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create_blog

Generate a blog post on your website using AI. Describe the content and optionally schedule it for later publication.

Instructions

Create an AI-generated blog post on a website.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
website_idYesThe website ID
promptYesDescribe the blog post to create
schedule_atNoOptional ISO 8601 datetime to schedule for later

Implementation Reference

  • The main handler function that executes the 'create_blog' tool logic. It accepts website_id (required), prompt (required), and schedule_at (optional ISO 8601 datetime). It calls the API endpoint POST /v1/ai/workspace/website/{website_id}/blog with the prompt and optional schedule_at, then returns the result as JSON text.
    server.tool(
      "create_blog",
      "Create an AI-generated blog post on a website.",
      {
        website_id: z.string().describe("The website ID"),
        prompt: z.string().describe("Describe the blog post to create"),
        schedule_at: z.string().optional().describe("Optional ISO 8601 datetime to schedule for later"),
      },
      { title: "Create Blog Post", readOnlyHint: false, destructiveHint: false, openWorldHint: true },
      async ({ website_id, prompt, schedule_at }) => {
        const body = { prompt };
        if (schedule_at) body.schedule_at = schedule_at;
        const data = await apiCall(`/v1/ai/workspace/website/${website_id}/blog`, "POST", body);
        return { content: [{ type: "text", text: JSON.stringify(data, null, 2) }] };
      }
    );
  • Input schema for the create_blog tool. Defines three parameters: website_id (string, required), prompt (string, required - describes the blog post to create), and schedule_at (string, optional - ISO 8601 datetime for scheduling).
    {
      website_id: z.string().describe("The website ID"),
      prompt: z.string().describe("Describe the blog post to create"),
      schedule_at: z.string().optional().describe("Optional ISO 8601 datetime to schedule for later"),
    },
  • The tool is registered via server.tool() with the name 'create_blog', a description 'Create an AI-generated blog post on a website.', metadata { title: 'Create Blog Post', readOnlyHint: false, destructiveHint: false, openWorldHint: true }, and the async handler function.
    server.tool(
      "create_blog",
      "Create an AI-generated blog post on a website.",
      {
        website_id: z.string().describe("The website ID"),
        prompt: z.string().describe("Describe the blog post to create"),
        schedule_at: z.string().optional().describe("Optional ISO 8601 datetime to schedule for later"),
      },
      { title: "Create Blog Post", readOnlyHint: false, destructiveHint: false, openWorldHint: true },
      async ({ website_id, prompt, schedule_at }) => {
        const body = { prompt };
        if (schedule_at) body.schedule_at = schedule_at;
        const data = await apiCall(`/v1/ai/workspace/website/${website_id}/blog`, "POST", body);
        return { content: [{ type: "text", text: JSON.stringify(data, null, 2) }] };
      }
    );
Behavior3/5

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

Annotations already indicate a write operation (readOnlyHint=false) and non-destructiveness (destructiveHint=false). The description adds minimal behavioral context beyond 'AI-generated', but does not mention side effects or return values. With annotations present, the description is adequate but not enriched.

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?

The description is a single, front-loaded sentence with no wasted words. It efficiently conveys the core action and resource.

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

Completeness2/5

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

The description lacks important contextual details: it does not mention that the blog is likely created as a draft, what the tool returns (e.g., blog ID), or any effects beyond creation (openWorldHint=true). For a tool among many siblings, more context is needed for an agent to invoke correctly.

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% description coverage, so the schema itself documents parameters. The description adds no extra semantic detail beyond what is already in the schema (e.g., it does not explain the relationship between prompt and AI generation). Baseline of 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 explicitly states the verb 'create' and the resource 'AI-generated blog post on a website', making the purpose clear and distinguishable from sibling tools like create_page or update_blog. The specificity of 'AI-generated' adds clarity.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives (e.g., update_blog, publish_blog) or when not to use it. It lacks explicit context about prerequisites or exclusions.

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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