjuwMjiYstZ0MzDrHqkGZ5dFTKd+zg=="],

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@@ -6553,14 +6555,10 @@

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    "c12/chokidar/readdirp": ["readdirp@5.0.0", "", {}, "sha512-9u/XQ1pvrQtYyMpZe7DXKv2p5CNvyVwzUB6uhLAnQwHMSgKMBR62lc7AHljaeteeHXn11XTAaLLUVZYVZyuRBQ=="],

-    "crc/buffer/ieee754": ["ieee754@1.2.1", "", {}, "sha512-dcyqhDvX1C46lXZcVqCpK+FtMRQVdIMN6/Df5js2zouUsqG7I6sFxitIC+7KYK29KdXOLHdu9zL4sFnoVQnqaA=="],
-
    "cross-spawn/which/isexe": ["isexe@2.0.0", "", {}, "sha512-RHxMLp9lnKHGHRng9QFhRCMbYAcVpn69smSGcq3f36xjgVVWThj4qqLbTLlq7Ssj8B+fIQ1EuCEGI2lKsyQeIw=="],

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@@ -6603,6 +6601,8 @@

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+    "lazystream/readable-stream/isarray": ["isarray@1.0.0", "", {}, "sha512-VLghIWNM6ELQzo7zwmcg0NmTVyWKYjvIeM83yjp0wRDTmUnrM678fQbcKBo6n2CJEF0szoG//ytg+TKla89ALQ=="],
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@@ -6617,18 +6617,6 @@

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-    "opencontrol/@modelcontextprotocol/sdk/raw-body": ["raw-body@3.0.2", "", { "dependencies": { "bytes": "~3.1.2", "http-errors": "~2.0.1", "iconv-lite": "~0.7.0", "unpipe": "~1.0.0" } }, "sha512-K5zQjDllxWkf7Z5xJdV0/B0WTNqx6vxG70zJE4N0kBs4LovmEYWJzQGxC9bS9RAKu3bgM40lrd5zoLJ12MQ5BA=="],
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-    "opencontrol/@modelcontextprotocol/sdk/zod": ["zod@3.25.76", "", {}, "sha512-gzUt/qt81nXsFGKIFcC3YnfEAx5NkunCfnDlvuBSSFS02bcXu4Lmea0AFIUwbLWxWPx3d9p8S5QoaujKcNQxcQ=="],
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-    "opencontrol/@modelcontextprotocol/sdk/zod-to-json-schema": ["zod-to-json-schema@3.25.2", "", { "peerDependencies": { "zod": "^3.25.28 || ^4" } }, "sha512-O/PgfnpT1xKSDeQYSCfRI5Gy3hPf91mKVDuYLUHZJMiDFptvP41MSnWofm8dnCm0256ZNfZIM7DSzuSMAFnjHA=="],
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    "ora/bl/readable-stream": ["readable-stream@3.6.2", "", { "dependencies": { "inherits": "^2.0.3", "string_decoder": "^1.1.1", "util-deprecate": "^1.0.1" } }, "sha512-9u/sniCrY3D5WdsERHzHE4G2YCXqoG5FTHUiCC4SIbr6XcLZBY05ya9EKjYek9O5xOAwjGq+1JdGBAS7Q9ScoA=="],
@@ -6641,8 +6629,6 @@

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@@ -6761,6 +6747,18 @@

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+
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+    "@aws-sdk/client-lambda/@aws-sdk/credential-provider-node/@aws-sdk/credential-provider-web-identity/@aws-sdk/nested-clients": ["@aws-sdk/nested-clients@3.997.9", "", { "dependencies": { "@aws-crypto/sha256-browser": "5.2.0", "@aws-crypto/sha256-js": "5.2.0", "@aws-sdk/core": "^3.974.11", "@aws-sdk/signature-v4-multi-region": "^3.996.27", "@aws-sdk/types": "^3.973.8", "@smithy/core": "^3.24.2", "@smithy/fetch-http-handler": "^5.4.2", "@smithy/node-http-handler": "^4.7.2", "@smithy/types": "^4.14.1", "tslib": "^2.6.2" } }, "sha512-jPR3rnmRI4hWYyzfmTGBr7NblMp8QYYeflHXba1H6+7CGrWVqWKQzaXFQ4qbExqPRsXN3T3L3JxFhr6aouXUGQ=="],
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@@ -6957,30 +6955,6 @@

    "js-beautify/glob/path-scurry/lru-cache": ["lru-cache@10.4.3", "", {}, "sha512-JNAzZcXrCt42VGLuYz0zfAzDfAvJWW6AfYlDBQyDV5DClI2m5sAmK+OIO7s59XfsRsWHp02jAJrRadPRGTt6SQ=="],

-    "opencontrol/@modelcontextprotocol/sdk/express/accepts": ["accepts@2.0.0", "", { "dependencies": { "mime-types": "^3.0.0", "negotiator": "^1.0.0" } }, "sha512-5cvg6CtKwfgdmVqY1WIiXKc3Q1bkRqGLi+2W/6ao+6Y7gu/RCwRuAhGEzh5B4KlszSuTLgZYuqFqo5bImjNKng=="],
-
-    "opencontrol/@modelcontextprotocol/sdk/express/body-parser": ["body-parser@2.2.2", "", { "dependencies": { "bytes": "^3.1.2", "content-type": "^1.0.5", "debug": "^4.4.3", "http-errors": "^2.0.0", "iconv-lite": "^0.7.0", "on-finished": "^2.4.1", "qs": "^6.14.1", "raw-body": "^3.0.1", "type-is": "^2.0.1" } }, "sha512-oP5VkATKlNwcgvxi0vM0p/D3n2C3EReYVX+DNYs5TjZFn/oQt2j+4sVJtSMr18pdRr8wjTcBl6LoV+FUwzPmNA=="],
-
-    "opencontrol/@modelcontextprotocol/sdk/express/content-disposition": ["content-disposition@1.1.0", "", {}, "sha512-5jRCH9Z/+DRP7rkvY83B+yGIGX96OYdJmzngqnw2SBSxqCFPd0w2km3s5iawpGX8krnwSGmF0FW5Nhr0Hfai3g=="],
-
-    "opencontrol/@modelcontextprotocol/sdk/express/cookie": ["cookie@0.7.2", "", {}, "sha512-yki5XnKuf750l50uGTllt6kKILY4nQ1eNIQatoXEByZ5dWgnKqbnqmTrBE5B4N7lrMJKQ2ytWMiTO2o0v6Ew/w=="],
-
-    "opencontrol/@modelcontextprotocol/sdk/express/cookie-signature": ["cookie-signature@1.2.2", "", {}, "sha512-D76uU73ulSXrD1UXF4KE2TMxVVwhsnCgfAyTg9k8P6KGZjlXKrOLe4dJQKI3Bxi5wjesZoFXJWElNWBjPZMbhg=="],
-
-    "opencontrol/@modelcontextprotocol/sdk/express/finalhandler": ["finalhandler@2.1.1", "", { "dependencies": { "debug": "^4.4.0", "encodeurl": "^2.0.0", "escape-html": "^1.0.3", "on-finished": "^2.4.1", "parseurl": "^1.3.3", "statuses": "^2.0.1" } }, "sha512-S8KoZgRZN+a5rNwqTxlZZePjT/4cnm0ROV70LedRHZ0p8u9fRID0hJUZQpkKLzro8LfmC8sx23bY6tVNxv8pQA=="],
-
-    "opencontrol/@modelcontextprotocol/sdk/express/fresh": ["fresh@2.0.0", "", {}, "sha512-Rx/WycZ60HOaqLKAi6cHRKKI7zxWbJ31MhntmtwMoaTeF7XFH9hhBp8vITaMidfljRQ6eYWCKkaTK+ykVJHP2A=="],
-
-    "opencontrol/@modelcontextprotocol/sdk/express/merge-descriptors": ["merge-descriptors@2.0.0", "", {}, "sha512-Snk314V5ayFLhp3fkUREub6WtjBfPdCPY1Ln8/8munuLuiYhsABgBVWsozAG+MWMbVEvcdcpbi9R7ww22l9Q3g=="],
-
-    "opencontrol/@modelcontextprotocol/sdk/express/send": ["send@1.2.1", "", { "dependencies": { "debug": "^4.4.3", "encodeurl": "^2.0.0", "escape-html": "^1.0.3", "etag": "^1.8.1", "fresh": "^2.0.0", "http-errors": "^2.0.1", "mime-types": "^3.0.2", "ms": "^2.1.3", "on-finished": "^2.4.1", "range-parser": "^1.2.1", "statuses": "^2.0.2" } }, "sha512-1gnZf7DFcoIcajTjTwjwuDjzuz4PPcY2StKPlsGAQ1+YH20IRVrBaXSWmdjowTJ6u8Rc01PoYOGHXfP1mYcZNQ=="],
-
-    "opencontrol/@modelcontextprotocol/sdk/express/serve-static": ["serve-static@2.2.1", "", { "dependencies": { "encodeurl": "^2.0.0", "escape-html": "^1.0.3", "parseurl": "^1.3.3", "send": "^1.2.0" } }, "sha512-xRXBn0pPqQTVQiC8wyQrKs2MOlX24zQ0POGaj0kultvoOCstBQM5yvOhAVSUwOMjQtTvsPWoNCHfPGwaaQJhTw=="],
-
-    "opencontrol/@modelcontextprotocol/sdk/express/type-is": ["type-is@2.0.1", "", { "dependencies": { "content-type": "^1.0.5", "media-typer": "^1.1.0", "mime-types": "^3.0.0" } }, "sha512-OZs6gsjF4vMp32qrCbiVSkrFmXtG/AZhY3t0iAMrMBiAZyV9oALtXO8hsrHbMXF9x6L3grlFuwW2oAz7cav+Gw=="],
-
-    "ora/bl/buffer/ieee754": ["ieee754@1.2.1", "", {}, "sha512-dcyqhDvX1C46lXZcVqCpK+FtMRQVdIMN6/Df5js2zouUsqG7I6sFxitIC+7KYK29KdXOLHdu9zL4sFnoVQnqaA=="],
-
    "pkg-dir/find-up/locate-path/p-locate": ["p-locate@4.1.0", "", { "dependencies": { "p-limit": "^2.2.0" } }, "sha512-R79ZZ/0wAxKGu3oYMlz8jy/kbhsNrS7SKZ7PxEHBgJ5+F2mtFW2fK2cOtBh1cHYkQsbzFV7I+EoRKe6Yt0oK7A=="],

    "pkg-up/find-up/locate-path/p-locate": ["p-locate@3.0.0", "", { "dependencies": { "p-limit": "^2.0.0" } }, "sha512-x+12w/To+4GFfgJhBEpiDcLozRJGegY+Ei7/z0tSLkMmxGZNybVMSfWj9aJn8Z5Fc7dBUNJOOVgPv2H7IwulSQ=="],
@@ -7003,6 +6977,16 @@

    "@aws-sdk/client-cognito-identity/@aws-sdk/core/@aws-sdk/xml-builder/fast-xml-parser/strnum": ["strnum@2.2.3", "", {}, "sha512-oKx6RUCuHfT3oyVjtnrmn19H1SiCqgJSg+54XqURKp5aCMbrXrhLjRN9TjuwMjiYstZ0MzDrHqkGZ5dFTKd+zg=="],

+    "@aws-sdk/client-lambda/@aws-sdk/core/@aws-sdk/xml-builder/fast-xml-parser/fast-xml-builder": ["fast-xml-builder@1.2.0", "", { "dependencies": { "path-expression-matcher": "^1.5.0", "xml-naming": "^0.1.0" } }, "sha512-00aAWieqff+ZJhsXA4g1g7M8k+7AYoMUUHF+/zFb5U6Uv/P0Vl4QZo84/IcufzYalLuEj9928bXN9PbbFzMF0Q=="],
+
+    "@aws-sdk/client-lambda/@aws-sdk/core/@aws-sdk/xml-builder/fast-xml-parser/strnum": ["strnum@2.2.3", "", {}, "sha512-oKx6RUCuHfT3oyVjtnrmn19H1SiCqgJSg+54XqURKp5aCMbrXrhLjRN9TjuwMjiYstZ0MzDrHqkGZ5dFTKd+zg=="],
+
+    "@aws-sdk/client-lambda/@aws-sdk/credential-provider-node/@aws-sdk/credential-provider-ini/@aws-sdk/nested-clients/@aws-sdk/signature-v4-multi-region": ["@aws-sdk/signature-v4-multi-region@3.996.27", "", { "dependencies": { "@aws-sdk/types": "^3.973.8", "@smithy/core": "^3.24.2", "@smithy/signature-v4": "^5.4.2", "@smithy/types": "^4.14.1", "tslib": "^2.6.2" } }, "sha512-0Phbz4t6HI3D3skxvG2uI+VWU034/nSIw1T8d+FPzzQG9EQTrw94o9mOKO2Gv3n3Oc8P7JD7RAUxkoneLWv5Eg=="],
+
+    "@aws-sdk/client-lambda/@aws-sdk/credential-provider-node/@aws-sdk/credential-provider-sso/@aws-sdk/nested-clients/@aws-sdk/signature-v4-multi-region": ["@aws-sdk/signature-v4-multi-region@3.996.27", "", { "dependencies": { "@aws-sdk/types": "^3.973.8", "@smithy/core": "^3.24.2", "@smithy/signature-v4": "^5.4.2", "@smithy/types": "^4.14.1", "tslib": "^2.6.2" } }, "sha512-0Phbz4t6HI3D3skxvG2uI+VWU034/nSIw1T8d+FPzzQG9EQTrw94o9mOKO2Gv3n3Oc8P7JD7RAUxkoneLWv5Eg=="],
+
+    "@aws-sdk/client-lambda/@aws-sdk/credential-provider-node/@aws-sdk/credential-provider-web-identity/@aws-sdk/nested-clients/@aws-sdk/signature-v4-multi-region": ["@aws-sdk/signature-v4-multi-region@3.996.27", "", { "dependencies": { "@aws-sdk/types": "^3.973.8", "@smithy/core": "^3.24.2", "@smithy/signature-v4": "^5.4.2", "@smithy/types": "^4.14.1", "tslib": "^2.6.2" } }, "sha512-0Phbz4t6HI3D3skxvG2uI+VWU034/nSIw1T8d+FPzzQG9EQTrw94o9mOKO2Gv3n3Oc8P7JD7RAUxkoneLWv5Eg=="],
+
    "@aws-sdk/client-sts/@aws-sdk/credential-provider-node/@aws-sdk/credential-provider-ini/@aws-sdk/nested-clients/@smithy/util-utf8": ["@smithy/util-utf8@4.2.2", "", { "dependencies": { "@smithy/util-buffer-from": "^4.2.2", "tslib": "^2.6.2" } }, "sha512-75MeYpjdWRe8M5E3AW0O4Cx3UadweS+cwdXjwYGBW5h/gxxnbeZ877sLPX/ZJA9GVTlL/qG0dXP29JWFCD1Ayw=="],

    "@aws-sdk/client-sts/@aws-sdk/credential-provider-node/@aws-sdk/credential-provider-sso/@aws-sdk/client-sso/@smithy/util-utf8": ["@smithy/util-utf8@4.2.2", "", { "dependencies": { "@smithy/util-buffer-from": "^4.2.2", "tslib": "^2.6.2" } }, "sha512-75MeYpjdWRe8M5E3AW0O4Cx3UadweS+cwdXjwYGBW5h/gxxnbeZ877sLPX/ZJA9GVTlL/qG0dXP29JWFCD1Ayw=="],
@@ -7077,8 +7061,6 @@

    "js-beautify/glob/minimatch/brace-expansion/balanced-match": ["balanced-match@1.0.2", "", {}, "sha512-3oSeUO0TMV67hN1AmbXsK4yaqU7tjiHlbxRDZOpH0KW9+CeX4bRAaX0Anxt0tx2MrpRpWwQaPwIlISEJhYU5Pw=="],

-    "opencontrol/@modelcontextprotocol/sdk/express/type-is/media-typer": ["media-typer@1.1.0", "", {}, "sha512-aisnrDP4GNe06UcKFnV5bfMNPBUw4jsLGaWwWfnH3v02GnBuXX2MCVn5RbrWo0j3pczUilYblq7fQ7Nw2t5XKw=="],
-
    "pkg-dir/find-up/locate-path/p-locate/p-limit": ["p-limit@2.3.0", "", { "dependencies": { "p-try": "^2.0.0" } }, "sha512-//88mFWSJx8lxCzwdAABTJL2MyWB12+eIY7MDL2SqLmAkeKU9qxRvWuSyTjm3FUmpBEMuFfckAIqEaVGUDxb6w=="],

    "pkg-up/find-up/locate-path/p-locate/p-limit": ["p-limit@2.3.0", "", { "dependencies": { "p-try": "^2.0.0" } }, "sha512-//88mFWSJx8lxCzwdAABTJL2MyWB12+eIY7MDL2SqLmAkeKU9qxRvWuSyTjm3FUmpBEMuFfckAIqEaVGUDxb6w=="],
@@ -7087,6 +7069,12 @@

    "tw-to-css/tailwindcss/chokidar/readdirp/picomatch": ["picomatch@2.3.2", "", {}, "sha512-V7+vQEJ06Z+c5tSye8S+nHUfI51xoXIXjHQ99cQtKUkQqqO1kO/KCJUfZXuB47h/YBlDhah2H3hdUGXn8ie0oA=="],

+    "@aws-sdk/client-lambda/@aws-sdk/credential-provider-node/@aws-sdk/credential-provider-ini/@aws-sdk/nested-clients/@aws-sdk/signature-v4-multi-region/@smithy/signature-v4": ["@smithy/signature-v4@5.4.3", "", { "dependencies": { "@smithy/core": "^3.24.3", "@smithy/types": "^4.14.2", "tslib": "^2.6.2" } }, "sha512-53+75QuPl6DL+ct6vVEB51FDO5oulXr20TPV46VvJZg76lIlXNWfxi8j+G2V/t0I2qxCBOa3vX/8bmjrpFVo9g=="],
+
+    "@aws-sdk/client-lambda/@aws-sdk/credential-provider-node/@aws-sdk/credential-provider-sso/@aws-sdk/nested-clients/@aws-sdk/signature-v4-multi-region/@smithy/signature-v4": ["@smithy/signature-v4@5.4.3", "", { "dependencies": { "@smithy/core": "^3.24.3", "@smithy/types": "^4.14.2", "tslib": "^2.6.2" } }, "sha512-53+75QuPl6DL+ct6vVEB51FDO5oulXr20TPV46VvJZg76lIlXNWfxi8j+G2V/t0I2qxCBOa3vX/8bmjrpFVo9g=="],
+
+    "@aws-sdk/client-lambda/@aws-sdk/credential-provider-node/@aws-sdk/credential-provider-web-identity/@aws-sdk/nested-clients/@aws-sdk/signature-v4-multi-region/@smithy/signature-v4": ["@smithy/signature-v4@5.4.3", "", { "dependencies": { "@smithy/core": "^3.24.3", "@smithy/types": "^4.14.2", "tslib": "^2.6.2" } }, "sha512-53+75QuPl6DL+ct6vVEB51FDO5oulXr20TPV46VvJZg76lIlXNWfxi8j+G2V/t0I2qxCBOa3vX/8bmjrpFVo9g=="],
+
    "@aws-sdk/client-sts/@aws-sdk/credential-provider-node/@aws-sdk/credential-provider-sso/@aws-sdk/token-providers/@aws-sdk/nested-clients/@smithy/util-utf8": ["@smithy/util-utf8@4.2.2", "", { "dependencies": { "@smithy/util-buffer-from": "^4.2.2", "tslib": "^2.6.2" } }, "sha512-75MeYpjdWRe8M5E3AW0O4Cx3UadweS+cwdXjwYGBW5h/gxxnbeZ877sLPX/ZJA9GVTlL/qG0dXP29JWFCD1Ayw=="],

    "@aws-sdk/credential-provider-cognito-identity/@aws-sdk/nested-clients/@aws-sdk/core/@aws-sdk/xml-builder/fast-xml-parser/strnum": ["strnum@2.2.3", "", {}, "sha512-oKx6RUCuHfT3oyVjtnrmn19H1SiCqgJSg+54XqURKp5aCMbrXrhLjRN9TjuwMjiYstZ0MzDrHqkGZ5dFTKd+zg=="],
@@ -4,7 +4,7 @@ import { domain } from "./stage"
 const description = "Managed by SST (Don't edit in Honeycomb UI)"
 const alertsDisabled = $app.stage !== "production"

-const webhookRecipient = new honeycomb.WebhookRecipient("DiscordAlerts", {
+const webhookRecipient = new honeycombio.WebhookRecipient("DiscordAlerts", {
  name: $app.stage === "production" ? "Discord Alerts" : `Discord Alerts (${$app.stage})`,
  url: `https://${domain}/honeycomb/webhook`,
  secret: SECRET.HoneycombWebhookSecret.result,
@@ -67,7 +67,7 @@ IF(
 )`,
  })

-  return honeycomb.getQuerySpecificationOutput({
+  return honeycombio.getQuerySpecificationOutput({
    breakdowns: ["model"],
    calculatedFields: [failedHttpStatus],
    calculations: [
@@ -99,7 +99,7 @@ const providerHttpErrorsQuery = () => {
    expression: `IF(GT($llm.error.code, "400"), 1, 0)`,
  })

-  return honeycomb.getQuerySpecificationOutput({
+  return honeycombio.getQuerySpecificationOutput({
    breakdowns: ["provider"],
    calculatedFields: [successHttpStatus, failedProviderHttpStatus],
    calculations: [
@@ -140,7 +140,7 @@ const modelLowTpsQuery = (product: "go" | "zen") => {
    { column: "tps.output", op: "exists" },
  ]

-  return honeycomb.getQuerySpecificationOutput({
+  return honeycombio.getQuerySpecificationOutput({
    breakdowns: ["model"],
    calculations: [
      { op: "COUNT", name: "TOTAL", filterCombination: "AND", filters },
@@ -157,7 +157,7 @@ const modelLowTpsQuery = (product: "go" | "zen") => {
  }).json
 }

-new honeycomb.Trigger("IncreasedModelHttpErrorsGo", {
+new honeycombio.Trigger("IncreasedModelHttpErrorsGo", {
  name: "Increased Model HTTP Errors [Go]",
  description,
  disabled: alertsDisabled,
@@ -177,7 +177,7 @@ new honeycomb.Trigger("IncreasedModelHttpErrorsGo", {
  ],
 })

-new honeycomb.Trigger("IncreasedModelHttpErrorsZen", {
+new honeycombio.Trigger("IncreasedModelHttpErrorsZen", {
  name: "Increased Model HTTP Errors [Zen]",
  description,
  disabled: alertsDisabled,
@@ -197,7 +197,7 @@ new honeycomb.Trigger("IncreasedModelHttpErrorsZen", {
  ],
 })

-new honeycomb.Trigger("LowModelTpsGo", {
+new honeycombio.Trigger("LowModelTpsGo", {
  name: "Low Model TPS [Go]",
  description,
  disabled: alertsDisabled,
@@ -217,7 +217,7 @@ new honeycomb.Trigger("LowModelTpsGo", {
  ],
 })

-new honeycomb.Trigger("LowModelTpsZen", {
+new honeycombio.Trigger("LowModelTpsZen", {
  name: "Low Model TPS [Zen]",
  description,
  disabled: alertsDisabled,
@@ -237,7 +237,7 @@ new honeycomb.Trigger("LowModelTpsZen", {
  ],
 })

-new honeycomb.Trigger("IncreasedProviderHttpErrors", {
+new honeycombio.Trigger("IncreasedProviderHttpErrors", {
  name: "Increased Provider HTTP Errors",
  description,
  disabled: alertsDisabled,
@@ -257,11 +257,11 @@ new honeycomb.Trigger("IncreasedProviderHttpErrors", {
  ],
 })

-new honeycomb.Trigger("IncreasedFreeTierRequests", {
+new honeycombio.Trigger("IncreasedFreeTierRequests", {
  name: "Increased Free Tier Requests",
  description,
  disabled: alertsDisabled,
-  queryJson: honeycomb.getQuerySpecificationOutput({
+  queryJson: honeycombio.getQuerySpecificationOutput({
    calculations: [{ op: "COUNT" }],
    filters: [
      { column: "event_type", op: "=", value: "completions" },
@@ -1,8 +1,8 @@
 {
  "nodeModules": {
-    "x86_64-linux": "sha256-hIarzU3QNIvkwpfnearfsGaBMCSdovkOWAuvX+EBQI8=",
-    "aarch64-linux": "sha256-qu+86RNsBZhqzE3CEyg4XHD/3Czc/BqHhY3O1vyogtY=",
-    "aarch64-darwin": "sha256-7sXZdPh/R4fQBBMq36YdpQE6G2ELMZd08BqMhHbhwv4=",
-    "x86_64-darwin": "sha256-g5QWpX33R143sNR1G9m7UsSA3jygFyJjT7Kjyjo6sCc="
+    "x86_64-linux": "sha256-1RiaZQHzIhdtcOJUMsLagpP+nBBL/Qu6zQgrAXMHDCI=",
+    "aarch64-linux": "sha256-5QZhtkWuNpY/qUxlKRHcGbILOAVnuyzu+h8VDIuMQcU=",
+    "aarch64-darwin": "sha256-9w3QA22XNc1itGLyhikYU90xGH/iLUUM+SSGXla7lhw=",
+    "x86_64-darwin": "sha256-cSYiyhhSqIYiTeK1uWHDkHbYstQYD5jEB7JaYjWjgi4="
  }
 }
@@ -98,7 +98,7 @@
    "oxlint-tsgolint": "0.21.0",
    "prettier": "3.6.2",
    "semver": "^7.6.0",
-    "sst": "3.18.10",
+    "sst": "4.13.1",
    "turbo": "2.8.13"
  },
  "dependencies": {
@@ -1,6 +1,6 @@
 {
  "name": "@opencode-ai/app",
-  "version": "1.15.6",
+  "version": "1.15.7",
  "description": "",
  "type": "module",
  "exports": {
@@ -1,6 +1,6 @@
 {
  "name": "@opencode-ai/console-app",
-  "version": "1.15.6",
+  "version": "1.15.7",
  "type": "module",
  "license": "MIT",
  "scripts": {
@@ -348,8 +348,8 @@ export const dict = {
    "Free models include Big Pickle plus promotional models available at the time, with a quota of 200 requests/day. Go includes GLM-5.1, GLM-5, Kimi K2.5, Kimi K2.6, MiMo-V2.5-Pro, MiMo-V2.5, Qwen3.5 Plus, Qwen3.6 Plus, MiniMax M2.5, MiniMax M2.7, DeepSeek V4 Pro, and DeepSeek V4 Flash with higher request quotas enforced across rolling windows (5-hour, weekly, and monthly), roughly equivalent to $12 per 5 hours, $30 per week, and $60 per month (actual request counts vary by model and usage).",

  "zen.api.error.rateLimitExceeded": "Rate limit exceeded. Please try again later.",
-  "zen.api.error.modelNotSupported": "Model {{model}} not supported",
-  "zen.api.error.modelFormatNotSupported": "Model {{model}} not supported for format {{format}}",
+  "zen.api.error.modelNotSupported": "Model {{model}} is not supported",
+  "zen.api.error.modelFormatNotSupported": "Model {{model}} is not supported for format {{format}}",
  "zen.api.error.noProviderAvailable": "No provider available",
  "zen.api.error.providerNotSupported": "Provider {{provider}} not supported",
  "zen.api.error.missingApiKey": "Missing API key.",
@@ -1,7 +1,7 @@
 {
  "$schema": "https://json.schemastore.org/package.json",
  "name": "@opencode-ai/console-core",
-  "version": "1.15.6",
+  "version": "1.15.7",
  "private": true,
  "type": "module",
  "license": "MIT",
@@ -1,6 +1,6 @@
 {
  "name": "@opencode-ai/console-function",
-  "version": "1.15.6",
+  "version": "1.15.7",
  "$schema": "https://json.schemastore.org/package.json",
  "private": true,
  "type": "module",
@@ -1,6 +1,6 @@
 {
  "name": "@opencode-ai/console-mail",
-  "version": "1.15.6",
+  "version": "1.15.7",
  "dependencies": {
    "@jsx-email/all": "2.2.3",
    "@jsx-email/cli": "1.4.3",
@@ -1,6 +1,6 @@
 {
  "$schema": "https://json.schemastore.org/package.json",
-  "version": "1.15.6",
+  "version": "1.15.7",
  "name": "@opencode-ai/core",
  "type": "module",
  "license": "MIT",
@@ -59,7 +59,7 @@
    "ai-gateway-provider": "3.1.2",
    "cross-spawn": "catalog:",
    "effect": "catalog:",
-    "gitlab-ai-provider": "6.6.0",
+    "gitlab-ai-provider": "6.7.0",
    "glob": "13.0.5",
    "google-auth-library": "10.5.0",
    "immer": "11.1.4",
@@ -1,7 +1,7 @@
 {
  "name": "@opencode-ai/desktop",
  "private": true,
-  "version": "1.15.6",
+  "version": "1.15.7",
  "type": "module",
  "license": "MIT",
  "homepage": "https://opencode.ai",
@@ -1,6 +1,6 @@
 {
  "$schema": "https://json.schemastore.org/package.json",
-  "version": "1.15.5",
+  "version": "1.15.7",
  "name": "@opencode-ai/effect-drizzle-sqlite",
  "type": "module",
  "license": "MIT",
@@ -0,0 +1,10 @@
+/* This file is auto-generated by SST. Do not edit. */
+/* tslint:disable */
+/* eslint-disable */
+/* deno-fmt-ignore-file */
+/* biome-ignore-all lint: auto-generated */
+
+/// <reference path="../../sst-env.d.ts" />
+
+import "sst"
+export {}
@@ -1,6 +1,6 @@
 {
  "name": "@opencode-ai/enterprise",
-  "version": "1.15.6",
+  "version": "1.15.7",
  "private": true,
  "type": "module",
  "license": "MIT",
@@ -1,7 +1,7 @@
 id = "opencode"
 name = "OpenCode"
 description = "The open source coding agent."
-version = "1.15.6"
+version = "1.15.7"
 schema_version = 1
 authors = ["Anomaly"]
 repository = "https://github.com/anomalyco/opencode"
@@ -11,26 +11,26 @@ name = "OpenCode"
 icon = "./icons/opencode.svg"

 [agent_servers.opencode.targets.darwin-aarch64]
-archive = "https://github.com/anomalyco/opencode/releases/download/v1.15.6/opencode-darwin-arm64.zip"
+archive = "https://github.com/anomalyco/opencode/releases/download/v1.15.7/opencode-darwin-arm64.zip"
 cmd = "./opencode"
 args = ["acp"]

 [agent_servers.opencode.targets.darwin-x86_64]
-archive = "https://github.com/anomalyco/opencode/releases/download/v1.15.6/opencode-darwin-x64.zip"
+archive = "https://github.com/anomalyco/opencode/releases/download/v1.15.7/opencode-darwin-x64.zip"
 cmd = "./opencode"
 args = ["acp"]

 [agent_servers.opencode.targets.linux-aarch64]
-archive = "https://github.com/anomalyco/opencode/releases/download/v1.15.6/opencode-linux-arm64.tar.gz"
+archive = "https://github.com/anomalyco/opencode/releases/download/v1.15.7/opencode-linux-arm64.tar.gz"
 cmd = "./opencode"
 args = ["acp"]

 [agent_servers.opencode.targets.linux-x86_64]
-archive = "https://github.com/anomalyco/opencode/releases/download/v1.15.6/opencode-linux-x64.tar.gz"
+archive = "https://github.com/anomalyco/opencode/releases/download/v1.15.7/opencode-linux-x64.tar.gz"
 cmd = "./opencode"
 args = ["acp"]

 [agent_servers.opencode.targets.windows-x86_64]
-archive = "https://github.com/anomalyco/opencode/releases/download/v1.15.6/opencode-windows-x64.zip"
+archive = "https://github.com/anomalyco/opencode/releases/download/v1.15.7/opencode-windows-x64.zip"
 cmd = "./opencode.exe"
 args = ["acp"]
@@ -1,6 +1,6 @@
 {
  "name": "@opencode-ai/function",
-  "version": "1.15.6",
+  "version": "1.15.7",
  "$schema": "https://json.schemastore.org/package.json",
  "private": true,
  "type": "module",
@@ -1,6 +1,6 @@
 {
  "$schema": "https://json.schemastore.org/package.json",
-  "version": "1.15.6",
+  "version": "1.15.7",
  "name": "@opencode-ai/http-recorder",
  "type": "module",
  "license": "MIT",
@@ -1,6 +1,6 @@
 {
  "$schema": "https://json.schemastore.org/package.json",
-  "version": "1.15.6",
+  "version": "1.15.7",
  "name": "@opencode-ai/llm",
  "type": "module",
  "license": "MIT",
@@ -10,6 +10,7 @@ import {
  type CacheHint,
  type FinishReason,
  type LLMRequest,
+  type MediaPart,
  type ProviderMetadata,
  type ToolCallPart,
  type ToolDefinition,
@@ -39,6 +40,17 @@ const AnthropicTextBlock = Schema.Struct({
 })
 type AnthropicTextBlock = Schema.Schema.Type<typeof AnthropicTextBlock>

+const AnthropicImageBlock = Schema.Struct({
+  type: Schema.tag("image"),
+  source: Schema.Struct({
+    type: Schema.tag("base64"),
+    media_type: Schema.String,
+    data: Schema.String,
+  }),
+  cache_control: Schema.optional(AnthropicCacheControl),
+})
+type AnthropicImageBlock = Schema.Schema.Type<typeof AnthropicImageBlock>
+
 const AnthropicThinkingBlock = Schema.Struct({
  type: Schema.tag("thinking"),
  thinking: Schema.String,
@@ -92,7 +104,8 @@ const AnthropicToolResultBlock = Schema.Struct({
  cache_control: Schema.optional(AnthropicCacheControl),
 })

-const AnthropicUserBlock = Schema.Union([AnthropicTextBlock, AnthropicToolResultBlock])
+const AnthropicUserBlock = Schema.Union([AnthropicTextBlock, AnthropicImageBlock, AnthropicToolResultBlock])
+type AnthropicUserBlock = Schema.Schema.Type<typeof AnthropicUserBlock>
 const AnthropicAssistantBlock = Schema.Union([
  AnthropicTextBlock,
  AnthropicThinkingBlock,
@@ -272,6 +285,19 @@ const lowerServerToolResult = Effect.fn("AnthropicMessages.lowerServerToolResult
  return { type: wireType, tool_use_id: part.id, content: part.result.value } satisfies AnthropicServerToolResultBlock
 })

+const lowerImage = Effect.fn("AnthropicMessages.lowerImage")(function* (part: MediaPart) {
+  if (!part.mediaType.startsWith("image/"))
+    return yield* invalid(`Anthropic Messages user media content only supports images`)
+  return {
+    type: "image" as const,
+    source: {
+      type: "base64" as const,
+      media_type: part.mediaType,
+      data: ProviderShared.mediaBase64(part),
+    },
+  } satisfies AnthropicImageBlock
+})
+
 const lowerMessages = Effect.fn("AnthropicMessages.lowerMessages")(function* (
  request: LLMRequest,
  breakpoints: Cache.Breakpoints,
@@ -280,11 +306,17 @@ const lowerMessages = Effect.fn("AnthropicMessages.lowerMessages")(function* (

  for (const message of request.messages) {
    if (message.role === "user") {
-      const content: AnthropicTextBlock[] = []
+      const content: AnthropicUserBlock[] = []
      for (const part of message.content) {
-        if (!ProviderShared.supportsContent(part, ["text"]))
-          return yield* ProviderShared.unsupportedContent("Anthropic Messages", "user", ["text"])
-        content.push({ type: "text", text: part.text, cache_control: cacheControl(breakpoints, part.cache) })
+        if (part.type === "text") {
+          content.push({ type: "text", text: part.text, cache_control: cacheControl(breakpoints, part.cache) })
+          continue
+        }
+        if (part.type === "media") {
+          content.push(yield* lowerImage(part))
+          continue
+        }
+        return yield* ProviderShared.unsupportedContent("Anthropic Messages", "user", ["text", "media"])
      }
      messages.push({ role: "user", content })
      continue
@@ -6,11 +6,11 @@ import { HttpTransport, WebSocketTransport } from "../route/transport"
 import { Protocol } from "../route/protocol"
 import {
  LLMEvent,
-  type MediaPart,
  Usage,
  type FinishReason,
  type LLMRequest,
  type ProviderMetadata,
+  type ReasoningPart,
  type TextPart,
  type ToolCallPart,
  type ToolDefinition,
@@ -43,10 +43,23 @@ const OpenAIResponsesOutputText = Schema.Struct({
  text: Schema.String,
 })

+const OpenAIResponsesReasoningSummaryText = Schema.Struct({
+  type: Schema.tag("summary_text"),
+  text: Schema.String,
+})
+
+const OpenAIResponsesReasoningItem = Schema.Struct({
+  type: Schema.tag("reasoning"),
+  id: Schema.String,
+  summary: Schema.Array(OpenAIResponsesReasoningSummaryText),
+  encrypted_content: optionalNull(Schema.String),
+})
+
 const OpenAIResponsesInputItem = Schema.Union([
  Schema.Struct({ role: Schema.tag("system"), content: Schema.String }),
  Schema.Struct({ role: Schema.tag("user"), content: Schema.Array(OpenAIResponsesInputContent) }),
  Schema.Struct({ role: Schema.tag("assistant"), content: Schema.Array(OpenAIResponsesOutputText) }),
+  OpenAIResponsesReasoningItem,
  Schema.Struct({
    type: Schema.tag("function_call"),
    call_id: Schema.String,
@@ -149,6 +162,7 @@ const OpenAIResponsesStreamItem = Schema.Struct({
  server_label: Schema.optional(Schema.String),
  output: Schema.optional(Schema.Unknown),
  error: Schema.optional(Schema.Unknown),
+  encrypted_content: optionalNull(Schema.String),
 })
 type OpenAIResponsesStreamItem = Schema.Schema.Type<typeof OpenAIResponsesStreamItem>

@@ -206,17 +220,31 @@ const lowerToolCall = (part: ToolCallPart): OpenAIResponsesInputItem => ({
  arguments: ProviderShared.encodeJson(part.input),
 })

-const imageUrl = (part: MediaPart) =>
-  typeof part.data === "string" && part.data.startsWith("data:")
-    ? part.data
-    : `data:${part.mediaType};base64,${ProviderShared.mediaBytes(part)}`
+const lowerReasoning = (part: ReasoningPart, store: boolean | undefined): OpenAIResponsesInputItem | undefined => {
+  const openai = part.providerMetadata?.openai
+  if (!ProviderShared.isRecord(openai) || typeof openai.itemId !== "string") return undefined
+  // With store:false, OpenAI only accepts previous reasoning items when the
+  // encrypted state is present. Bare rs_* ids point to non-persisted items.
+  if (store === false && typeof openai.reasoningEncryptedContent !== "string") return undefined
+  return {
+    type: "reasoning",
+    id: openai.itemId,
+    summary: part.text.length > 0 ? [{ type: "summary_text", text: part.text }] : [],
+    encrypted_content:
+      typeof openai.reasoningEncryptedContent === "string"
+        ? openai.reasoningEncryptedContent
+        : openai.reasoningEncryptedContent === null
+          ? null
+          : undefined,
+  }
+}

 const lowerUserContent = Effect.fn("OpenAIResponses.lowerUserContent")(function* (
  part: LLMRequest["messages"][number]["content"][number],
 ) {
  if (part.type === "text") return { type: "input_text" as const, text: part.text }
  if (part.type === "media" && part.mediaType.startsWith("image/")) {
-    return { type: "input_image" as const, image_url: imageUrl(part) }
+    return { type: "input_image" as const, image_url: ProviderShared.mediaDataUrl(part) }
  }
  if (part.type === "media") return yield* invalid("OpenAI Responses user media content only supports images")
  return yield* ProviderShared.unsupportedContent("OpenAI Responses", "user", ["text", "media"])
@@ -226,6 +254,7 @@ const lowerMessages = Effect.fn("OpenAIResponses.lowerMessages")(function* (requ
  const system: OpenAIResponsesInputItem[] =
    request.system.length === 0 ? [] : [{ role: "system", content: ProviderShared.joinText(request.system) }]
  const input: OpenAIResponsesInputItem[] = [...system]
+  const store = OpenAIOptions.store(request)

  for (const message of request.messages) {
    if (message.role === "user") {
@@ -235,20 +264,34 @@ const lowerMessages = Effect.fn("OpenAIResponses.lowerMessages")(function* (requ

    if (message.role === "assistant") {
      const content: TextPart[] = []
+      const flushText = () => {
+        if (content.length === 0) return
+        input.push({ role: "assistant", content: content.map((part) => ({ type: "output_text", text: part.text })) })
+        content.splice(0, content.length)
+      }
      for (const part of message.content) {
-        if (!ProviderShared.supportsContent(part, ["text", "tool-call"]))
-          return yield* ProviderShared.unsupportedContent("OpenAI Responses", "assistant", ["text", "tool-call"])
        if (part.type === "text") {
          content.push(part)
          continue
        }
+        if (part.type === "reasoning") {
+          flushText()
+          const reasoning = lowerReasoning(part, store)
+          if (reasoning) input.push(reasoning)
+          continue
+        }
        if (part.type === "tool-call") {
+          flushText()
          input.push(lowerToolCall(part))
          continue
        }
+        return yield* ProviderShared.unsupportedContent("OpenAI Responses", "assistant", [
+          "text",
+          "reasoning",
+          "tool-call",
+        ])
      }
-      if (content.length > 0)
-        input.push({ role: "assistant", content: content.map((part) => ({ type: "output_text", text: part.text })) })
+      flushText()
      continue
    }

@@ -367,6 +410,11 @@ const isHostedToolItem = (
 ): item is OpenAIResponsesStreamItem & { type: HostedToolType; id: string } =>
  item.type in HOSTED_TOOLS && typeof item.id === "string" && item.id.length > 0

+const isReasoningItem = (
+  item: OpenAIResponsesStreamItem,
+): item is OpenAIResponsesStreamItem & { type: "reasoning"; id: string } =>
+  item.type === "reasoning" && typeof item.id === "string" && item.id.length > 0
+
 // Round-trip the full item as the structured result so consumers can extract
 // outputs / sources / status without re-decoding.
 const hostedToolResult = (item: OpenAIResponsesStreamItem) => {
@@ -428,16 +476,12 @@ const onReasoningDelta = (state: ParserState, event: OpenAIResponsesEvent): Step
  ]
 }

-const onReasoningDone = (state: ParserState, event: OpenAIResponsesEvent): StepResult => {
-  const events: LLMEvent[] = []
-  return [
-    {
-      ...state,
-      lifecycle: Lifecycle.reasoningEnd(state.lifecycle, events, event.item_id ?? "reasoning-0"),
-    },
-    events,
-  ]
-}
+// The summary done event does not carry encrypted continuation state. Finish the
+// common reasoning block when the full reasoning item arrives in output_item.done.
+const onReasoningDone = (state: ParserState, _event: OpenAIResponsesEvent): StepResult => [state, NO_EVENTS]
+
+const reasoningMetadata = (item: OpenAIResponsesStreamItem & { id: string }) =>
+  openaiMetadata({ itemId: item.id, reasoningEncryptedContent: item.encrypted_content ?? null })

 const onOutputItemAdded = (state: ParserState, event: OpenAIResponsesEvent): StepResult => {
  const item = event.item
@@ -518,6 +562,21 @@ const onOutputItemDone = Effect.fn("OpenAIResponses.onOutputItemDone")(function*
    return [{ ...state, lifecycle }, events] satisfies StepResult
  }

+  if (isReasoningItem(item)) {
+    const events: LLMEvent[] = []
+    const providerMetadata = reasoningMetadata(item)
+    if (!state.lifecycle.reasoning.has(item.id)) {
+      const lifecycle = Lifecycle.stepStart(state.lifecycle, events)
+      events.push(LLMEvent.reasoningStart({ id: item.id, providerMetadata }))
+      events.push(LLMEvent.reasoningEnd({ id: item.id, providerMetadata }))
+      return [{ ...state, lifecycle }, events] satisfies StepResult
+    }
+    return [
+      { ...state, lifecycle: Lifecycle.reasoningEnd(state.lifecycle, events, item.id, providerMetadata) },
+      events,
+    ] satisfies StepResult
+  }
+
  return [state, NO_EVENTS] satisfies StepResult
 })

@@ -80,7 +80,7 @@ export const subtractTokens = (total: number | undefined, subtrahend: number | u
 */
 export const sumTokens = (...values: ReadonlyArray<number | undefined>): number | undefined => {
  if (values.every((value) => value === undefined)) return undefined
-  return values.reduce<number>((acc, value) => acc + (value ?? 0), 0)
+  return values.reduce((acc: number, value) => acc + (value ?? 0), 0)
 }

 export const eventError = (route: string, message: string, raw?: string) =>
@@ -122,6 +122,16 @@ export const parseToolInput = (route: string, name: string, raw: string) =>
 export const mediaBytes = (part: MediaPart) =>
  typeof part.data === "string" ? part.data : Buffer.from(part.data).toString("base64")

+export const mediaBase64 = (part: MediaPart) => {
+  if (typeof part.data !== "string" || !part.data.startsWith("data:")) return mediaBytes(part)
+  return part.data.slice(part.data.indexOf(",") + 1)
+}
+
+export const mediaDataUrl = (part: MediaPart) =>
+  typeof part.data === "string" && part.data.startsWith("data:")
+    ? part.data
+    : `data:${part.mediaType};base64,${mediaBytes(part)}`
+
 export const trimBaseUrl = (value: string) => value.replace(/\/+$/, "")

 export const toolResultText = (part: ToolResultPart) => {
@@ -0,0 +1,104 @@
+import { LLM, Message, ToolCallPart, ToolDefinition, ToolResultPart, type ContentPart, type Model } from "../src"
+
+export const basicContinuation = ["system", "user-text", "assistant-text", "user-follow-up"] as const
+export const toolContinuation = ["tool-call", "tool-result"] as const
+export const reasoningContinuation = ["assistant-reasoning", "encrypted-reasoning"] as const
+export const mediaContinuation = ["user-image"] as const
+export const maximalContinuation = [
+  ...basicContinuation,
+  ...toolContinuation,
+  ...reasoningContinuation,
+  ...mediaContinuation,
+] as const
+
+export type ContinuationFeature = (typeof maximalContinuation)[number]
+
+export const nativeOpenAIResponsesContinuation = [
+  ...basicContinuation,
+  ...toolContinuation,
+  "encrypted-reasoning",
+  ...mediaContinuation,
+] as const satisfies ReadonlyArray<ContinuationFeature>
+
+export const nativeAnthropicMessagesContinuation = [
+  ...basicContinuation,
+  ...toolContinuation,
+  "assistant-reasoning",
+  ...mediaContinuation,
+] as const satisfies ReadonlyArray<ContinuationFeature>
+
+export const continuationTool = ToolDefinition.make({
+  name: "get_weather",
+  description: "Get current weather for a city.",
+  inputSchema: {
+    type: "object",
+    properties: { city: { type: "string" } },
+    required: ["city"],
+    additionalProperties: false,
+  },
+})
+
+export function continuationRequest(input: {
+  readonly id: string
+  readonly model: Model
+  readonly features: ReadonlyArray<ContinuationFeature>
+  readonly image?: string
+}) {
+  const features = new Set(input.features)
+  const messages = []
+  const firstUser: ContentPart[] = []
+  const firstAssistant: ContentPart[] = []
+
+  if (features.has("user-text")) firstUser.push({ type: "text", text: "What is shown here?" })
+  if (features.has("user-image"))
+    firstUser.push({ type: "media", mediaType: "image/png", data: input.image ?? "AAECAw==" })
+  if (firstUser.length > 0) messages.push(Message.user(firstUser))
+
+  if (features.has("assistant-reasoning"))
+    firstAssistant.push({
+      type: "reasoning",
+      text: "I inspected the previous turn.",
+      providerMetadata: { anthropic: { signature: "sig_continuation_1" } },
+    })
+  if (features.has("encrypted-reasoning"))
+    firstAssistant.push({
+      type: "reasoning",
+      text: "I inspected the previous turn.",
+      providerMetadata: {
+        openai: {
+          itemId: "rs_continuation_1",
+          reasoningEncryptedContent: "encrypted-continuation-state",
+        },
+      },
+    })
+  if (features.has("assistant-text")) firstAssistant.push({ type: "text", text: "It shows a small test image." })
+  if (firstAssistant.length > 0) messages.push(Message.assistant(firstAssistant))
+
+  if (features.has("tool-call")) {
+    messages.push(Message.user("Check the weather in Paris before continuing."))
+    messages.push(
+      Message.assistant([ToolCallPart.make({ id: "call_weather_1", name: "get_weather", input: { city: "Paris" } })]),
+    )
+  }
+  if (features.has("tool-result")) {
+    messages.push(
+      Message.tool(ToolResultPart.make({ id: "call_weather_1", name: "get_weather", result: { temperature: 22 } })),
+    )
+    if (features.has("assistant-text")) messages.push(Message.assistant("Paris is 22 degrees."))
+  }
+  if (features.has("user-follow-up"))
+    messages.push(Message.user("Continue from this conversation in one short sentence."))
+
+  return LLM.request({
+    id: input.id,
+    model: input.model,
+    system: features.has("system") ? "You are concise. Continue from the provided history." : undefined,
+    messages,
+    tools: features.has("tool-call") ? [continuationTool] : [],
+    cache: "none",
+    providerOptions: features.has("encrypted-reasoning")
+      ? { openai: { store: false, includeEncryptedReasoning: true, reasoningSummary: "auto" } }
+      : undefined,
+    generation: { maxTokens: 80, temperature: 0 },
+  })
+}
@@ -1,10 +1,12 @@
 import { describe, expect } from "bun:test"
 import { Effect } from "effect"
+import { HttpClientRequest } from "effect/unstable/http"
 import { CacheHint, LLM, LLMError, Message, ToolCallPart, Usage } from "../../src"
 import { Auth, LLMClient } from "../../src/route"
 import * as AnthropicMessages from "../../src/protocols/anthropic-messages"
+import { continuationRequest, nativeAnthropicMessagesContinuation } from "../continuation-scenarios"
 import { it } from "../lib/effect"
-import { fixedResponse } from "../lib/http"
+import { dynamicResponse, fixedResponse } from "../lib/http"
 import { sseEvents } from "../lib/sse"

 const model = AnthropicMessages.route
@@ -40,7 +42,7 @@ describe("Anthropic Messages route", () => {

  it.effect("prepares tool call and tool result messages", () =>
    Effect.gen(function* () {
-      const prepared = yield* LLMClient.prepare(
+      const prepared = yield* LLMClient.prepare<AnthropicMessages.AnthropicMessagesBody>(
        LLM.request({
          id: "req_tool_result",
          model,
@@ -69,6 +71,50 @@ describe("Anthropic Messages route", () => {
    }),
  )

+  it.effect("prepares the composed native continuation request", () =>
+    Effect.gen(function* () {
+      const prepared = yield* LLMClient.prepare<AnthropicMessages.AnthropicMessagesBody>(
+        continuationRequest({
+          id: "req_native_continuation_anthropic",
+          model,
+          features: nativeAnthropicMessagesContinuation,
+        }),
+      )
+
+      expect(prepared.body).toMatchObject({
+        system: [{ type: "text", text: "You are concise. Continue from the provided history." }],
+        messages: [
+          {
+            role: "user",
+            content: [
+              { type: "text", text: "What is shown here?" },
+              { type: "image", source: { type: "base64", media_type: "image/png", data: "AAECAw==" } },
+            ],
+          },
+          {
+            role: "assistant",
+            content: [
+              { type: "thinking", thinking: "I inspected the previous turn.", signature: "sig_continuation_1" },
+              { type: "text", text: "It shows a small test image." },
+            ],
+          },
+          { role: "user", content: [{ type: "text", text: "Check the weather in Paris before continuing." }] },
+          {
+            role: "assistant",
+            content: [{ type: "tool_use", id: "call_weather_1", name: "get_weather", input: { city: "Paris" } }],
+          },
+          {
+            role: "user",
+            content: [{ type: "tool_result", tool_use_id: "call_weather_1", content: '{"temperature":22}' }],
+          },
+          { role: "assistant", content: [{ type: "text", text: "Paris is 22 degrees." }] },
+          { role: "user", content: [{ type: "text", text: "Continue from this conversation in one short sentence." }] },
+        ],
+      })
+      expect(prepared.body.tools).toEqual([expect.objectContaining({ name: "get_weather" })])
+    }),
+  )
+
  it.effect("lowers preserved Anthropic reasoning signature metadata", () =>
    Effect.gen(function* () {
      const prepared = yield* LLMClient.prepare(
@@ -392,17 +438,51 @@ describe("Anthropic Messages route", () => {
    }),
  )

-  it.effect("rejects unsupported user media content", () =>
+  it.effect("continues a conversation with user image content", () =>
    Effect.gen(function* () {
-      const error = yield* LLMClient.prepare(
+      const response = yield* LLMClient.generate(
        LLM.request({
          id: "req_media",
          model,
-          messages: [Message.user({ type: "media", mediaType: "image/png", data: "AAECAw==" })],
+          messages: [
+            Message.user([
+              { type: "text", text: "What is in this image?" },
+              { type: "media", mediaType: "image/png", data: "AAECAw==" },
+            ]),
+          ],
        }),
-      ).pipe(Effect.flip)
+      ).pipe(
+        Effect.provide(
+          dynamicResponse((input) =>
+            Effect.gen(function* () {
+              const web = yield* HttpClientRequest.toWeb(input.request).pipe(Effect.orDie)
+              expect(yield* Effect.promise(() => web.json())).toMatchObject({
+                messages: [
+                  {
+                    role: "user",
+                    content: [
+                      { type: "text", text: "What is in this image?" },
+                      { type: "image", source: { type: "base64", media_type: "image/png", data: "AAECAw==" } },
+                    ],
+                  },
+                ],
+              })
+              return input.respond(
+                sseEvents(
+                  { type: "content_block_start", index: 0, content_block: { type: "text", text: "" } },
+                  { type: "content_block_delta", index: 0, delta: { type: "text_delta", text: "An image." } },
+                  { type: "content_block_stop", index: 0 },
+                  { type: "message_delta", delta: { stop_reason: "end_turn" }, usage: { output_tokens: 3 } },
+                  { type: "message_stop" },
+                ),
+                { headers: { "content-type": "text/event-stream" } },
+              )
+            }),
+          ),
+        ),
+      )

-      expect(error.message).toContain("Anthropic Messages user messages only support text content for now")
+      expect(response.text).toBe("An image.")
    }),
  )

@@ -84,6 +84,7 @@ describeRecordedGoldenScenarios([
    scenarios: [
      { id: "text", temperature: false },
      { id: "reasoning", temperature: false },
+      { id: "reasoning-continuation", temperature: false },
      { id: "tool-call", temperature: false },
      { id: "tool-loop", temperature: false },
    ],
@@ -7,6 +7,7 @@ import * as Azure from "../../src/providers/azure"
 import * as OpenAI from "../../src/providers/openai"
 import * as OpenAIResponses from "../../src/protocols/openai-responses"
 import * as ProviderShared from "../../src/protocols/shared"
+import { continuationRequest, nativeOpenAIResponsesContinuation } from "../continuation-scenarios"
 import { it } from "../lib/effect"
 import { dynamicResponse, fixedResponse } from "../lib/http"
 import { sseEvents } from "../lib/sse"
@@ -247,6 +248,49 @@ describe("OpenAI Responses route", () => {
    }),
  )

+  it.effect("prepares the composed native continuation request", () =>
+    Effect.gen(function* () {
+      const prepared = yield* LLMClient.prepare<OpenAIResponses.OpenAIResponsesBody>(
+        continuationRequest({
+          id: "req_native_continuation_openai",
+          model,
+          features: nativeOpenAIResponsesContinuation,
+        }),
+      )
+
+      expect(prepared.body).toMatchObject({
+        input: [
+          { role: "system", content: "You are concise. Continue from the provided history." },
+          {
+            role: "user",
+            content: [
+              { type: "input_text", text: "What is shown here?" },
+              { type: "input_image", image_url: "data:image/png;base64,AAECAw==" },
+            ],
+          },
+          {
+            type: "reasoning",
+            id: "rs_continuation_1",
+            encrypted_content: "encrypted-continuation-state",
+            summary: [{ type: "summary_text", text: "I inspected the previous turn." }],
+          },
+          { role: "assistant", content: [{ type: "output_text", text: "It shows a small test image." }] },
+          { role: "user", content: [{ type: "input_text", text: "Check the weather in Paris before continuing." }] },
+          { type: "function_call", call_id: "call_weather_1", name: "get_weather", arguments: '{"city":"Paris"}' },
+          { type: "function_call_output", call_id: "call_weather_1", output: '{"temperature":22}' },
+          { role: "assistant", content: [{ type: "output_text", text: "Paris is 22 degrees." }] },
+          {
+            role: "user",
+            content: [{ type: "input_text", text: "Continue from this conversation in one short sentence." }],
+          },
+        ],
+        include: ["reasoning.encrypted_content"],
+        store: false,
+      })
+      expect(prepared.body.tools).toEqual([expect.objectContaining({ type: "function", name: "get_weather" })])
+    }),
+  )
+
  it.effect("maps OpenAI provider options to Responses options", () =>
    Effect.gen(function* () {
      const prepared = yield* LLMClient.prepare<OpenAIResponses.OpenAIResponsesBody>(
@@ -380,6 +424,172 @@ describe("OpenAI Responses route", () => {
    }),
  )

+  it.effect("preserves encrypted reasoning metadata for continuation", () =>
+    Effect.gen(function* () {
+      const response = yield* LLMClient.generate(request).pipe(
+        Effect.provide(
+          fixedResponse(
+            sseEvents(
+              { type: "response.reasoning_summary_text.delta", item_id: "rs_1", delta: "thinking" },
+              {
+                type: "response.output_item.done",
+                item: {
+                  type: "reasoning",
+                  id: "rs_1",
+                  encrypted_content: "encrypted-state",
+                  summary: [{ type: "summary_text", text: "thinking" }],
+                },
+              },
+              { type: "response.completed", response: { id: "resp_1" } },
+            ),
+          ),
+        ),
+      )
+
+      expect(response.events).toContainEqual(
+        expect.objectContaining({
+          type: "reasoning-end",
+          id: "rs_1",
+          providerMetadata: { openai: { itemId: "rs_1", reasoningEncryptedContent: "encrypted-state" } },
+        }),
+      )
+    }),
+  )
+
+  it.effect("continues a stateless reasoning conversation", () =>
+    Effect.gen(function* () {
+      const response = yield* LLMClient.generate(
+        LLM.request({
+          id: "req_reasoning_continue",
+          model,
+          messages: [
+            Message.user("What changed?"),
+            Message.assistant([
+              {
+                type: "reasoning",
+                text: "Checked the previous diff.",
+                providerMetadata: {
+                  openai: {
+                    itemId: "rs_1",
+                    reasoningEncryptedContent: "encrypted-state",
+                  },
+                },
+              },
+              { type: "text", text: "The parser changed." },
+            ]),
+            Message.user("Summarize it."),
+          ],
+        }),
+      ).pipe(
+        Effect.provide(
+          dynamicResponse((input) =>
+            Effect.gen(function* () {
+              const web = yield* HttpClientRequest.toWeb(input.request).pipe(Effect.orDie)
+              expect(yield* Effect.promise(() => web.json())).toMatchObject({
+                input: [
+                  { role: "user", content: [{ type: "input_text", text: "What changed?" }] },
+                  {
+                    type: "reasoning",
+                    id: "rs_1",
+                    encrypted_content: "encrypted-state",
+                    summary: [{ type: "summary_text", text: "Checked the previous diff." }],
+                  },
+                  { role: "assistant", content: [{ type: "output_text", text: "The parser changed." }] },
+                  { role: "user", content: [{ type: "input_text", text: "Summarize it." }] },
+                ],
+              })
+              return input.respond(
+                sseEvents(
+                  { type: "response.output_text.delta", item_id: "msg_1", delta: "Parser now round-trips reasoning." },
+                  { type: "response.completed", response: { id: "resp_1" } },
+                ),
+                { headers: { "content-type": "text/event-stream" } },
+              )
+            }),
+          ),
+        ),
+      )
+
+      expect(response.text).toBe("Parser now round-trips reasoning.")
+    }),
+  )
+
+  it.effect("preserves assistant content order around reasoning items", () =>
+    Effect.gen(function* () {
+      const prepared = yield* LLMClient.prepare<OpenAIResponses.OpenAIResponsesBody>(
+        LLM.request({
+          id: "req_reasoning_order",
+          model,
+          messages: [
+            Message.assistant([
+              { type: "text", text: "Before." },
+              {
+                type: "reasoning",
+                text: "Checked order.",
+                providerMetadata: {
+                  openai: {
+                    itemId: "rs_1",
+                    reasoningEncryptedContent: "encrypted-state",
+                  },
+                },
+              },
+              { type: "text", text: "After." },
+            ]),
+          ],
+        }),
+      )
+
+      expect(prepared.body.input).toEqual([
+        { role: "assistant", content: [{ type: "output_text", text: "Before." }] },
+        {
+          type: "reasoning",
+          id: "rs_1",
+          encrypted_content: "encrypted-state",
+          summary: [{ type: "summary_text", text: "Checked order." }],
+        },
+        { role: "assistant", content: [{ type: "output_text", text: "After." }] },
+      ])
+    }),
+  )
+
+  it.effect("skips non-persisted reasoning ids without encrypted state", () =>
+    Effect.gen(function* () {
+      const prepared = yield* LLMClient.prepare(
+        LLM.request({
+          id: "req_reasoning_without_encrypted_state",
+          model,
+          messages: [
+            Message.user("What changed?"),
+            Message.assistant([
+              {
+                type: "reasoning",
+                text: "Checked the previous diff.",
+                providerMetadata: {
+                  openai: {
+                    itemId: "rs_1",
+                    reasoningEncryptedContent: null,
+                  },
+                },
+              },
+              { type: "text", text: "The parser changed." },
+            ]),
+            Message.user("Summarize it."),
+          ],
+          providerOptions: { openai: { store: false } },
+        }),
+      )
+
+      expect(prepared.body).toMatchObject({
+        input: [
+          { role: "user", content: [{ type: "input_text", text: "What changed?" }] },
+          { role: "assistant", content: [{ type: "output_text", text: "The parser changed." }] },
+          { role: "user", content: [{ type: "input_text", text: "Summarize it." }] },
+        ],
+        store: false,
+      })
+    }),
+  )
+
  it.effect("assembles streamed function call input", () =>
    Effect.gen(function* () {
      const body = sseEvents(
@@ -2,7 +2,7 @@ import type { HttpRecorder } from "@opencode-ai/http-recorder"
 import { describe } from "bun:test"
 import { Effect } from "effect"
 import type { Model } from "../src"
-import { goldenScenarioTags, runGoldenScenario, type GoldenScenarioID } from "./recorded-scenarios"
+import { goldenScenarioTags, goldenScenarioTitle, runGoldenScenario, type GoldenScenarioID } from "./recorded-scenarios"
 import { recordedTests } from "./recorded-test"
 import { kebab } from "./recorded-utils"

@@ -35,14 +35,6 @@ type TargetInput = {

 const scenarioInput = (input: ScenarioInput) => (typeof input === "string" ? { id: input } : input)

-const scenarioTitle = (id: GoldenScenarioID) => {
-  if (id === "text") return "streams text"
-  if (id === "tool-call") return "streams tool call"
-  if (id === "reasoning") return "uses reasoning"
-  if (id === "image") return "reads image text"
-  return "drives a tool loop"
-}
-
 const defaultPrefix = (target: TargetInput) => {
  if (target.prefix) return target.prefix
  const transport = target.transport === "websocket" ? "-websocket" : ""
@@ -77,7 +69,7 @@ const runTarget = (target: TargetInput) => {
  describe(`${target.name} recorded`, () => {
    target.scenarios.forEach((raw) => {
      const input = scenarioInput(raw)
-      const name = input.name ?? scenarioTitle(input.id)
+      const name = input.name ?? goldenScenarioTitle(input.id)
      recorded.effect.with(
        name,
        {
@@ -1,6 +1,17 @@
 import { expect } from "bun:test"
 import { Effect, Schema, Stream } from "effect"
-import { LLM, LLMEvent, LLMResponse, Message, ToolChoice, ToolDefinition, type LLMRequest, type Model } from "../src"
+import {
+  LLM,
+  LLMEvent,
+  LLMResponse,
+  Message,
+  ToolChoice,
+  ToolDefinition,
+  type ContentPart,
+  type FinishReason,
+  type LLMRequest,
+  type Model,
+} from "../src"
 import { LLMClient } from "../src/route"
 import { tool } from "../src/tool"

@@ -39,47 +50,6 @@ export const weatherRuntimeTool = tool({
    ),
 })

-export const textRequest = (input: {
-  readonly id: string
-  readonly model: Model
-  readonly prompt?: string
-  readonly maxTokens?: number
-  readonly temperature?: number | false
-}) =>
-  LLM.request({
-    id: input.id,
-    model: input.model,
-    system: "You are concise.",
-    prompt: input.prompt ?? "Reply with exactly: Hello!",
-    cache: "none",
-    providerOptions:
-      input.model.route.id === "gemini" ? { gemini: { thinkingConfig: { thinkingBudget: 0 } } } : undefined,
-    generation:
-      input.temperature === false
-        ? { maxTokens: input.maxTokens ?? 80 }
-        : { maxTokens: input.maxTokens ?? 80, temperature: input.temperature ?? 0 },
-  })
-
-export const weatherToolRequest = (input: {
-  readonly id: string
-  readonly model: Model
-  readonly maxTokens?: number
-  readonly temperature?: number | false
-}) =>
-  LLM.request({
-    id: input.id,
-    model: input.model,
-    system: "Call tools exactly as requested.",
-    prompt: "Call get_weather with city exactly Paris.",
-    tools: [weatherTool],
-    toolChoice: ToolChoice.make(weatherTool),
-    cache: "none",
-    generation:
-      input.temperature === false
-        ? { maxTokens: input.maxTokens ?? 80 }
-        : { maxTokens: input.maxTokens ?? 80, temperature: input.temperature ?? 0 },
-  })
-
 export const weatherToolLoopRequest = (input: {
  readonly id: string
  readonly model: Model
@@ -116,52 +86,6 @@ const restroomImage = () =>
    Effect.map((bytes) => Buffer.from(bytes).toString("base64")),
  )

-export const imageRequest = (input: {
-  readonly id: string
-  readonly model: Model
-  readonly image: string
-  readonly maxTokens?: number
-  readonly temperature?: number | false
-}) =>
-  LLM.request({
-    id: input.id,
-    model: input.model,
-    system: "Read images carefully. Reply only with the visible text.",
-    messages: [
-      Message.user([
-        {
-          type: "text",
-          text: "The image contains exactly three lowercase English words. Read them left to right and reply with only those words.",
-        },
-        { type: "media", mediaType: "image/png", data: input.image },
-      ]),
-    ],
-    cache: "none",
-    generation:
-      input.temperature === false
-        ? { maxTokens: input.maxTokens ?? 20 }
-        : { maxTokens: input.maxTokens ?? 20, temperature: input.temperature ?? 0 },
-  })
-
-export const reasoningRequest = (input: {
-  readonly id: string
-  readonly model: Model
-  readonly maxTokens?: number
-  readonly temperature?: number | false
-}) =>
-  LLM.request({
-    id: input.id,
-    model: input.model,
-    system: "Show concise reasoning when the provider supports visible reasoning summaries.",
-    prompt: "Think briefly, then reply exactly with: Hello!",
-    cache: "none",
-    providerOptions: { openai: { reasoningEffort: "low", reasoningSummary: "auto" } },
-    generation:
-      input.temperature === false
-        ? { maxTokens: input.maxTokens ?? 120 }
-        : { maxTokens: input.maxTokens ?? 120, temperature: input.temperature ?? 0 },
-  })
-
 export const runWeatherToolLoop = (request: LLMRequest) =>
  LLMClient.stream({
    request,
@@ -212,8 +136,6 @@ export const expectGoldenWeatherToolLoop = (events: ReadonlyArray<LLMEvent>) =>
  expect(LLMResponse.text({ events }).trim()).toMatch(/^Paris is sunny\.?$/)
 }

-export type GoldenScenarioID = "text" | "tool-call" | "tool-loop" | "image" | "reasoning"
-
 export interface GoldenScenarioContext {
  readonly id: string
  readonly model: Model
@@ -223,6 +145,9 @@ export interface GoldenScenarioContext {

 const generate = (request: LLMRequest) => LLMClient.generate(request)

+const generation = (context: GoldenScenarioContext, maxTokens: number) =>
+  context.temperature === false ? { maxTokens } : { maxTokens, temperature: context.temperature ?? 0 }
+
 const normalizeImageText = (value: string) =>
  value
    .toLowerCase()
@@ -230,75 +155,193 @@ const normalizeImageText = (value: string) =>
    .replace(/\s+/g, " ")
    .trim()

-export const goldenScenarioTags = (id: GoldenScenarioID) => {
-  if (id === "text") return ["text", "golden"]
-  if (id === "tool-call") return ["tool", "tool-call", "golden"]
-  if (id === "image") return ["media", "image", "vision", "golden"]
-  if (id === "reasoning") return ["reasoning", "golden"]
-  return ["tool", "tool-loop", "golden"]
+const encryptedReasoningOptions = {
+  openai: {
+    store: false,
+    includeEncryptedReasoning: true,
+    reasoningEffort: "low",
+    reasoningSummary: "auto",
+  },
+} as const
+
+type AssistantTextExpectation = string | RegExp
+
+type UserStep = { readonly type: "user"; readonly content: Message.ContentInput }
+type AssistantStep = {
+  readonly type: "assistant"
+  readonly text?: AssistantTextExpectation
+  readonly toolCall?: { readonly name: string; readonly input: unknown }
+  readonly reasoning?: "openai-encrypted"
+  readonly id?: string
+  readonly system?: string
+  readonly maxTokens?: number
+  readonly finish?: FinishReason
+  readonly tools?: LLM.RequestInput["tools"]
+  readonly toolChoice?: LLM.RequestInput["toolChoice"]
+  readonly providerOptions?: LLMRequest["providerOptions"]
+  readonly assert?: (response: LLMResponse) => void
+}
+type ConversationStep = UserStep | AssistantStep
+
+const user = (content: Message.ContentInput): ConversationStep => ({ type: "user", content })
+
+const assistant = {
+  expectText: (
+    text: AssistantTextExpectation,
+    options?: Omit<AssistantStep, "type" | "text" | "reasoning" | "toolCall">,
+  ): ConversationStep => ({ type: "assistant", text, ...options }),
+  expectToolCall: (
+    name: string,
+    input: unknown,
+    options?: Omit<AssistantStep, "type" | "text" | "reasoning" | "toolCall" | "finish">,
+  ): ConversationStep => ({ type: "assistant", toolCall: { name, input }, finish: "tool-calls", ...options }),
+  expectEncryptedReasoningText: (
+    text: AssistantTextExpectation,
+    options?: Omit<AssistantStep, "type" | "text" | "reasoning" | "toolCall" | "providerOptions">,
+  ): ConversationStep => ({
+    type: "assistant",
+    text,
+    reasoning: "openai-encrypted",
+    providerOptions: encryptedReasoningOptions,
+    ...options,
+  }),
 }

-export const runGoldenScenario = (id: GoldenScenarioID, context: GoldenScenarioContext) =>
+const assertAssistantText = (actual: string, expected: AssistantTextExpectation) => {
+  if (typeof expected === "string") {
+    expect(actual.trim()).toBe(expected)
+    return
+  }
+  expect(actual.trim()).toMatch(expected)
+}
+
+const assertAssistantToolCall = (response: LLMResponse, expected: NonNullable<AssistantStep["toolCall"]>) => {
+  expect(response.toolCalls).toMatchObject([
+    { type: "tool-call", id: expect.any(String), name: expected.name, input: expected.input },
+  ])
+}
+
+// The generated golden scenarios only model one assistant shape at a time:
+// encrypted reasoning + text, text, or tool call. Keep mixed interleavings in
+// focused protocol tests where event order can be asserted directly.
+const assistantMessageFromResponse = (response: LLMResponse, step: AssistantStep) => {
+  const content: ContentPart[] = []
+  if (step.reasoning === "openai-encrypted") {
+    const reasoning = response.events.find(
+      (event): event is Extract<LLMEvent, { readonly type: "reasoning-end" }> =>
+        LLMEvent.is.reasoningEnd(event) && typeof event.providerMetadata?.openai?.itemId === "string",
+    )
+    if (!reasoning) throw new Error("OpenAI Responses did not return reasoning metadata")
+    expect(reasoning.providerMetadata?.openai?.reasoningEncryptedContent).toEqual(expect.any(String))
+    content.push({ type: "reasoning", text: response.reasoning, providerMetadata: reasoning.providerMetadata })
+  }
+
+  if (response.text.length > 0) content.push({ type: "text", text: response.text })
+  content.push(...response.toolCalls)
+  return Message.assistant(content)
+}
+
+const runGeneratedConversation = (context: GoldenScenarioContext, steps: ReadonlyArray<ConversationStep>) =>
  Effect.gen(function* () {
-    if (id === "text") {
+    const messages: Message[] = []
+    let generated = 0
+    for (const step of steps) {
+      if (step.type === "user") {
+        messages.push(Message.user(step.content))
+        continue
+      }
+
+      generated += 1
      const response = yield* generate(
-        textRequest({
-          id: context.id,
+        LLM.request({
+          id: step.id ? `${context.id}_${step.id}` : `${context.id}_${generated}`,
          model: context.model,
-          prompt: "Reply exactly with: Hello!",
-          maxTokens: context.maxTokens ?? 40,
-          temperature: context.temperature,
+          system: step.system,
+          cache: "none",
+          messages,
+          tools: step.tools,
+          toolChoice: step.toolChoice,
+          providerOptions: step.providerOptions,
+          generation: generation(context, step.maxTokens ?? context.maxTokens ?? 80),
        }),
      )
-      expect(response.text.trim()).toMatch(/^Hello!?$/)
-      expectFinish(response.events, "stop")
-      return
+      if (step.text !== undefined) assertAssistantText(response.text, step.text)
+      if (step.toolCall) assertAssistantToolCall(response, step.toolCall)
+      step.assert?.(response)
+      expectFinish(response.events, step.finish ?? "stop")
+      messages.push(assistantMessageFromResponse(response, step))
    }
+  })

-    if (id === "tool-call") {
-      const response = yield* generate(
-        weatherToolRequest({
-          id: context.id,
-          model: context.model,
-          maxTokens: context.maxTokens ?? 80,
-          temperature: context.temperature,
-        }),
-      )
-      expectWeatherToolCall(response)
-      expectFinish(response.events, "tool-calls")
-      return
-    }
+const runTextScenario = (context: GoldenScenarioContext) =>
+  runGeneratedConversation(context, [
+    user("Reply exactly with: Hello!"),
+    assistant.expectText(/^Hello!?$/, {
+      system: "You are concise.",
+      maxTokens: context.maxTokens ?? 40,
+      providerOptions:
+        context.model.route.id === "gemini" ? { gemini: { thinkingConfig: { thinkingBudget: 0 } } } : undefined,
+    }),
+  ])

-    if (id === "image") {
-      const response = yield* generate(
-        imageRequest({
-          id: context.id,
-          model: context.model,
-          image: yield* restroomImage(),
-          maxTokens: context.maxTokens ?? 20,
-          temperature: context.temperature,
-        }),
-      )
-      expect(normalizeImageText(response.text)).toBe(RESTROOM_IMAGE_TEXT)
-      expectFinish(response.events, "stop")
-      return
-    }
+const runToolCallScenario = (context: GoldenScenarioContext) =>
+  runGeneratedConversation(context, [
+    user("Call get_weather with city exactly Paris."),
+    assistant.expectToolCall(
+      weatherToolName,
+      { city: "Paris" },
+      {
+        system: "Call tools exactly as requested.",
+        tools: [weatherTool],
+        toolChoice: ToolChoice.make(weatherTool),
+        maxTokens: context.maxTokens ?? 80,
+      },
+    ),
+  ])

-    if (id === "reasoning") {
-      const response = yield* generate(
-        reasoningRequest({
-          id: context.id,
-          model: context.model,
-          maxTokens: context.maxTokens ?? 120,
-          temperature: context.temperature,
-        }),
-      )
-      expect(response.text.trim()).toMatch(/^Hello!?$/)
-      expect(response.usage?.reasoningTokens ?? 0).toBeGreaterThan(0)
-      expectFinish(response.events, "stop")
-      return
-    }
+const runImageScenario = (context: GoldenScenarioContext) =>
+  Effect.gen(function* () {
+    yield* runGeneratedConversation(context, [
+      user([
+        {
+          type: "text",
+          text: "The image contains exactly three lowercase English words. Read them left to right and reply with only those words.",
+        },
+        { type: "media", mediaType: "image/png", data: yield* restroomImage() },
+      ]),
+      assistant.expectText(/.+/, {
+        system: "Read images carefully. Reply only with the visible text.",
+        maxTokens: context.maxTokens ?? 20,
+        assert: (response) => expect(normalizeImageText(response.text)).toBe(RESTROOM_IMAGE_TEXT),
+      }),
+    ])
+  })

+const runReasoningScenario = (context: GoldenScenarioContext) =>
+  runGeneratedConversation(context, [
+    user("Think briefly, then reply exactly with: Hello!"),
+    assistant.expectText(/^Hello!?$/, {
+      system: "Show concise reasoning when the provider supports visible reasoning summaries.",
+      providerOptions: { openai: { reasoningEffort: "low", reasoningSummary: "auto" } },
+      maxTokens: context.maxTokens ?? 120,
+      assert: (response) => expect(response.usage?.reasoningTokens ?? 0).toBeGreaterThan(0),
+    }),
+  ])
+
+const runReasoningContinuationScenario = (context: GoldenScenarioContext) =>
+  runGeneratedConversation(context, [
+    user("Think briefly, then reply exactly with: Hello!"),
+    assistant.expectEncryptedReasoningText(/^Hello!?$/, {
+      id: "first",
+      system: "Show concise reasoning when the provider supports visible reasoning summaries.",
+      maxTokens: context.maxTokens ?? 120,
+    }),
+    user("Now reply exactly with: Done."),
+    assistant.expectText(/^Done\.?$/, { id: "second", maxTokens: 40, providerOptions: encryptedReasoningOptions }),
+  ])
+
+const runToolLoopScenario = (context: GoldenScenarioContext) =>
+  Effect.gen(function* () {
    expectGoldenWeatherToolLoop(
      yield* runWeatherToolLoop(
        goldenWeatherToolLoopRequest({
@@ -311,6 +354,25 @@ export const runGoldenScenario = (id: GoldenScenarioID, context: GoldenScenarioC
    )
  })

+const goldenScenarios = {
+  text: { title: "streams text", tags: ["text", "golden"], run: runTextScenario },
+  "tool-call": { title: "streams tool call", tags: ["tool", "tool-call", "golden"], run: runToolCallScenario },
+  "tool-loop": { title: "drives a tool loop", tags: ["tool", "tool-loop", "golden"], run: runToolLoopScenario },
+  image: { title: "reads image text", tags: ["media", "image", "vision", "golden"], run: runImageScenario },
+  reasoning: { title: "uses reasoning", tags: ["reasoning", "golden"], run: runReasoningScenario },
+  "reasoning-continuation": {
+    title: "continues encrypted reasoning",
+    tags: ["reasoning", "continuation", "encrypted-reasoning", "golden"],
+    run: runReasoningContinuationScenario,
+  },
+} as const
+
+export type GoldenScenarioID = keyof typeof goldenScenarios
+export const goldenScenarioTitle = (id: GoldenScenarioID) => goldenScenarios[id].title
+export const goldenScenarioTags = (id: GoldenScenarioID) => [...goldenScenarios[id].tags]
+export const runGoldenScenario = (id: GoldenScenarioID, context: GoldenScenarioContext) =>
+  goldenScenarios[id].run(context)
+
 const usageSummary = (usage: LLMResponse["usage"] | undefined) => {
  if (!usage) return undefined
  return Object.fromEntries(
@@ -1,6 +1,6 @@
 {
  "$schema": "https://json.schemastore.org/package.json",
-  "version": "1.15.6",
+  "version": "1.15.7",
  "name": "opencode",
  "type": "module",
  "license": "MIT",
@@ -135,7 +135,7 @@
    "drizzle-orm": "catalog:",
    "effect": "catalog:",
    "fuzzysort": "3.1.0",
-    "gitlab-ai-provider": "6.6.0",
+    "gitlab-ai-provider": "6.7.0",
    "glob": "13.0.5",
    "google-auth-library": "10.5.0",
    "gray-matter": "4.0.3",
@@ -19,7 +19,7 @@ import {
  WorkspaceRoutingQuery,
  WorkspaceRoutingQueryFields,
 } from "../middleware/workspace-routing"
-import { ApiNotFoundError } from "../errors"
+import { ApiNotFoundError, SessionBusyError } from "../errors"
 import { described } from "./metadata"
 import { QueryBoolean } from "./query"

@@ -354,7 +354,7 @@ export const SessionApi = HttpApi.make("session")
          query: WorkspaceRoutingQuery,
          payload: ShellPayload,
          success: described(MessageV2.WithParts, "Created message"),
-          error: [HttpApiError.BadRequest, ApiNotFoundError],
+          error: [HttpApiError.BadRequest, ApiNotFoundError, SessionBusyError],
        }).annotateMerge(
          OpenApi.annotations({
            identifier: "session.shell",
@@ -367,7 +367,7 @@ export const SessionApi = HttpApi.make("session")
          query: WorkspaceRoutingQuery,
          payload: RevertPayload,
          success: described(Session.Info, "Updated session"),
-          error: [HttpApiError.BadRequest, ApiNotFoundError],
+          error: [HttpApiError.BadRequest, ApiNotFoundError, SessionBusyError],
        }).annotateMerge(
          OpenApi.annotations({
            identifier: "session.revert",
@@ -380,7 +380,7 @@ export const SessionApi = HttpApi.make("session")
          params: { sessionID: SessionID },
          query: WorkspaceRoutingQuery,
          success: described(Session.Info, "Updated session"),
-          error: [HttpApiError.BadRequest, ApiNotFoundError],
+          error: [HttpApiError.BadRequest, ApiNotFoundError, SessionBusyError],
        }).annotateMerge(
          OpenApi.annotations({
            identifier: "session.unrevert",
@@ -406,7 +406,7 @@ export const SessionApi = HttpApi.make("session")
          params: { sessionID: SessionID, messageID: MessageID },
          query: WorkspaceRoutingQuery,
          success: described(Schema.Boolean, "Successfully deleted message"),
-          error: [HttpApiError.BadRequest, ApiNotFoundError],
+          error: [HttpApiError.BadRequest, ApiNotFoundError, SessionBusyError],
        }).annotateMerge(
          OpenApi.annotations({
            identifier: "session.deleteMessage",
@@ -1,7 +1,6 @@
 import type { NotFoundError as StorageNotFoundError } from "@/storage/storage"
 import type { Session } from "@/session/session"
 import { Effect } from "effect"
-import { HttpApiError } from "effect/unstable/httpapi"
 import * as ApiError from "../errors"

 export function mapStorageNotFound<A, R>(self: Effect.Effect<A, StorageNotFoundError, R>) {
@@ -9,5 +8,14 @@ export function mapStorageNotFound<A, R>(self: Effect.Effect<A, StorageNotFoundE
 }

 export function mapBusy<A, R>(self: Effect.Effect<A, Session.BusyError, R>) {
-  return self.pipe(Effect.catchTag("SessionBusyError", () => Effect.fail(new HttpApiError.BadRequest({}))))
+  return self.pipe(
+    Effect.catchTag("SessionBusyError", (error) =>
+      Effect.fail(
+        new ApiError.SessionBusyError({
+          sessionID: error.sessionID,
+          message: `Session is busy: ${error.sessionID}`,
+        }),
+      ),
+    ),
+  )
 }
@@ -42,10 +42,15 @@ const providerMetadata = (value: unknown): ProviderMetadata | undefined => {
  return Object.keys(result).length === 0 ? undefined : result
 }

+// Stored AI SDK parts historically kept provider-owned continuation metadata in
+// `providerOptions`; native parts now use `providerMetadata` directly.
+const partProviderMetadata = (part: Record<string, unknown>) =>
+  providerMetadata(part.providerMetadata) ?? providerMetadata(part.providerOptions)
+
 const textPart = (part: Record<string, unknown>) => ({
  type: "text" as const,
  text: typeof part.text === "string" ? part.text : "",
-  providerMetadata: providerMetadata(part.providerOptions),
+  providerMetadata: partProviderMetadata(part),
 })

 const mediaPart = (part: Record<string, unknown>) => {
@@ -68,7 +73,7 @@ const toolResult = (part: Record<string, unknown>) => {
    result: "value" in output ? output.value : output,
    resultType: type,
    providerExecuted: typeof part.providerExecuted === "boolean" ? part.providerExecuted : undefined,
-    providerMetadata: providerMetadata(part.providerOptions),
+    providerMetadata: partProviderMetadata(part),
  })
 }

@@ -80,7 +85,7 @@ const contentPart = (part: unknown) => {
    return {
      type: "reasoning" as const,
      text: typeof part.text === "string" ? part.text : "",
-      providerMetadata: providerMetadata(part.providerOptions),
+      providerMetadata: partProviderMetadata(part),
    }
  if (part.type === "tool-call")
    return ToolCallPart.make({
@@ -88,7 +93,7 @@ const contentPart = (part: unknown) => {
      name: typeof part.toolName === "string" ? part.toolName : "",
      input: part.input,
      providerExecuted: typeof part.providerExecuted === "boolean" ? part.providerExecuted : undefined,
-      providerMetadata: providerMetadata(part.providerOptions),
+      providerMetadata: partProviderMetadata(part),
    })
  if (part.type === "tool-result") return toolResult(part)
  throw new Error(`Native LLM request adapter does not support ${String(part.type)} content parts`)
@@ -20,6 +20,7 @@ import * as Log from "@opencode-ai/core/util/log"
 import { EffectBridge } from "@/effect/bridge"

 const log = Log.create({ service: "session.tools" })
+const schemaInternalKeys = new Set(["_def", "def", "_zod", "~standard", "_cached", "typeName"])

 export const resolve = Effect.fn("SessionTools.resolve")(function* (input: {
  agent: Agent.Info
@@ -78,6 +79,7 @@ export const resolve = Effect.fn("SessionTools.resolve")(function* (input: {
    agent: input.agent,
  })) {
    const schema = ProviderTransform.schema(input.model, ToolJsonSchema.fromTool(item))
+    assertNoSchemaInternals(item.id, schema)
    tools[item.id] = tool({
      description: item.description,
      inputSchema: jsonSchema(schema),
@@ -121,6 +123,7 @@ export const resolve = Effect.fn("SessionTools.resolve")(function* (input: {

    const schema = yield* Effect.promise(() => Promise.resolve(asSchema(item.inputSchema).jsonSchema))
    const transformed = ProviderTransform.schema(input.model, schema)
+    assertNoSchemaInternals(key, transformed)
    item.inputSchema = jsonSchema(transformed)
    item.execute = (args, opts) =>
      run.promise(
@@ -205,4 +208,31 @@ export const resolve = Effect.fn("SessionTools.resolve")(function* (input: {
  return tools
 })

+function assertNoSchemaInternals(toolID: string, schema: unknown) {
+  const path = schemaInternalPath(schema)
+  if (!path) return
+  throw new Error(`Tool ${toolID} input schema contains non-JSON-Schema Zod internals at ${path}`)
+}
+
+function schemaInternalPath(value: unknown, path = "$", skipKeys = false): string | undefined {
+  if (Array.isArray(value)) {
+    return value
+      .map((item, index) => schemaInternalPath(item, `${path}[${index}]`))
+      .find((item): item is string => item !== undefined)
+  }
+  if (typeof value !== "object" || value === null) return undefined
+
+  for (const [key, item] of Object.entries(value)) {
+    const nextPath = /^[A-Za-z_$][\w$]*$/.test(key) ? `${path}.${key}` : `${path}[${JSON.stringify(key)}]`
+    if (!skipKeys && schemaInternalKeys.has(key)) return nextPath
+    const found = schemaInternalPath(
+      item,
+      nextPath,
+      key === "properties" || key === "$defs" || key === "definitions" || key === "patternProperties",
+    )
+    if (found) return found
+  }
+  return undefined
+}
+
 export * as SessionTools from "./tools"
@@ -55,6 +55,13 @@ import { Reference } from "@/reference/reference"
 import { BackgroundJob } from "@/background/job"
 import { SessionStatus } from "@/session/status"
 import { RuntimeFlags } from "@/effect/runtime-flags"
+import {
+  objectFromShape,
+  safeParse,
+  type AnyObjectSchema,
+  type AnySchema,
+} from "@modelcontextprotocol/sdk/server/zod-compat.js"
+import { toJsonSchemaCompat } from "@modelcontextprotocol/sdk/server/zod-json-schema-compat.js"

 const log = Log.create({ service: "tool.registry" })

@@ -150,10 +157,10 @@ export const layer: Layer.Layer<
          const args = def.args ?? {}
          const entries = Object.entries(args)
          const allZod = entries.every((entry) => isZodType(entry[1]))
-          const zodParams = allZod ? z.object(args) : undefined
+          const zodParams = allZod ? objectFromShape(args as Record<string, AnySchema>) : undefined
          const jsonSchema = zodParams ? zodJsonSchema(zodParams) : legacyJsonSchema(entries)
          const parameters = zodParams
-            ? Schema.declare<unknown>((u): u is unknown => zodParams.safeParse(u).success)
+            ? Schema.declare<unknown>((u): u is unknown => safeParse(zodParams, u).success)
            : Schema.Unknown
          return {
            id,
@@ -402,7 +409,11 @@ export const defaultLayer = Layer.suspend(() =>
    .pipe(Layer.provide(RuntimeFlags.defaultLayer)),
 )

-function isZodType(value: unknown): value is z.ZodType {
+function isZodType(value: unknown): value is AnySchema {
+  return typeof value === "object" && value !== null && ("_zod" in value || "_def" in value)
+}
+
+function isZod4Type(value: unknown): value is z.ZodType {
  return typeof value === "object" && value !== null && "_zod" in value
 }

@@ -425,8 +436,12 @@ function legacyJsonSchema(entries: [string, unknown][]): JSONSchema7 {
  }
 }

-function zodJsonSchema(schema: z.ZodType): JSONSchema7 {
-  const result = normalizeZodJsonSchema(z.toJSONSchema(schema, { io: "input", metadata: zodMetadataRegistry(schema) }))
+function zodJsonSchema(schema: AnyObjectSchema): JSONSchema7 {
+  const result = normalizeZodJsonSchema(
+    isZod4Type(schema)
+      ? z.toJSONSchema(schema, { io: "input", metadata: zodMetadataRegistry(schema) })
+      : toJsonSchemaCompat(schema, { pipeStrategy: "input" }),
+  )
  if (!isJsonSchemaObject(result)) throw new Error("plugin tool Zod schema produced a non-object JSON Schema")
  const { $defs, ...rest } = result
  return (
@@ -434,7 +449,7 @@ function zodJsonSchema(schema: z.ZodType): JSONSchema7 {
  ) as JSONSchema7
 }

-function zodMetadataRegistry(schema: z.ZodType) {
+function zodMetadataRegistry(schema: AnyObjectSchema) {
  const registry = z.registry<Record<string, unknown>>()
  const seen = new WeakSet<object>()
  const collect = (value: unknown) => {
@@ -442,7 +457,7 @@ function zodMetadataRegistry(schema: z.ZodType) {
    if (seen.has(value)) return
    seen.add(value)

-    if (isZodType(value)) {
+    if (isZod4Type(value)) {
      const metadata = typeof value.meta === "function" ? value.meta() : undefined
      const description = typeof value.description === "string" ? value.description : undefined
      const merged = {
@@ -207,6 +207,12 @@ export function provideTmpdirInstance<A, E, R>(

 export class TestInstance extends Context.Service<TestInstance, { readonly directory: string }>()("@test/Instance") {}

+export const requireInstance = Effect.gen(function* () {
+  const instance = yield* InstanceRef
+  if (!instance) return yield* Effect.die(new Error("missing test instance"))
+  return instance
+})
+
 export const withTmpdirInstance =
  (options?: { git?: boolean; config?: Partial<Config.Info> | (() => Partial<Config.Info>) }) =>
  <A, E, R>(self: Effect.Effect<A, E, R>) =>
@@ -142,4 +142,19 @@ describe("PublicApi OpenAPI v2 errors", () => {
      )
    }
  })
+
+  test("documents session busy errors", () => {
+    const spec = OpenApi.fromApi(PublicApi) as OpenApiSpec
+
+    for (const route of [
+      ["post", "/session/{sessionID}/shell"],
+      ["post", "/session/{sessionID}/revert"],
+      ["post", "/session/{sessionID}/unrevert"],
+      ["delete", "/session/{sessionID}/message/{messageID}"],
+    ] as const) {
+      expect(componentName(responseRef(spec.paths[route[1]]?.[route[0]]?.responses?.["409"]) ?? "")).toBe(
+        "SessionBusyError",
+      )
+    }
+  })
 })
@@ -1,7 +1,7 @@
 import { afterEach, describe, expect } from "bun:test"
 import { mkdir } from "node:fs/promises"
 import path from "node:path"
-import { Effect, Layer } from "effect"
+import { Cause, Effect, Exit, Layer } from "effect"
 import { Flag } from "@opencode-ai/core/flag/flag"
 import { registerAdapter } from "../../src/control-plane/adapters"
 import type { WorkspaceAdapter } from "../../src/control-plane/types"
@@ -13,6 +13,7 @@ import { InstanceBootstrap as InstanceBootstrapService } from "../../src/project
 import { InstanceStore } from "../../src/project/instance-store"
 import { Project } from "../../src/project/project"
 import { Server } from "../../src/server/server"
+import * as HttpSessionError from "../../src/server/routes/instance/httpapi/handlers/session-errors"
 import { SessionPaths } from "../../src/server/routes/instance/httpapi/groups/session"
 import { Session } from "@/session/session"
 import { MessageID, PartID, SessionID, type SessionID as SessionIDType } from "../../src/session/schema"
@@ -215,6 +216,22 @@ afterEach(async () => {
 })

 describe("session HttpApi", () => {
+  it.effect("maps busy sessions to public session busy errors", () =>
+    Effect.gen(function* () {
+      const sessionID = SessionID.descending()
+      const exit = yield* HttpSessionError.mapBusy(Effect.fail(new Session.BusyError({ sessionID }))).pipe(Effect.exit)
+
+      expect(Exit.isFailure(exit)).toBe(true)
+      if (Exit.isFailure(exit)) {
+        expect(Cause.squash(exit.cause)).toMatchObject({
+          _tag: "SessionBusyError",
+          sessionID,
+          message: `Session is busy: ${sessionID}`,
+        })
+      }
+    }),
+  )
+
  it.instance(
    "returns declared not found errors for read routes",
    () =>
@@ -1,13 +1,14 @@
 import { describe, expect, test } from "bun:test"
 import { ToolFailure } from "@opencode-ai/llm"
 import { LLMClient, RequestExecutor, WebSocketExecutor } from "@opencode-ai/llm/route"
-import { jsonSchema, tool, type ModelMessage } from "ai"
+import { jsonSchema, tool, type ModelMessage, type Tool } from "ai"
 import { Effect, Layer, Stream } from "effect"
 import { LLMNative } from "@/session/llm/native-request"
 import { LLMNativeRuntime } from "@/session/llm/native-runtime"
 import type { Provider } from "@/provider/provider"
 import { ModelID, ProviderID } from "@/provider/schema"
 import { OAUTH_DUMMY_KEY } from "@/auth"
+import { testEffect } from "../lib/effect"

 const baseModel: Provider.Model = {
  id: ModelID.make("gpt-5-mini"),
@@ -69,6 +70,10 @@ const providerInfo: Provider.Info = {
  models: {},
 }

+const it = testEffect(
+  LLMClient.layer.pipe(Layer.provide(Layer.mergeAll(RequestExecutor.defaultLayer, WebSocketExecutor.layer))),
+)
+
 function responsesStream(chunks: unknown[]) {
  return new Response(chunks.map((chunk) => `data: ${JSON.stringify(chunk)}`).join("\n\n") + "\n\n", {
    status: 200,
@@ -76,6 +81,72 @@ function responsesStream(chunks: unknown[]) {
  })
 }

+type NativeRequestInput = Parameters<typeof LLMNative.request>[0]
+
+const sessionText = (text: string) => ({ type: "text" as const, text })
+
+const sessionOpenAIReasoning = (
+  text: string,
+  options: {
+    readonly storedAs: "providerMetadata" | "providerOptions"
+    readonly itemId: string
+    readonly encryptedContent: string | null
+  },
+) => {
+  const metadata = {
+    openai: { itemId: options.itemId, reasoningEncryptedContent: options.encryptedContent },
+  }
+  if (options.storedAs === "providerMetadata")
+    return Object.assign({ type: "reasoning" as const, text }, { providerMetadata: metadata })
+  return Object.assign({ type: "reasoning" as const, text }, { providerOptions: metadata })
+}
+
+type SessionAssistantPart = ReturnType<typeof sessionText> | ReturnType<typeof sessionOpenAIReasoning>
+
+const storedSession = {
+  user: (content: string): ModelMessage => ({ role: "user", content }),
+  assistant: (content: SessionAssistantPart[]): ModelMessage => ({ role: "assistant", content }),
+  text: sessionText,
+  openaiReasoning: sessionOpenAIReasoning,
+}
+
+const openAIResponses = {
+  user: (text: string) => ({ role: "user", content: [{ type: "input_text", text }] }),
+  assistant: (text: string) => ({ role: "assistant", content: [{ type: "output_text", text }] }),
+  openaiReasoning: (text: string, options: { readonly itemId: string; readonly encryptedContent: string }) => ({
+    type: "reasoning",
+    id: options.itemId,
+    encrypted_content: options.encryptedContent,
+    summary: [{ type: "summary_text", text }],
+  }),
+}
+
+const prepareNativeRequest = (input: NativeRequestInput) => LLMClient.prepare(LLMNative.request(input))
+
+const expectOpenAIResponsesRequest = (input: {
+  readonly history: NativeRequestInput["messages"]
+  readonly providerOptions?: NativeRequestInput["providerOptions"]
+  readonly maxOutputTokens?: NativeRequestInput["maxOutputTokens"]
+  readonly headers?: NativeRequestInput["headers"]
+  readonly expectedBody: unknown
+}) =>
+  Effect.gen(function* () {
+    expect(
+      yield* prepareNativeRequest({
+        model: baseModel,
+        apiKey: "test-openai-key",
+        messages: input.history,
+        providerOptions: input.providerOptions,
+        maxOutputTokens: input.maxOutputTokens,
+        headers: input.headers,
+      }),
+    ).toMatchObject({
+      route: "openai-responses",
+      protocol: "openai-responses",
+      body: input.expectedBody,
+    })
+  })
+
 describe("session.llm-native.request", () => {
  test("maps normalized stream inputs to a native LLM request", () => {
    const messages: ModelMessage[] = [
@@ -219,6 +290,42 @@ describe("session.llm-native.request", () => {
    ])
  })

+  test("maps stored provider metadata to native content metadata", () => {
+    const reasoning = Object.assign(
+      { type: "reasoning" as const, text: "thinking" },
+      {
+        providerMetadata: {
+          openai: {
+            itemId: "rs_1",
+            reasoningEncryptedContent: "encrypted-state",
+          },
+        },
+      },
+    )
+    const request = LLMNative.request({
+      model: baseModel,
+      messages: [
+        {
+          role: "assistant",
+          content: [reasoning],
+        },
+      ],
+    })
+
+    expect(request.messages).toMatchObject([
+      {
+        role: "assistant",
+        content: [
+          {
+            type: "reasoning",
+            text: "thinking",
+            providerMetadata: { openai: { itemId: "rs_1", reasoningEncryptedContent: "encrypted-state" } },
+          },
+        ],
+      },
+    ])
+  })
+
  test("selects native request routes for provider packages", () => {
    const openai = LLMNative.model({
      model: { ...baseModel, api: { ...baseModel.api, url: "", npm: "@ai-sdk/openai" } },
@@ -390,122 +497,163 @@ describe("session.llm-native.request", () => {
    })
  })

-  test("native tool wrapper converts thrown errors into typed ToolFailure", async () => {
-    const wrapped = LLMNativeRuntime.nativeTools(
-      {
-        explode: {
-          description: "always throws",
-          inputSchema: jsonSchema({ type: "object" }),
-          execute: async () => {
-            throw new Error("boom")
-          },
-        } as any,
-      },
-      { messages: [] as ModelMessage[], abort: new AbortController().signal },
-    )
+  it.effect("native tool wrapper converts thrown errors into typed ToolFailure", () =>
+    Effect.gen(function* () {
+      const wrapped = LLMNativeRuntime.nativeTools(
+        {
+          explode: {
+            description: "always throws",
+            inputSchema: jsonSchema({ type: "object" }),
+            execute: async () => {
+              throw new Error("boom")
+            },
+          } satisfies Tool,
+        },
+        { messages: [] as ModelMessage[], abort: new AbortController().signal },
+      )

-    const failure = await Effect.runPromise(
-      Effect.flip(wrapped.explode!.execute!({}, { id: "call-1", name: "explode" })),
-    )
-    expect(failure).toBeInstanceOf(ToolFailure)
-    expect((failure as ToolFailure).message).toBe("boom")
-  })
+      const failure = yield* Effect.flip(wrapped.explode.execute({}, { id: "call-1", name: "explode" }))
+      expect(failure).toBeInstanceOf(ToolFailure)
+      expect(failure.message).toBe("boom")
+    }),
+  )

-  test("native tool wrapper raises ToolFailure when the source tool has no execute handler", async () => {
-    // The AI SDK Tool shape allows execute to be omitted (e.g., client-side / MCP tools).
-    // The native runtime owns execution, so encountering such a tool here means upstream
-    // wiring is wrong; we want a typed failure, not a silent skip or unhandled exception.
-    const wrapped = LLMNativeRuntime.nativeTools(
-      { incomplete: { description: "no execute", inputSchema: jsonSchema({ type: "object" }) } as any },
-      { messages: [] as ModelMessage[], abort: new AbortController().signal },
-    )
+  it.effect("native tool wrapper raises ToolFailure when the source tool has no execute handler", () =>
+    Effect.gen(function* () {
+      // The AI SDK Tool shape allows execute to be omitted (e.g., client-side / MCP tools).
+      // The native runtime owns execution, so encountering such a tool here means upstream
+      // wiring is wrong; we want a typed failure, not a silent skip or unhandled exception.
+      const wrapped = LLMNativeRuntime.nativeTools(
+        { incomplete: { description: "no execute", inputSchema: jsonSchema({ type: "object" }) } satisfies Tool },
+        { messages: [] as ModelMessage[], abort: new AbortController().signal },
+      )

-    const failure = await Effect.runPromise(
-      Effect.flip(wrapped.incomplete!.execute!({}, { id: "call-1", name: "incomplete" })),
-    )
-    expect(failure).toBeInstanceOf(ToolFailure)
-    expect((failure as ToolFailure).message).toContain("incomplete")
-  })
+      const failure = yield* Effect.flip(wrapped.incomplete.execute({}, { id: "call-1", name: "incomplete" }))
+      expect(failure).toBeInstanceOf(ToolFailure)
+      expect(failure.message).toContain("incomplete")
+    }),
+  )

-  test("compiles through the native OpenAI Responses route", async () => {
-    const prepared = await Effect.runPromise(
-      LLMClient.prepare(
-        LLMNative.request({
-          model: baseModel,
-          apiKey: "test-openai-key",
-          messages: [{ role: "user", content: "hello" }],
-          providerOptions: { openai: { store: false, instructions: "You are concise." } },
-          maxOutputTokens: 512,
-          headers: { "x-request": "request-header" },
-        }),
-      ).pipe(
-        Effect.provide(LLMClient.layer),
-        Effect.provide(Layer.mergeAll(RequestExecutor.defaultLayer, WebSocketExecutor.layer)),
-      ),
-    )
-
-    expect(prepared).toMatchObject({
-      route: "openai-responses",
-      protocol: "openai-responses",
-      body: {
+  it.effect("compiles through the native OpenAI Responses route", () =>
+    expectOpenAIResponsesRequest({
+      history: [storedSession.user("hello")],
+      providerOptions: { openai: { store: false, instructions: "You are concise." } },
+      maxOutputTokens: 512,
+      headers: { "x-request": "request-header" },
+      expectedBody: {
        model: "gpt-5-mini",
        instructions: "You are concise.",
-        input: [{ role: "user", content: [{ type: "input_text", text: "hello" }] }],
+        input: [openAIResponses.user("hello")],
        max_output_tokens: 512,
        store: false,
        stream: true,
      },
-    })
-  })
+    }),
+  )

-  test("uses provider fetch override for native OpenAI OAuth requests", async () => {
-    const captures: Array<{ url: string; body: unknown }> = []
-    const customFetch = (async (input, init) => {
-      const request = input instanceof Request ? input : new Request(input, init)
-      captures.push({ url: request.url, body: await request.clone().json() })
-      return responsesStream([
-        { type: "response.output_text.delta", item_id: "msg_1", delta: "Hello" },
-        { type: "response.completed", response: { usage: { input_tokens: 1, output_tokens: 1 } } },
-      ])
-    }) as typeof fetch
-
-    const events = await Effect.runPromise(
-      Effect.gen(function* () {
-        const llmClient = yield* LLMClient.Service
-        const native = LLMNativeRuntime.stream({
-          model: baseModel,
-          provider: { ...providerInfo, options: { apiKey: OAUTH_DUMMY_KEY, fetch: customFetch } },
-          auth: { type: "oauth", refresh: "refresh", access: "access", expires: Date.now() + 60_000 },
-          llmClient,
-          messages: [{ role: "user", content: "hello" }],
-          tools: {},
-          providerOptions: { instructions: "You are concise." },
-          headers: {},
-          abort: new AbortController().signal,
-        })
-        expect(native.type).toBe("supported")
-        if (native.type === "unsupported") return []
-        return yield* native.stream.pipe(Stream.runCollect)
-      }).pipe(
-        Effect.provide(LLMClient.layer),
-        Effect.provide(Layer.mergeAll(RequestExecutor.defaultLayer, WebSocketExecutor.layer)),
-      ),
-    )
-
-    expect(captures).toHaveLength(1)
-    expect(captures[0]).toMatchObject({
-      url: "https://api.openai.com/v1/responses",
-      body: {
-        model: "gpt-5-mini",
-        instructions: "You are concise.",
-        input: [{ role: "user", content: [{ type: "input_text", text: "hello" }] }],
+  it.effect("omits non-persisted OpenAI reasoning ids without encrypted state", () =>
+    expectOpenAIResponsesRequest({
+      history: [
+        storedSession.user("What changed?"),
+        storedSession.assistant([
+          storedSession.openaiReasoning("Checked the previous diff.", {
+            storedAs: "providerOptions",
+            itemId: "rs_1",
+            encryptedContent: null,
+          }),
+          storedSession.text("The parser changed."),
+        ]),
+        storedSession.user("Summarize it."),
+      ],
+      providerOptions: { openai: { store: false } },
+      expectedBody: {
+        input: [
+          openAIResponses.user("What changed?"),
+          openAIResponses.assistant("The parser changed."),
+          openAIResponses.user("Summarize it."),
+        ],
+        store: false,
      },
-    })
-    expect(events).toEqual(
-      expect.arrayContaining([
-        expect.objectContaining({ type: "text-delta", text: "Hello" }),
-        expect.objectContaining({ type: "finish" }),
-      ]),
-    )
-  })
+    }),
+  )
+
+  it.effect("preserves encrypted OpenAI reasoning state through native request lowering", () =>
+    expectOpenAIResponsesRequest({
+      history: [
+        storedSession.user("What changed?"),
+        storedSession.assistant([
+          storedSession.openaiReasoning("Checked the previous diff.", {
+            storedAs: "providerMetadata",
+            itemId: "rs_1",
+            encryptedContent: "encrypted-state",
+          }),
+          storedSession.text("The parser changed."),
+        ]),
+        storedSession.user("Summarize it."),
+      ],
+      providerOptions: { openai: { store: false, includeEncryptedReasoning: true } },
+      expectedBody: {
+        input: [
+          openAIResponses.user("What changed?"),
+          openAIResponses.openaiReasoning("Checked the previous diff.", {
+            itemId: "rs_1",
+            encryptedContent: "encrypted-state",
+          }),
+          openAIResponses.assistant("The parser changed."),
+          openAIResponses.user("Summarize it."),
+        ],
+        include: ["reasoning.encrypted_content"],
+        store: false,
+      },
+    }),
+  )
+
+  it.effect("uses provider fetch override for native OpenAI OAuth requests", () =>
+    Effect.gen(function* () {
+      const captures: Array<{ url: string; body: unknown }> = []
+      const customFetch = Object.assign(
+        async (input: Parameters<typeof fetch>[0], init: Parameters<typeof fetch>[1]) => {
+          const request = input instanceof Request ? input : new Request(input, init)
+          captures.push({ url: request.url, body: await request.clone().json() })
+          return responsesStream([
+            { type: "response.output_text.delta", item_id: "msg_1", delta: "Hello" },
+            { type: "response.completed", response: { usage: { input_tokens: 1, output_tokens: 1 } } },
+          ])
+        },
+        { preconnect: () => undefined },
+      ) satisfies typeof fetch
+
+      const llmClient = yield* LLMClient.Service
+      const native = LLMNativeRuntime.stream({
+        model: baseModel,
+        provider: { ...providerInfo, options: { apiKey: OAUTH_DUMMY_KEY, fetch: customFetch } },
+        auth: { type: "oauth", refresh: "refresh", access: "access", expires: Date.now() + 60_000 },
+        llmClient,
+        messages: [{ role: "user", content: "hello" }],
+        tools: {},
+        providerOptions: { instructions: "You are concise." },
+        headers: {},
+        abort: new AbortController().signal,
+      })
+      expect(native.type).toBe("supported")
+      if (native.type === "unsupported") throw new Error(native.reason)
+      const events = Array.from(yield* native.stream.pipe(Stream.runCollect))
+
+      expect(captures).toHaveLength(1)
+      expect(captures[0]).toMatchObject({
+        url: "https://api.openai.com/v1/responses",
+        body: {
+          model: "gpt-5-mini",
+          instructions: "You are concise.",
+          input: [{ role: "user", content: [{ type: "input_text", text: "hello" }] }],
+        },
+      })
+      expect(events).toEqual(
+        expect.arrayContaining([
+          expect.objectContaining({ type: "text-delta", text: "Hello" }),
+          expect.objectContaining({ type: "finish" }),
+        ]),
+      )
+    }),
+  )
 })
@@ -0,0 +1,201 @@
+import { describe, expect } from "bun:test"
+import { jsonSchema } from "ai"
+import { Effect, Exit, Layer } from "effect"
+import { Agent } from "@/agent/agent"
+import { MCP } from "@/mcp"
+import { Permission } from "@/permission"
+import { ProjectID } from "@/project/schema"
+import { ModelID, ProviderID } from "@/provider/schema"
+import type { Provider } from "@/provider/provider"
+import { SessionTools } from "@/session/tools"
+import { MessageV2 } from "@/session/message-v2"
+import { MessageID, SessionID } from "@/session/schema"
+import { ToolRegistry } from "@/tool/registry"
+import { Truncate } from "@/tool/truncate"
+import { Plugin } from "@/plugin"
+import { testEffect } from "../lib/effect"
+
+const it = testEffect(
+  Layer.mergeAll(
+    Layer.succeed(
+      ToolRegistry.Service,
+      ToolRegistry.Service.of({
+        ids: () => Effect.succeed([]),
+        all: () => Effect.succeed([]),
+        named: () => Effect.die("unexpected named tool lookup"),
+        tools: () => Effect.succeed([]),
+      }),
+    ),
+    Layer.succeed(
+      MCP.Service,
+      MCP.Service.of({
+        status: () => Effect.succeed({}),
+        clients: () => Effect.succeed({}),
+        tools: () =>
+          Effect.succeed({
+            ctx_batch_execute: {
+              description: "context tool",
+              inputSchema: jsonSchema({
+                type: "object",
+                properties: {
+                  batch: {
+                    type: "array",
+                    items: schemaWithZodInternals(),
+                  },
+                },
+              }),
+              execute: () => Promise.resolve({ content: [{ type: "text" as const, text: "ok" }] }),
+            },
+          }),
+        prompts: () => Effect.succeed({}),
+        resources: () => Effect.succeed({}),
+        add: () => Effect.succeed({ status: { status: "disabled" as const } }),
+        connect: () => Effect.void,
+        disconnect: () => Effect.void,
+        getPrompt: () => Effect.succeed(undefined),
+        readResource: () => Effect.succeed(undefined),
+        startAuth: () => Effect.die("unexpected MCP auth"),
+        authenticate: () => Effect.die("unexpected MCP auth"),
+        finishAuth: () => Effect.die("unexpected MCP auth"),
+        removeAuth: () => Effect.void,
+        supportsOAuth: () => Effect.succeed(false),
+        hasStoredTokens: () => Effect.succeed(false),
+        getAuthStatus: () => Effect.succeed("not_authenticated" as const),
+      }),
+    ),
+    Layer.succeed(
+      Plugin.Service,
+      Plugin.Service.of({
+        trigger: (_name, _input, output) => Effect.succeed(output),
+        list: () => Effect.succeed([]),
+        init: () => Effect.void,
+      }),
+    ),
+    Layer.succeed(
+      Permission.Service,
+      Permission.Service.of({
+        ask: () => Effect.void,
+        reply: () => Effect.void,
+        list: () => Effect.succeed([]),
+      }),
+    ),
+    Layer.succeed(
+      Truncate.Service,
+      Truncate.Service.of({
+        cleanup: () => Effect.void,
+        write: () => Effect.succeed("/tmp/tool-output"),
+        output: (text) => Effect.succeed({ content: text, truncated: false as const }),
+        limits: () => Effect.succeed({ maxLines: 2000, maxBytes: 50 * 1024 }),
+      }),
+    ),
+  ),
+)
+
+describe("SessionTools.resolve", () => {
+  it.effect("fails locally when MCP schemas contain Zod internals", () =>
+    Effect.gen(function* () {
+      const exit = yield* SessionTools.resolve({
+        agent: agentInfo(),
+        model: kimiModel(),
+        session: sessionInfo(),
+        processor: processor(),
+        bypassAgentCheck: false,
+        messages: [],
+        promptOps: promptOps(),
+      }).pipe(Effect.exit)
+
+      expect(Exit.isFailure(exit)).toBe(true)
+      if (!Exit.isFailure(exit)) return
+
+      expect(String(exit.cause)).toContain("ctx_batch_execute")
+      expect(String(exit.cause)).toContain("non-JSON-Schema Zod internals")
+      expect(String(exit.cause)).toContain("$.properties.batch.items._zod")
+    }),
+  )
+})
+
+function agentInfo(): Agent.Info {
+  return {
+    name: "build",
+    mode: "primary",
+    permission: [],
+    options: {},
+  }
+}
+
+function schemaWithZodInternals() {
+  return JSON.parse(
+    JSON.stringify({
+      _zod: { def: { type: "object" } },
+      def: { type: "object" },
+      typeName: "ZodObject",
+      "~standard": { vendor: "zod" },
+    }),
+  )
+}
+
+function kimiModel(): Provider.Model {
+  return {
+    id: ModelID.make("kimi-k2.6"),
+    providerID: ProviderID.make("moonshotai"),
+    name: "Kimi K2.6",
+    limit: { context: 128_000, output: 32_000 },
+    cost: { input: 0, output: 0, cache: { read: 0, write: 0 } },
+    capabilities: {
+      toolcall: true,
+      attachment: false,
+      reasoning: false,
+      temperature: true,
+      input: { text: true, image: false, audio: false, video: false, pdf: false },
+      output: { text: true, image: false, audio: false, video: false, pdf: false },
+      interleaved: false,
+    },
+    api: { id: "kimi-k2.6", url: "https://api.moonshot.example/v1", npm: "@ai-sdk/openai-compatible" },
+    options: {},
+    headers: {},
+    release_date: "2026-01-01",
+    status: "active",
+  }
+}
+
+function sessionInfo() {
+  return {
+    id: SessionID.descending(),
+    slug: "test",
+    projectID: ProjectID.global,
+    directory: "/tmp/test",
+    title: "test",
+    version: "test",
+    time: { created: Date.now(), updated: Date.now() },
+  }
+}
+
+function processor() {
+  return {
+    message: {
+      id: MessageID.ascending(),
+      sessionID: SessionID.descending(),
+      role: "assistant",
+      parentID: MessageID.ascending(),
+      modelID: ModelID.make("kimi-k2.6"),
+      providerID: ProviderID.make("moonshotai"),
+      mode: "build",
+      agent: "build",
+      path: { cwd: "/tmp/test", root: "/tmp/test" },
+      cost: 0,
+      tokens: { input: 0, output: 0, reasoning: 0, cache: { read: 0, write: 0 } },
+      time: { created: Date.now() },
+    } satisfies MessageV2.Assistant,
+    updateToolCall: () => Effect.succeed(undefined),
+    completeToolCall: () => Effect.void,
+  }
+}
+
+function promptOps() {
+  return {
+    cancel: () => Effect.void,
+    resolvePromptParts: (template: string) => Effect.succeed([{ type: "text" as const, text: template }]),
+    prompt: () => Effect.die("unexpected prompt call"),
+    loop: () => Effect.die("unexpected loop call"),
+  }
+}
@@ -34,6 +34,7 @@ import { ProviderID, ModelID } from "@/provider/schema"
 import { ToolJsonSchema } from "@/tool/json-schema"
 import { MessageID, SessionID } from "@/session/schema"
 import { RuntimeFlags } from "@/effect/runtime-flags"
+import z3 from "zod/v3"

 const node = CrossSpawnSpawner.defaultLayer
 const configLayer = TestConfig.layer({
@@ -80,7 +81,7 @@ const brokenPluginLayer = Layer.succeed(
    init: () => Effect.void,
    trigger: ((_name: unknown, _input: unknown, output: unknown) =>
      Effect.succeed(output)) as Plugin.Interface["trigger"],
-    list: () =>
+    list: (() =>
      Effect.succeed([
        {
          tool: {
@@ -91,7 +92,41 @@ const brokenPluginLayer = Layer.succeed(
            },
          },
        },
-      ]),
+      ])) as unknown as Plugin.Interface["list"],
+  }),
+)
+
+const zod3PluginLayer = Layer.succeed(
+  Plugin.Service,
+  Plugin.Service.of({
+    init: () => Effect.void,
+    trigger: ((_name: unknown, _input: unknown, output: unknown) =>
+      Effect.succeed(output)) as Plugin.Interface["trigger"],
+    list: (() =>
+      Effect.succeed([
+        {
+          tool: {
+            ctx_batch_execute: {
+              description: "context-mode batch executor",
+              args: {
+                batch: z3
+                  .preprocess(
+                    (value) => (typeof value === "string" ? JSON.parse(value) : value),
+                    z3
+                      .array(
+                        z3.object({
+                          command: z3.string().describe("Command to execute"),
+                        }),
+                      )
+                      .min(1),
+                  )
+                  .describe("Commands to execute as a batch"),
+              },
+              execute: async () => "ok",
+            },
+          },
+        },
+      ])) as unknown as Plugin.Interface["list"],
  }),
 )

@@ -105,6 +140,7 @@ const background = testEffect(
 const withBrokenPlugin = testEffect(
  Layer.mergeAll(registryLayer({ plugin: brokenPluginLayer }), node, Agent.defaultLayer),
 )
+const withZod3Plugin = testEffect(Layer.mergeAll(registryLayer({ plugin: zod3PluginLayer }), node, Agent.defaultLayer))

 afterEach(async () => {
  await disposeAllInstances()
@@ -349,6 +385,52 @@ describe("tool.registry", () => {
    }),
  )

+  withZod3Plugin.instance("loads plugin tools with Zod 3 args as JSON Schema", () =>
+    Effect.gen(function* () {
+      const registry = yield* ToolRegistry.Service
+      const loaded = (yield* registry.all()).find((tool) => tool.id === "ctx_batch_execute")
+      if (!loaded) throw new Error("ctx_batch_execute tool was not loaded")
+
+      expect(loaded.jsonSchema).toMatchObject({
+        type: "object",
+        properties: {
+          batch: {
+            type: "array",
+            description: "Commands to execute as a batch",
+            items: {
+              type: "object",
+              properties: {
+                command: { type: "string", description: "Command to execute" },
+              },
+            },
+            minItems: 1,
+          },
+        },
+        required: ["batch"],
+      })
+      expect(JSON.stringify(loaded.jsonSchema)).not.toContain("_def")
+      expect(JSON.stringify(loaded.jsonSchema)).not.toContain("_zod")
+      expect(Result.isSuccess(Schema.decodeUnknownResult(loaded.parameters)({ batch: [{ command: "pwd" }] }))).toBe(
+        true,
+      )
+      expect(Result.isSuccess(Schema.decodeUnknownResult(loaded.parameters)({}))).toBe(false)
+    }),
+  )
+
+  withZod3Plugin.instance("validates plugin tools with Zod 3 preprocessors", () =>
+    Effect.gen(function* () {
+      const registry = yield* ToolRegistry.Service
+      const loaded = (yield* registry.all()).find((tool) => tool.id === "ctx_batch_execute")
+      if (!loaded) throw new Error("ctx_batch_execute tool was not loaded")
+
+      expect(
+        Result.isSuccess(
+          Schema.decodeUnknownResult(loaded.parameters)({ batch: JSON.stringify([{ command: "pwd" }]) }),
+        ),
+      ).toBe(true)
+    }),
+  )
+
  it.instance(
    "preserves Zod arg descriptions from older config-scoped plugin packages",
    () =>
@@ -1,7 +1,7 @@
 {
  "$schema": "https://json.schemastore.org/package.json",
  "name": "@opencode-ai/plugin",
-  "version": "1.15.6",
+  "version": "1.15.7",
  "type": "module",
  "license": "MIT",
  "scripts": {
@@ -1,7 +1,7 @@
 {
  "$schema": "https://json.schemastore.org/package.json",
  "name": "@opencode-ai/sdk",
-  "version": "1.15.6",
+  "version": "1.15.7",
  "type": "module",
  "license": "MIT",
  "scripts": {
@@ -1806,6 +1806,12 @@ export type SubtaskPartInput = {
  command?: string
 }

+export type SessionBusyError = {
+  _tag: "SessionBusyError"
+  sessionID: string
+  message: string
+}
+
 export type V2SessionsResponse = {
  items: Array<SessionInfo>
  cursor: {
@@ -6387,6 +6393,10 @@ export type SessionDeleteMessageErrors = {
   * NotFoundError
   */
  404: NotFoundError
+  /**
+   * SessionBusyError
+   */
+  409: SessionBusyError
 }

 export type SessionDeleteMessageError = SessionDeleteMessageErrors[keyof SessionDeleteMessageErrors]
@@ -6786,6 +6796,10 @@ export type SessionShellErrors = {
   * NotFoundError
   */
  404: NotFoundError
+  /**
+   * SessionBusyError
+   */
+  409: SessionBusyError
 }

 export type SessionShellError = SessionShellErrors[keyof SessionShellErrors]
@@ -6826,6 +6840,10 @@ export type SessionRevertErrors = {
   * NotFoundError
   */
  404: NotFoundError
+  /**
+   * SessionBusyError
+   */
+  409: SessionBusyError
 }

 export type SessionRevertError = SessionRevertErrors[keyof SessionRevertErrors]
@@ -6860,6 +6878,10 @@ export type SessionUnrevertErrors = {
   * NotFoundError
   */
  404: NotFoundError
+  /**
+   * SessionBusyError
+   */
+  409: SessionBusyError
 }

 export type SessionUnrevertError = SessionUnrevertErrors[keyof SessionUnrevertErrors]
@@ -6194,6 +6194,16 @@
                }
              }
            }
+          },
+          "409": {
+            "description": "SessionBusyError",
+            "content": {
+              "application/json": {
+                "schema": {
+                  "$ref": "#/components/schemas/SessionBusyError"
+                }
+              }
+            }
          }
        },
        "description": "Permanently delete a specific message and all of its parts from a session without reverting file changes.",
@@ -7123,6 +7133,16 @@
                }
              }
            }
+          },
+          "409": {
+            "description": "SessionBusyError",
+            "content": {
+              "application/json": {
+                "schema": {
+                  "$ref": "#/components/schemas/SessionBusyError"
+                }
+              }
+            }
          }
        },
        "description": "Execute a shell command within the session context and return the AI's response.",
@@ -7239,6 +7259,16 @@
                }
              }
            }
+          },
+          "409": {
+            "description": "SessionBusyError",
+            "content": {
+              "application/json": {
+                "schema": {
+                  "$ref": "#/components/schemas/SessionBusyError"
+                }
+              }
+            }
          }
        },
        "description": "Revert a specific message in a session, undoing its effects and restoring the previous state.",
@@ -7340,6 +7370,16 @@
                }
              }
            }
+          },
+          "409": {
+            "description": "SessionBusyError",
+            "content": {
+              "application/json": {
+                "schema": {
+                  "$ref": "#/components/schemas/SessionBusyError"
+                }
+              }
+            }
          }
        },
        "description": "Restore all previously reverted messages in a session.",
@@ -15668,6 +15708,23 @@
        "required": ["type", "prompt", "description", "agent"],
        "additionalProperties": false
      },
+      "SessionBusyError": {
+        "type": "object",
+        "properties": {
+          "_tag": {
+            "type": "string",
+            "enum": ["SessionBusyError"]
+          },
+          "sessionID": {
+            "type": "string"
+          },
+          "message": {
+            "type": "string"
+          }
+        },
+        "required": ["_tag", "sessionID", "message"],
+        "additionalProperties": false
+      },
      "V2SessionsResponse": {
        "type": "object",
        "properties": {
@@ -1,6 +1,6 @@
 {
  "name": "@opencode-ai/slack",
-  "version": "1.15.6",
+  "version": "1.15.7",
  "type": "module",
  "license": "MIT",
  "scripts": {
@@ -1,6 +1,6 @@
 {
  "name": "@opencode-ai/ui",
-  "version": "1.15.6",
+  "version": "1.15.7",
  "type": "module",
  "license": "MIT",
  "exports": {
@@ -2,7 +2,7 @@
  "name": "@opencode-ai/web",
  "type": "module",
  "license": "MIT",
-  "version": "1.15.6",
+  "version": "1.15.7",
  "scripts": {
    "dev": "astro dev",
    "dev:remote": "VITE_API_URL=https://api.opencode.ai astro dev",
@@ -2,7 +2,7 @@
  "name": "opencode",
  "displayName": "opencode",
  "description": "opencode for VS Code",
-  "version": "1.15.6",
+  "version": "1.15.7",
  "publisher": "sst-dev",
  "repository": {
    "type": "git",
@@ -9,6 +9,7 @@ export default $config({
      home: "cloudflare",
      providers: {
        stripe: {
+          version: "0.0.28",
          apiKey: process.env.STRIPE_SECRET_KEY!,
        },
        random: "4.19.2",
Author	SHA1	Message	Date
Kit Langton	7fa8ad4ec2	fix(tool): support zod 3 plugin schemas	2026-05-21 17:26:53 -04:00
Kit Langton	463af5e079	fix(session): reject tool schemas with zod internals	2026-05-21 16:39:56 -04:00
Kit Langton	40da77e77c	test(opencode): cover native reasoning continuation (#28683 )	2026-05-21 14:50:37 -04:00
Frank	0d2de7db65	sync	2026-05-21 14:25:43 -04:00
Frank	a568f616c9	sync	2026-05-21 13:55:31 -04:00
opencode-agent[bot]	e4957a78ea	chore: update nix node_modules hashes	2026-05-21 17:27:59 +00:00
opencode-agent[bot]	7e35cff4f5	chore: generate	2026-05-21 17:25:26 +00:00
Shoubhit Dash	82b796ce31	fix(httpapi): return session busy error bodies (#28684 )	2026-05-21 22:53:49 +05:30
Vladimir Glafirov	6c24062d2f	chore(deps): bump gitlab-ai-provider to 6.7.0 (#28218 )	2026-05-21 12:12:39 -05:00
opencode-agent[bot]	3ca09ee3ef	chore: generate	2026-05-21 16:50:49 +00:00
Kit Langton	003f1ce0f4	test(control-plane): finish porting workspace.test.ts to it.instance (#28665 )	2026-05-21 12:48:59 -04:00
Kit Langton	61390dbb49	fix(llm): preserve native continuation metadata (#28678 )	2026-05-21 11:57:45 -04:00
opencode	a58c3c53a9	sync release versions for v1.15.7	2026-05-21 15:51:26 +00:00
Victor Navarro	75ce8feff5	chore: upgrade sst version (#26224 )	2026-05-21 17:19:15 +02:00