add-tool

name: add-tool description: Scaffold and implement a new MCP tool end-to-end — endpoint, handler, registration, docs argument-hint: "[tool-name and description]"

Add a new MCP tool: $ARGUMENTS

Do NOT start coding immediately. Follow this workflow.

Phase 1 — Understand

1. What does this tool do? Restate in one sentence
2. Which API endpoint does it call? (GET/POST/PATCH/DELETE + path)
3. What category does it belong to? (testruns, testcases, manual-testcases, manual-testsuites, or new category)
4. What params does it need? (required vs optional)
5. What does the API response look like?

If any of these are unclear, ask before proceeding.

Phase 2 — Plan

List every file that needs to be created or modified:

1. src/lib/endpoints.ts — new endpoint URL builder
2. src/tools/<category>/<tool-name>.ts — new tool file
3. src/tools/index.ts — barrel export
4. src/index.ts — tool registration + routing
5. docs/TOOLS.md — tool documentation
6. docs/skill.md — if it affects AI agent workflows

Get user approval before writing code.

Phase 3 — Implement

Follow this exact order:

Step 1: Endpoint (src/lib/endpoints.ts)

Add a new method to the endpoints object. Follow the existing pattern:

toolName: (params: { projectId: string /* other params */ }): string => {
  const baseUrl = getBaseUrl();
  const { projectId, ...queryParams } = params;
  const queryString = buildQueryString(queryParams);
  return `${baseUrl}/api/mcp/${projectId}/endpoint-path${queryString}`;
};

Run: npm run typecheck

Step 2: Tool file (src/tools//.ts)

Create the tool file with exactly two exports:

export const toolNameTool = {
  name: "tool_name",
  description: "...",  // Write for AI agents — be specific about when to use this
  inputSchema: {
    type: "object",
    properties: { /* every property MUST have a description */ },
    required: [/* required params */]
  }
};

export async function handleToolName(args: Record<string, unknown>) {
  // 1. Auth
  const token = getApiKey(args);
  if (!token) throw new Error("Missing TESTDINO_PAT...");

  // 2. Validate required params
  if (!args?.projectId) throw new Error("projectId is required");

  // 3. Build URL
  const url = endpoints.toolName({ projectId: String(args.projectId), ... });

  // 4. Fetch
  const response = await apiRequestJson(url, {
    headers: { Authorization: `Bearer ${token}` }
  });

  // 5. Return formatted
  return {
    content: [{ type: "text", text: JSON.stringify(response, null, 2) }]
  };
}

Run: npm run typecheck

Step 3: Barrel export (src/tools/index.ts)

Add export line following existing pattern:

export { toolNameTool, handleToolName } from "./<category>/<tool-name>.js";

Run: npm run typecheck

Step 4: Registration (src/index.ts)

Two changes:

1. Add to imports at the top
2. Add to the tools array
3. Add routing if-block in the CallToolRequestSchema handler

Run: npm run typecheck && npm run lint

Step 5: Tests

Add test file at tests/tools/<category>/<tool-name>.test.ts covering:

• Missing PAT returns error
• Missing required params returns error
• Successful response is properly formatted
• API error is properly wrapped

Run: npm run test

Phase 4 — Document

1. Add full documentation to docs/TOOLS.md following existing format
2. Update docs/skill.md if the tool creates a new workflow or decision path
3. Update the tool count in README.md if applicable

Phase 5 — Final Verify

npm run format && npm run typecheck && npm run lint && npm run test && npm run build

All must pass. git diff to confirm only intentional changes.

Rules

• Follow existing patterns exactly — consistency over cleverness
• Every inputSchema property MUST have a description (AI agents depend on these)
• Tool descriptions must be specific enough for an AI to choose the right tool
• Never skip the endpoint step — all URLs go through endpoints.ts
• Run typecheck after EACH step, not just at the end