fix(kimi-coding): normalize anthropic tool payload format

CHANGELOG.md

@@ -35,6 +35,7 @@ Docs: https://docs.openclaw.ai
 - OpenAI Codex OAuth/login hardening: fail OAuth completion early when the returned token is missing `api.responses.write`, and allow `openclaw models auth login --provider openai-codex` to use the built-in OAuth path even when no provider plugins are installed. (#36660) Thanks @driesvints.
 - OpenAI Codex OAuth/scope request parity: augment the OAuth authorize URL with required API scopes (`api.responses.write`, `model.request`, `api.model.read`) before browser handoff so OAuth tokens include runtime model/request permissions expected by OpenAI API calls. (#24720) Thanks @Skippy-Gunboat.
 - Onboarding/API key input hardening: strip non-Latin1 Unicode artifacts from normalized secret input (while preserving Latin-1 content and internal spaces) so malformed copied API keys cannot trigger HTTP header `ByteString` construction crashes; adds regression coverage for shared normalization and MiniMax auth header usage. (#24496) Thanks @fa6maalassaf.
+- Kimi Coding/Anthropic tools compatibility: normalize `anthropic-messages` tool payloads to OpenAI-style `tools[].function` + compatible `tool_choice` when targeting Kimi Coding endpoints, restoring tool-call workflows that regressed after v2026.3.2. (#37038) Thanks @mochimochimochi-hub.
 - Gateway/remote WS break-glass hostname support: honor `OPENCLAW_ALLOW_INSECURE_PRIVATE_WS=1` for `ws://` hostname URLs (not only private IP literals) across onboarding validation and runtime gateway connection checks, while still rejecting public IP literals and non-unicast IPv6 endpoints. (#36930) Thanks @manju-rn.
 - Routing/binding lookup scalability: pre-index route bindings by channel/account and avoid full binding-list rescans on channel-account cache rollover, preventing multi-second `resolveAgentRoute` stalls in large binding configurations. (#36915) Thanks @songchenghao.
 - Browser/session cleanup: track browser tabs opened by session-scoped browser tool runs and close tracked tabs during `sessions.reset`/`sessions.delete` runtime cleanup, preventing orphaned tabs and unbounded browser memory growth after session teardown. (#36666) Thanks @Harnoor6693.

src/agents/pi-embedded-runner-extraparams.test.ts

@@ -497,6 +497,116 @@ describe("applyExtraParamsToAgent", () => {
     expect(payloads[0]?.thinking).toEqual({ type: "disabled" });
   });
 
+  it("normalizes kimi-coding anthropic tools to OpenAI function format", () => {
+    const payloads: Record<string, unknown>[] = [];
+    const baseStreamFn: StreamFn = (_model, _context, options) => {
+      const payload: Record<string, unknown> = {
+        tools: [
+          {
+            name: "read",
+            description: "Read file",
+            input_schema: {
+              type: "object",
+              properties: { path: { type: "string" } },
+              required: ["path"],
+            },
+          },
+          {
+            type: "function",
+            function: {
+              name: "exec",
+              description: "Run command",
+              parameters: { type: "object", properties: {} },
+            },
+          },
+        ],
+        tool_choice: { type: "tool", name: "read" },
+      };
+      options?.onPayload?.(payload);
+      payloads.push(payload);
+      return {} as ReturnType<StreamFn>;
+    };
+    const agent = { streamFn: baseStreamFn };
+
+    applyExtraParamsToAgent(agent, undefined, "kimi-coding", "k2p5", undefined, "low");
+
+    const model = {
+      api: "anthropic-messages",
+      provider: "kimi-coding",
+      id: "k2p5",
+      baseUrl: "https://api.kimi.com/coding/",
+    } as Model<"anthropic-messages">;
+    const context: Context = { messages: [] };
+    void agent.streamFn?.(model, context, {});
+
+    expect(payloads).toHaveLength(1);
+    expect(payloads[0]?.tools).toEqual([
+      {
+        type: "function",
+        function: {
+          name: "read",
+          description: "Read file",
+          parameters: {
+            type: "object",
+            properties: { path: { type: "string" } },
+            required: ["path"],
+          },
+        },
+      },
+      {
+        type: "function",
+        function: {
+          name: "exec",
+          description: "Run command",
+          parameters: { type: "object", properties: {} },
+        },
+      },
+    ]);
+    expect(payloads[0]?.tool_choice).toEqual({
+      type: "function",
+      function: { name: "read" },
+    });
+  });
+
+  it("does not rewrite anthropic tool schema for non-kimi endpoints", () => {
+    const payloads: Record<string, unknown>[] = [];
+    const baseStreamFn: StreamFn = (_model, _context, options) => {
+      const payload: Record<string, unknown> = {
+        tools: [
+          {
+            name: "read",
+            description: "Read file",
+            input_schema: { type: "object", properties: {} },
+          },
+        ],
+      };
+      options?.onPayload?.(payload);
+      payloads.push(payload);
+      return {} as ReturnType<StreamFn>;
+    };
+    const agent = { streamFn: baseStreamFn };
+
+    applyExtraParamsToAgent(agent, undefined, "anthropic", "claude-sonnet-4-6", undefined, "low");
+
+    const model = {
+      api: "anthropic-messages",
+      provider: "anthropic",
+      id: "claude-sonnet-4-6",
+      baseUrl: "https://api.anthropic.com",
+    } as Model<"anthropic-messages">;
+    const context: Context = { messages: [] };
+    void agent.streamFn?.(model, context, {});
+
+    expect(payloads).toHaveLength(1);
+    expect(payloads[0]?.tools).toEqual([
+      {
+        name: "read",
+        description: "Read file",
+        input_schema: { type: "object", properties: {} },
+      },
+    ]);
+  });
+
   it("removes invalid negative Google thinkingBudget and maps Gemini 3.1 to thinkingLevel", () => {
     const payloads: Record<string, unknown>[] = [];
     const baseStreamFn: StreamFn = (_model, _context, options) => {

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

@@ -661,6 +661,117 @@ function createMoonshotThinkingWrapper(
   };
 }
 
+function isKimiCodingAnthropicEndpoint(model: {
+  api?: unknown;
+  provider?: unknown;
+  baseUrl?: unknown;
+}): boolean {
+  if (model.api !== "anthropic-messages") {
+    return false;
+  }
+
+  if (typeof model.provider === "string" && model.provider.trim().toLowerCase() === "kimi-coding") {
+    return true;
+  }
+
+  if (typeof model.baseUrl !== "string" || !model.baseUrl.trim()) {
+    return false;
+  }
+
+  try {
+    const parsed = new URL(model.baseUrl);
+    const host = parsed.hostname.toLowerCase();
+    const pathname = parsed.pathname.toLowerCase();
+    return host.endsWith("kimi.com") && pathname.startsWith("/coding");
+  } catch {
+    const normalized = model.baseUrl.toLowerCase();
+    return normalized.includes("kimi.com/coding");
+  }
+}
+
+function normalizeKimiCodingToolDefinition(tool: unknown): Record<string, unknown> | undefined {
+  if (!tool || typeof tool !== "object" || Array.isArray(tool)) {
+    return undefined;
+  }
+
+  const toolObj = tool as Record<string, unknown>;
+  if (toolObj.function && typeof toolObj.function === "object") {
+    return toolObj;
+  }
+
+  const rawName = typeof toolObj.name === "string" ? toolObj.name.trim() : "";
+  if (!rawName) {
+    return toolObj;
+  }
+
+  const functionSpec: Record<string, unknown> = {
+    name: rawName,
+    parameters:
+      toolObj.input_schema && typeof toolObj.input_schema === "object"
+        ? toolObj.input_schema
+        : toolObj.parameters && typeof toolObj.parameters === "object"
+          ? toolObj.parameters
+          : { type: "object", properties: {} },
+  };
+
+  if (typeof toolObj.description === "string" && toolObj.description.trim()) {
+    functionSpec.description = toolObj.description;
+  }
+  if (typeof toolObj.strict === "boolean") {
+    functionSpec.strict = toolObj.strict;
+  }
+
+  return {
+    type: "function",
+    function: functionSpec,
+  };
+}
+
+function normalizeKimiCodingToolChoice(toolChoice: unknown): unknown {
+  if (!toolChoice || typeof toolChoice !== "object" || Array.isArray(toolChoice)) {
+    return toolChoice;
+  }
+
+  const choice = toolChoice as Record<string, unknown>;
+  if (choice.type === "any") {
+    return "required";
+  }
+  if (choice.type === "tool" && typeof choice.name === "string" && choice.name.trim()) {
+    return {
+      type: "function",
+      function: { name: choice.name.trim() },
+    };
+  }
+
+  return toolChoice;
+}
+
+/**
+ * Kimi Coding's anthropic-messages endpoint expects OpenAI-style tool payloads
+ * (`tools[].function`) even when messages use Anthropic request framing.
+ */
+function createKimiCodingAnthropicToolSchemaWrapper(baseStreamFn: StreamFn | undefined): StreamFn {
+  const underlying = baseStreamFn ?? streamSimple;
+  return (model, context, options) => {
+    const originalOnPayload = options?.onPayload;
+    return underlying(model, context, {
+      ...options,
+      onPayload: (payload) => {
+        if (payload && typeof payload === "object" && isKimiCodingAnthropicEndpoint(model)) {
+          const payloadObj = payload as Record<string, unknown>;
+          if (Array.isArray(payloadObj.tools)) {
+            payloadObj.tools = payloadObj.tools
+              .map((tool) => normalizeKimiCodingToolDefinition(tool))
+              .filter((tool): tool is Record<string, unknown> => !!tool);
+          }
+          payloadObj.tool_choice = normalizeKimiCodingToolChoice(payloadObj.tool_choice);
+        }
+        originalOnPayload?.(payload);
+      },
+    });
+  };
+}
+
 /**
  * Create a streamFn wrapper that adds OpenRouter app attribution headers
  * and injects reasoning.effort based on the configured thinking level.
@@ -922,6 +1033,8 @@ export function applyExtraParamsToAgent(
     agent.streamFn = createMoonshotThinkingWrapper(agent.streamFn, moonshotThinkingType);
   }
 
+  agent.streamFn = createKimiCodingAnthropicToolSchemaWrapper(agent.streamFn);
+
   if (provider === "openrouter") {
     log.debug(`applying OpenRouter app attribution headers for ${provider}/${modelId}`);
     // "auto" is a dynamic routing model — we don't know which underlying model