chore: update changelog for llm-task (#1498) (thanks @vignesh07)

CHANGELOG.md

@@ -5,6 +5,7 @@ Docs: https://docs.clawd.bot
 ## 2026.1.23 (Unreleased)
 
 ### Changes
+- Plugins: add optional llm-task JSON-only tool for workflows. (#1498) Thanks @vignesh07.
 - CLI: restart the gateway by default after `clawdbot update`; add `--no-restart` to skip it.
 - CLI: add live auth probes to `clawdbot models status` for per-profile verification.
 - Docs: add cron vs heartbeat decision guide (with Lobster workflow notes). (#1533) Thanks @JustYannicc.

docs/docs.json

@@ -1000,6 +1000,8 @@
         "group": "Tools & Skills",
         "pages": [
           "tools",
+          "tools/lobster",
+          "tools/llm-task",
           "plugin",
           "plugins/voice-call",
           "plugins/zalouser",

docs/tools/index.md

@@ -156,6 +156,7 @@ alongside tools (for example, the voice-call plugin).
 
 Optional plugin tools:
 - [Lobster](/tools/lobster): typed workflow runtime with resumable approvals (requires the Lobster CLI on the gateway host).
+- [LLM Task](/tools/llm-task): JSON-only LLM step for structured workflow output (optional schema validation).
 
 ## Tool inventory
 

docs/tools/llm-task.md

@@ -0,0 +1,114 @@
+---
+summary: "JSON-only LLM tasks for workflows (optional plugin tool)"
+read_when:
+  - You want a JSON-only LLM step inside workflows
+  - You need schema-validated LLM output for automation
+---
+
+# LLM Task
+
+`llm-task` is an **optional plugin tool** that runs a JSON-only LLM task and
+returns structured output (optionally validated against JSON Schema).
+
+This is ideal for workflow engines like Lobster: you can add a single LLM step
+without writing custom Clawdbot code for each workflow.
+
+## Enable the plugin
+
+1) Enable the plugin:
+
+```json
+{
+  "plugins": {
+    "entries": {
+      "llm-task": { "enabled": true }
+    }
+  }
+}
+```
+
+2) Allowlist the tool (it is registered with `optional: true`):
+
+```json
+{
+  "agents": {
+    "list": [
+      {
+        "id": "main",
+        "tools": { "allow": ["llm-task"] }
+      }
+    ]
+  }
+}
+```
+
+## Config (optional)
+
+```json
+{
+  "plugins": {
+    "entries": {
+      "llm-task": {
+        "enabled": true,
+        "config": {
+          "defaultProvider": "openai-codex",
+          "defaultModel": "gpt-5.2",
+          "defaultAuthProfileId": "main",
+          "allowedModels": ["openai-codex/gpt-5.2"],
+          "maxTokens": 800,
+          "timeoutMs": 30000
+        }
+      }
+    }
+  }
+}
+```
+
+`allowedModels` is an allowlist of `provider/model` strings. If set, any request
+outside the list is rejected.
+
+## Tool parameters
+
+- `prompt` (string, required)
+- `input` (any, optional)
+- `schema` (object, optional JSON Schema)
+- `provider` (string, optional)
+- `model` (string, optional)
+- `authProfileId` (string, optional)
+- `temperature` (number, optional)
+- `maxTokens` (number, optional)
+- `timeoutMs` (number, optional)
+
+## Output
+
+Returns `details.json` containing the parsed JSON (and validates against
+`schema` when provided).
+
+## Example: Lobster workflow step
+
+```lobster
+clawd.invoke --tool llm-task --action json --args-json '{
+  "prompt": "Given the input email, return intent and draft.",
+  "input": {
+    "subject": "Hello",
+    "body": "Can you help?"
+  },
+  "schema": {
+    "type": "object",
+    "properties": {
+      "intent": { "type": "string" },
+      "draft": { "type": "string" }
+    },
+    "required": ["intent", "draft"],
+    "additionalProperties": false
+  }
+}'
+```
+
+## Safety notes
+
+- The tool is **JSON-only** and instructs the model to output only JSON (no
+  code fences, no commentary).
+- No tools are exposed to the model for this run.
+- Treat output as untrusted unless you validate with `schema`.
+- Put approvals before any side-effecting step (send, post, exec).

docs/tools/lobster.md

@@ -65,6 +65,52 @@ gog.gmail.search --query 'newer_than:1d' \
   | clawd.invoke --tool message --action send --each --item-key message --args-json '{"provider":"telegram","to":"..."}'
 ```
 
+## JSON-only LLM steps (llm-task)
+
+For workflows that need a **structured LLM step**, enable the optional
+`llm-task` plugin tool and call it from Lobster. This keeps the workflow
+deterministic while still letting you classify/summarize/draft with a model.
+
+Enable the tool:
+
+```json
+{
+  "plugins": {
+    "entries": {
+      "llm-task": { "enabled": true }
+    }
+  },
+  "agents": {
+    "list": [
+      {
+        "id": "main",
+        "tools": { "allow": ["llm-task"] }
+      }
+    ]
+  }
+}
+```
+
+Use it in a pipeline:
+
+```lobster
+clawd.invoke --tool llm-task --action json --args-json '{
+  "prompt": "Given the input email, return intent and draft.",
+  "input": { "subject": "Hello", "body": "Can you help?" },
+  "schema": {
+    "type": "object",
+    "properties": {
+      "intent": { "type": "string" },
+      "draft": { "type": "string" }
+    },
+    "required": ["intent", "draft"],
+    "additionalProperties": false
+  }
+}'
+```
+
+See [LLM Task](/tools/llm-task) for details and configuration options.
+
 ## Workflow files (.lobster)
 
 Lobster can run YAML/JSON workflow files with `name`, `args`, `steps`, `env`, `condition`, and `approval` fields. In Clawdbot tool calls, set `pipeline` to the file path.

extensions/llm-task/README.md

@@ -0,0 +1,97 @@
+# LLM Task (plugin)
+
+Adds an **optional** agent tool `llm-task` for running **JSON-only** LLM tasks
+(drafting, summarizing, classifying) with optional JSON Schema validation.
+
+Designed to be called from workflow engines (for example, Lobster via
+`clawd.invoke --each`) without adding new Clawdbot code per workflow.
+
+## Enable
+
+1) Enable the plugin:
+
+```json
+{
+  "plugins": {
+    "entries": {
+      "llm-task": { "enabled": true }
+    }
+  }
+}
+```
+
+2) Allowlist the tool (it is registered with `optional: true`):
+
+```json
+{
+  "agents": {
+    "list": [
+      {
+        "id": "main",
+        "tools": { "allow": ["llm-task"] }
+      }
+    ]
+  }
+}
+```
+
+## Config (optional)
+
+```json
+{
+  "plugins": {
+    "entries": {
+      "llm-task": {
+        "enabled": true,
+        "config": {
+          "defaultProvider": "openai-codex",
+          "defaultModel": "gpt-5.2",
+          "defaultAuthProfileId": "main",
+          "allowedModels": ["openai-codex/gpt-5.2"],
+          "maxTokens": 800,
+          "timeoutMs": 30000
+        }
+      }
+    }
+  }
+}
+```
+
+`allowedModels` is an allowlist of `provider/model` strings. If set, any request
+outside the list is rejected.
+
+## Tool API
+
+### Parameters
+
+- `prompt` (string, required)
+- `input` (any, optional)
+- `schema` (object, optional JSON Schema)
+- `provider` (string, optional)
+- `model` (string, optional)
+- `authProfileId` (string, optional)
+- `temperature` (number, optional)
+- `maxTokens` (number, optional)
+- `timeoutMs` (number, optional)
+
+### Output
+
+Returns `details.json` containing the parsed JSON (and validates against
+`schema` when provided).
+
+## Notes
+
+- The tool is **JSON-only** and instructs the model to output only JSON
+  (no code fences, no commentary).
+- No tools are exposed to the model for this run.
+- Side effects should be handled outside this tool (for example, approvals in
+  Lobster) before calling tools that send messages/emails.
+
+## Bundled extension note
+
+This extension depends on Clawdbot internal modules (the embedded agent runner).
+It is intended to ship as a **bundled** Clawdbot extension (like `lobster`) and
+be enabled via `plugins.entries` + tool allowlists.
+
+It is **not** currently designed to be copied into
+`~/.clawdbot/extensions` as a standalone plugin directory.

extensions/llm-task/clawdbot.plugin.json

@@ -0,0 +1,21 @@
+{
+  "id": "llm-task",
+  "name": "LLM Task",
+  "description": "Generic JSON-only LLM tool for structured tasks callable from workflows.",
+  "configSchema": {
+    "type": "object",
+    "additionalProperties": false,
+    "properties": {
+      "defaultProvider": { "type": "string" },
+      "defaultModel": { "type": "string" },
+      "defaultAuthProfileId": { "type": "string" },
+      "allowedModels": {
+        "type": "array",
+        "items": { "type": "string" },
+        "description": "Allowlist of provider/model keys like openai-codex/gpt-5.2."
+      },
+      "maxTokens": { "type": "number" },
+      "timeoutMs": { "type": "number" }
+    }
+  }
+}

extensions/llm-task/index.ts

@@ -0,0 +1,7 @@
+import type { ClawdbotPluginApi } from "../../src/plugins/types.js";
+
+import { createLlmTaskTool } from "./src/llm-task-tool.js";
+
+export default function register(api: ClawdbotPluginApi) {
+  api.registerTool(createLlmTaskTool(api), { optional: true });
+}

extensions/llm-task/package.json

@@ -0,0 +1,11 @@
+{
+  "name": "@clawdbot/llm-task",
+  "version": "2026.1.23",
+  "type": "module",
+  "description": "Clawdbot JSON-only LLM task plugin",
+  "clawdbot": {
+    "extensions": [
+      "./index.ts"
+    ]
+  }
+}

extensions/llm-task/src/llm-task-tool.test.ts

@@ -0,0 +1,117 @@
+import { describe, it, expect, vi, beforeEach } from "vitest";
+
+vi.mock("../../../src/agents/pi-embedded-runner.js", () => {
+  return {
+    runEmbeddedPiAgent: vi.fn(async () => ({
+      meta: { startedAt: Date.now() },
+      payloads: [{ text: "{}" }],
+    })),
+  };
+});
+
+import { runEmbeddedPiAgent } from "../../../src/agents/pi-embedded-runner.js";
+import { createLlmTaskTool } from "./llm-task-tool.js";
+
+function fakeApi(overrides: any = {}) {
+  return {
+    id: "llm-task",
+    name: "llm-task",
+    source: "test",
+    config: { agents: { defaults: { workspace: "/tmp", model: { primary: "openai-codex/gpt-5.2" } } } },
+    pluginConfig: {},
+    runtime: { version: "test" },
+    logger: { debug() {}, info() {}, warn() {}, error() {} },
+    registerTool() {},
+    ...overrides,
+  };
+}
+
+describe("llm-task tool (json-only)", () => {
+  beforeEach(() => vi.clearAllMocks());
+
+  it("returns parsed json", async () => {
+    (runEmbeddedPiAgent as any).mockResolvedValueOnce({
+      meta: {},
+      payloads: [{ text: JSON.stringify({ foo: "bar" }) }],
+    });
+    const tool = createLlmTaskTool(fakeApi() as any);
+    const res = await tool.execute("id", { prompt: "return foo" });
+    expect((res as any).details.json).toEqual({ foo: "bar" });
+  });
+
+  it("strips fenced json", async () => {
+    (runEmbeddedPiAgent as any).mockResolvedValueOnce({
+      meta: {},
+      payloads: [{ text: "```json\n{\"ok\":true}\n```" }],
+    });
+    const tool = createLlmTaskTool(fakeApi() as any);
+    const res = await tool.execute("id", { prompt: "return ok" });
+    expect((res as any).details.json).toEqual({ ok: true });
+  });
+
+  it("validates schema", async () => {
+    (runEmbeddedPiAgent as any).mockResolvedValueOnce({
+      meta: {},
+      payloads: [{ text: JSON.stringify({ foo: "bar" }) }],
+    });
+    const tool = createLlmTaskTool(fakeApi() as any);
+    const schema = {
+      type: "object",
+      properties: { foo: { type: "string" } },
+      required: ["foo"],
+      additionalProperties: false,
+    };
+    const res = await tool.execute("id", { prompt: "return foo", schema });
+    expect((res as any).details.json).toEqual({ foo: "bar" });
+  });
+
+  it("throws on invalid json", async () => {
+    (runEmbeddedPiAgent as any).mockResolvedValueOnce({ meta: {}, payloads: [{ text: "not-json" }] });
+    const tool = createLlmTaskTool(fakeApi() as any);
+    await expect(tool.execute("id", { prompt: "x" })).rejects.toThrow(/invalid json/i);
+  });
+
+  it("throws on schema mismatch", async () => {
+    (runEmbeddedPiAgent as any).mockResolvedValueOnce({
+      meta: {},
+      payloads: [{ text: JSON.stringify({ foo: 1 }) }],
+    });
+    const tool = createLlmTaskTool(fakeApi() as any);
+    const schema = { type: "object", properties: { foo: { type: "string" } }, required: ["foo"] };
+    await expect(tool.execute("id", { prompt: "x", schema })).rejects.toThrow(/match schema/i);
+  });
+
+  it("passes provider/model overrides to embedded runner", async () => {
+    (runEmbeddedPiAgent as any).mockResolvedValueOnce({
+      meta: {},
+      payloads: [{ text: JSON.stringify({ ok: true }) }],
+    });
+    const tool = createLlmTaskTool(fakeApi() as any);
+    await tool.execute("id", { prompt: "x", provider: "anthropic", model: "claude-4-sonnet" });
+    const call = (runEmbeddedPiAgent as any).mock.calls[0]?.[0];
+    expect(call.provider).toBe("anthropic");
+    expect(call.model).toBe("claude-4-sonnet");
+  });
+
+  it("enforces allowedModels", async () => {
+    (runEmbeddedPiAgent as any).mockResolvedValueOnce({
+      meta: {},
+      payloads: [{ text: JSON.stringify({ ok: true }) }],
+    });
+    const tool = createLlmTaskTool(fakeApi({ pluginConfig: { allowedModels: ["openai-codex/gpt-5.2"] } }) as any);
+    await expect(tool.execute("id", { prompt: "x", provider: "anthropic", model: "claude-4-sonnet" })).rejects.toThrow(
+      /not allowed/i,
+    );
+  });
+
+  it("disables tools for embedded run", async () => {
+    (runEmbeddedPiAgent as any).mockResolvedValueOnce({
+      meta: {},
+      payloads: [{ text: JSON.stringify({ ok: true }) }],
+    });
+    const tool = createLlmTaskTool(fakeApi() as any);
+    await tool.execute("id", { prompt: "x" });
+    const call = (runEmbeddedPiAgent as any).mock.calls[0]?.[0];
+    expect(call.disableTools).toBe(true);
+  });
+});

extensions/llm-task/src/llm-task-tool.ts

@@ -0,0 +1,218 @@
+import os from "node:os";
+import path from "node:path";
+import fs from "node:fs/promises";
+
+import Ajv from "ajv";
+import { Type } from "@sinclair/typebox";
+
+// NOTE: This extension is intended to be bundled with Clawdbot.
+// When running from source (tests/dev), Clawdbot internals live under src/.
+// When running from a built install, internals live under dist/ (no src/ tree).
+// So we resolve internal imports dynamically with src-first, dist-fallback.
+
+import type { ClawdbotPluginApi } from "../../../src/plugins/types.js";
+
+type RunEmbeddedPiAgentFn = (params: Record<string, unknown>) => Promise<unknown>;
+
+async function loadRunEmbeddedPiAgent(): Promise<RunEmbeddedPiAgentFn> {
+  // Source checkout (tests/dev)
+  try {
+    const mod = await import("../../../src/agents/pi-embedded-runner.js");
+    if (typeof (mod as any).runEmbeddedPiAgent === "function") return (mod as any).runEmbeddedPiAgent;
+  } catch {
+    // ignore
+  }
+
+  // Bundled install (built)
+  const mod = await import("../../../agents/pi-embedded-runner.js");
+  if (typeof (mod as any).runEmbeddedPiAgent !== "function") {
+    throw new Error("Internal error: runEmbeddedPiAgent not available");
+  }
+  return (mod as any).runEmbeddedPiAgent;
+}
+
+function stripCodeFences(s: string): string {
+  const trimmed = s.trim();
+  const m = trimmed.match(/^```(?:json)?\s*([\s\S]*?)\s*```$/i);
+  if (m) return (m[1] ?? "").trim();
+  return trimmed;
+}
+
+function collectText(payloads: Array<{ text?: string; isError?: boolean }> | undefined): string {
+  const texts = (payloads ?? [])
+    .filter((p) => !p.isError && typeof p.text === "string")
+    .map((p) => p.text ?? "");
+  return texts.join("\n").trim();
+}
+
+function toModelKey(provider?: string, model?: string): string | undefined {
+  const p = provider?.trim();
+  const m = model?.trim();
+  if (!p || !m) return undefined;
+  return `${p}/${m}`;
+}
+
+type PluginCfg = {
+  defaultProvider?: string;
+  defaultModel?: string;
+  defaultAuthProfileId?: string;
+  allowedModels?: string[];
+  maxTokens?: number;
+  timeoutMs?: number;
+};
+
+export function createLlmTaskTool(api: ClawdbotPluginApi) {
+  return {
+    name: "llm-task",
+    description:
+      "Run a generic JSON-only LLM task and return schema-validated JSON. Designed for orchestration from Lobster workflows via clawd.invoke.",
+    parameters: Type.Object({
+      prompt: Type.String({ description: "Task instruction for the LLM." }),
+      input: Type.Optional(Type.Unknown({ description: "Optional input payload for the task." })),
+      schema: Type.Optional(Type.Unknown({ description: "Optional JSON Schema to validate the returned JSON." })),
+      provider: Type.Optional(Type.String({ description: "Provider override (e.g. openai-codex, anthropic)." })),
+      model: Type.Optional(Type.String({ description: "Model id override." })),
+      authProfileId: Type.Optional(Type.String({ description: "Auth profile override." })),
+      temperature: Type.Optional(Type.Number({ description: "Best-effort temperature override." })),
+      maxTokens: Type.Optional(Type.Number({ description: "Best-effort maxTokens override." })),
+      timeoutMs: Type.Optional(Type.Number({ description: "Timeout for the LLM run." })),
+    }),
+
+    async execute(_id: string, params: Record<string, unknown>) {
+      const prompt = String(params.prompt ?? "");
+      if (!prompt.trim()) throw new Error("prompt required");
+
+      const pluginCfg = (api.pluginConfig ?? {}) as PluginCfg;
+
+      const primary = api.config?.agents?.defaults?.model?.primary;
+      const primaryProvider = typeof primary === "string" ? primary.split("/")[0] : undefined;
+      const primaryModel = typeof primary === "string" ? primary.split("/").slice(1).join("/") : undefined;
+
+      const provider =
+        (typeof params.provider === "string" && params.provider.trim()) ||
+        (typeof pluginCfg.defaultProvider === "string" && pluginCfg.defaultProvider.trim()) ||
+        primaryProvider ||
+        undefined;
+
+      const model =
+        (typeof params.model === "string" && params.model.trim()) ||
+        (typeof pluginCfg.defaultModel === "string" && pluginCfg.defaultModel.trim()) ||
+        primaryModel ||
+        undefined;
+
+      const authProfileId =
+        (typeof (params as any).authProfileId === "string" && (params as any).authProfileId.trim()) ||
+        (typeof pluginCfg.defaultAuthProfileId === "string" && pluginCfg.defaultAuthProfileId.trim()) ||
+        undefined;
+
+      const modelKey = toModelKey(provider, model);
+      if (!provider || !model || !modelKey) {
+        throw new Error(
+          `provider/model could not be resolved (provider=${String(provider ?? "")}, model=${String(model ?? "")})`,
+        );
+      }
+
+      const allowed = Array.isArray(pluginCfg.allowedModels) ? pluginCfg.allowedModels : undefined;
+      if (allowed && allowed.length > 0 && !allowed.includes(modelKey)) {
+        throw new Error(
+          `Model not allowed by llm-task plugin config: ${modelKey}. Allowed models: ${allowed.join(", ")}`,
+        );
+      }
+
+      const timeoutMs =
+        (typeof params.timeoutMs === "number" && params.timeoutMs > 0 ? params.timeoutMs : undefined) ||
+        (typeof pluginCfg.timeoutMs === "number" && pluginCfg.timeoutMs > 0 ? pluginCfg.timeoutMs : undefined) ||
+        30_000;
+
+      const streamParams = {
+        temperature: typeof params.temperature === "number" ? params.temperature : undefined,
+        maxTokens:
+          typeof params.maxTokens === "number"
+            ? params.maxTokens
+            : typeof pluginCfg.maxTokens === "number"
+              ? pluginCfg.maxTokens
+              : undefined,
+      };
+
+      const input = (params as any).input as unknown;
+      let inputJson: string;
+      try {
+        inputJson = JSON.stringify(input ?? null, null, 2);
+      } catch {
+        throw new Error("input must be JSON-serializable");
+      }
+
+      const system = [
+        "You are a JSON-only function.",
+        "Return ONLY a valid JSON value.",
+        "Do not wrap in markdown fences.",
+        "Do not include commentary.",
+        "Do not call tools.",
+      ].join(" ");
+
+      const fullPrompt = `${system}\n\nTASK:\n${prompt}\n\nINPUT_JSON:\n${inputJson}\n`;
+
+      let tmpDir: string | null = null;
+      try {
+        tmpDir = await fs.mkdtemp(path.join(os.tmpdir(), "clawdbot-llm-task-"));
+        const sessionId = `llm-task-${Date.now()}`;
+        const sessionFile = path.join(tmpDir, "session.json");
+
+        const runEmbeddedPiAgent = await loadRunEmbeddedPiAgent();
+
+        const result = await runEmbeddedPiAgent({
+          sessionId,
+          sessionFile,
+          workspaceDir: api.config?.agents?.defaults?.workspace ?? process.cwd(),
+          config: api.config,
+          prompt: fullPrompt,
+          timeoutMs,
+          runId: `llm-task-${Date.now()}`,
+          provider,
+          model,
+          authProfileId,
+          authProfileIdSource: authProfileId ? "user" : "auto",
+          streamParams,
+          disableTools: true,
+        });
+
+        const text = collectText((result as any).payloads);
+        if (!text) throw new Error("LLM returned empty output");
+
+        const raw = stripCodeFences(text);
+        let parsed: unknown;
+        try {
+          parsed = JSON.parse(raw);
+        } catch {
+          throw new Error("LLM returned invalid JSON");
+        }
+
+        const schema = (params as any).schema as unknown;
+        if (schema && typeof schema === "object" && !Array.isArray(schema)) {
+          const ajv = new Ajv({ allErrors: true, strict: false });
+          const validate = ajv.compile(schema as any);
+          const ok = validate(parsed);
+          if (!ok) {
+            const msg =
+              validate.errors?.map((e) => `${e.instancePath || "<root>"} ${e.message || "invalid"}`).join("; ") ??
+              "invalid";
+            throw new Error(`LLM JSON did not match schema: ${msg}`);
+          }
+        }
+
+        return {
+          content: [{ type: "text", text: JSON.stringify(parsed, null, 2) }],
+          details: { json: parsed, provider, model },
+        };
+      } finally {
+        if (tmpDir) {
+          try {
+            await fs.rm(tmpDir, { recursive: true, force: true });
+          } catch {
+            // ignore
+          }
+        }
+      }
+    },
+  };
+}

src/agents/pi-embedded-runner/run.ts

@@ -273,6 +273,7 @@ export async function runEmbeddedPiAgent(
             skillsSnapshot: params.skillsSnapshot,
             prompt,
             images: params.images,
+            disableTools: params.disableTools,
             provider,
             modelId,
             model,

src/agents/pi-embedded-runner/run/attempt.ts

@@ -196,30 +196,32 @@ export async function runEmbeddedAttempt(
 
     // Check if the model supports native image input
     const modelHasVision = params.model.input?.includes("image") ?? false;
-    const toolsRaw = createClawdbotCodingTools({
+    const toolsRaw = params.disableTools
-      exec: {
+      ? []
-        ...params.execOverrides,
+      : createClawdbotCodingTools({
-        elevated: params.bashElevated,
+          exec: {
-      },
+            ...params.execOverrides,
-      sandbox,
+            elevated: params.bashElevated,
-      messageProvider: params.messageChannel ?? params.messageProvider,
+          },
-      agentAccountId: params.agentAccountId,
+          sandbox,
-      messageTo: params.messageTo,
+          messageProvider: params.messageChannel ?? params.messageProvider,
-      messageThreadId: params.messageThreadId,
+          agentAccountId: params.agentAccountId,
-      sessionKey: params.sessionKey ?? params.sessionId,
+          messageTo: params.messageTo,
-      agentDir,
+          messageThreadId: params.messageThreadId,
-      workspaceDir: effectiveWorkspace,
+          sessionKey: params.sessionKey ?? params.sessionId,
-      config: params.config,
+          agentDir,
-      abortSignal: runAbortController.signal,
+          workspaceDir: effectiveWorkspace,
-      modelProvider: params.model.provider,
+          config: params.config,
-      modelId: params.modelId,
+          abortSignal: runAbortController.signal,
-      modelAuthMode: resolveModelAuthMode(params.model.provider, params.config),
+          modelProvider: params.model.provider,
-      currentChannelId: params.currentChannelId,
+          modelId: params.modelId,
-      currentThreadTs: params.currentThreadTs,
+          modelAuthMode: resolveModelAuthMode(params.model.provider, params.config),
-      replyToMode: params.replyToMode,
+          currentChannelId: params.currentChannelId,
-      hasRepliedRef: params.hasRepliedRef,
+          currentThreadTs: params.currentThreadTs,
-      modelHasVision,
+          replyToMode: params.replyToMode,
-    });
+          hasRepliedRef: params.hasRepliedRef,
+          modelHasVision,
+        });
     const tools = sanitizeToolsForGoogle({ tools: toolsRaw, provider: params.provider });
     logToolSchemasForGoogle({ tools, provider: params.provider });
 

src/agents/pi-embedded-runner/run/params.ts

@@ -44,6 +44,8 @@ export type RunEmbeddedPiAgentParams = {
   images?: ImageContent[];
   /** Optional client-provided tools (OpenResponses hosted tools). */
   clientTools?: ClientToolDefinition[];
+  /** Disable built-in tools for this run (LLM-only mode). */
+  disableTools?: boolean;
   provider?: string;
   model?: string;
   authProfileId?: string;

src/agents/pi-embedded-runner/run/types.ts

@@ -36,6 +36,8 @@ export type EmbeddedRunAttemptParams = {
   images?: ImageContent[];
   /** Optional client-provided tools (OpenResponses hosted tools). */
   clientTools?: ClientToolDefinition[];
+  /** Disable built-in tools for this run (LLM-only mode). */
+  disableTools?: boolean;
   provider: string;
   modelId: string;
   model: Model<Api>;