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Check Blog Creation Status

check_blog_status
Read-only

Monitor a blog creation workflow by polling with its workflow ID. Receive status updates until completion, then access the published blog result.

Instructions

Poll the status of a blog-creation workflow started by create_blog. Pass the workflow_id you received from that tool. While running, call this again after poll_after_ms ms. Once done is true, status is complete or errored; when complete, result holds the published blog info.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
workflow_idYesWorkflow id returned by create_blog

Implementation Reference

  • Registration of the 'check_blog_status' tool via server.registerTool(). Includes tool name, title, description, input schema (workflow_id), readOnlyHint=true annotation, and the handler.
    server.registerTool(
      "check_blog_status",
      {
        title: "Check Blog Creation Status",
        description: "Poll the status of a blog-creation workflow started by `create_blog`. Pass the `workflow_id` you received from that tool. While running, call this again after `poll_after_ms` ms. Once `done` is true, `status` is `complete` or `errored`; when complete, `result` holds the published blog info.",
        inputSchema: {
        workflow_id: z.string().describe("Workflow id returned by create_blog"),
      },
        annotations: { readOnlyHint: true, destructiveHint: false, openWorldHint: false },
      },
      async ({ workflow_id }) => {
        const data = await apiCall(`/v1/ai/workspace/blog/status/${encodeURIComponent(workflow_id)}`, "GET");
        const payload = data?.result || data;
        return { content: [{ type: "text", text: JSON.stringify(payload, null, 2) }] };
      }
    );
  • Handler function for 'check_blog_status'. Takes { workflow_id }, calls GET /v1/ai/workspace/blog/status/{workflow_id} via apiCall(), and returns the JSON response as text content.
    async ({ workflow_id }) => {
      const data = await apiCall(`/v1/ai/workspace/blog/status/${encodeURIComponent(workflow_id)}`, "GET");
      const payload = data?.result || data;
      return { content: [{ type: "text", text: JSON.stringify(payload, null, 2) }] };
    }
  • Input schema for 'check_blog_status': expects a single 'workflow_id' string field, described as 'Workflow id returned by create_blog'.
      inputSchema: {
      workflow_id: z.string().describe("Workflow id returned by create_blog"),
    },
      annotations: { readOnlyHint: true, destructiveHint: false, openWorldHint: false },
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare `readOnlyHint: true` and `destructiveHint: false`, so the description adds value by detailing the polling behavior and expected response fields (`done`, `status`, `result`). No contradictions with annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences, no wasted words. The purpose is front-loaded, and the polling mechanics are explained efficiently. Every sentence earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple polling tool with one parameter and no output schema, the description adequately covers usage, polling intervals, and result states. It could specify the exact response structure more, but the mention of key fields suffices.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 100% coverage with a description for `workflow_id`. The description reiterates the parameter's origin from `create_blog` but does not add significant new meaning beyond the schema. Baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool polls the status of a blog-creation workflow, explicitly referencing the triggering tool `create_blog` and the `workflow_id` parameter. It distinguishes itself from sibling tools like `check_page_status` by specifying the workflow context.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides clear polling instructions: when to call after `create_blog`, the interval to wait (`poll_after_ms`), and stopping conditions (`done` true). It could be more explicit about when not to use it (e.g., versus batch variants), but the guidance is otherwise solid.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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