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social_thread_builder

Create structured Twitter/X threads from topics by organizing content into sequential posts with configurable length.

Instructions

Build a Twitter/X thread structure from a topic

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
topicYesMain topic
pointsNoNumber of thread tweets (3-10)

Implementation Reference

  • The tool 'social_thread_builder' is implemented here as an MCP tool definition within the 'registerSocialTools' function. It takes a topic and point count to generate a thread structure.
    server.tool("social_thread_builder", "Build a Twitter/X thread structure from a topic", {
      topic: z.string().describe("Main topic"),
      points: z.number().default(5).describe("Number of thread tweets (3-10)")
    }, async ({ topic, points }) => {
      const count = Math.min(Math.max(points, 3), 10);
      const structure = Array.from({ length: count }, (_, i) => {
        if (i === 0) return `1/ ${topic}\n\nMost people have no idea what's happening\n\nHere's a breakdown`;
        if (i === count - 1) return `${i + 1}/ Summary:\n\n- [key takeaway 1]\n- [key takeaway 2]\n- [key takeaway 3]\n\nFollow for more analysis like this`;
        return `${i + 1}/ [Point ${i}: specific data or insight about ${topic}]`;
      });
      return { content: [{ type: "text", text: `**Thread Structure (${count} tweets)**\n\n${structure.join("\n\n---\n\n")}` }] };
    });
Behavior2/5

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

With no annotations and no output schema provided, the description carries the full burden of behavioral disclosure but fails to clarify whether the tool actually posts to Twitter/X or merely generates content for manual posting. It also does not describe the return format, rate limits, or required authentication scope.

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

Conciseness4/5

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

The single sentence is front-loaded with the verb and contains no redundant words. However, extreme brevity comes at the cost of omitting critical behavioral context that would normally be expected given the lack of annotations and output schema.

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?

Despite low parameter complexity (2 simple params), the absence of annotations, output schema, and critical behavioral context (read vs. write operations) leaves significant gaps. For a social media tool, failing to clarify whether it publishes content or merely generates it is a material omission.

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?

Schema description coverage is 100% ('Main topic' and 'Number of thread tweets'), so the baseline score applies. The description neither repeats nor enhances the parameter documentation, but the schema is self-sufficient for understanding the 'topic' and 'points' parameters.

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

Purpose4/5

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

The description uses a specific verb ('Build') and identifies the resource ('Twitter/X thread structure'), clearly positioning it as a thread generation tool. It implicitly distinguishes from sibling 'social_generate_tweet' by specifying 'thread' versus a single tweet, though 'structure' remains slightly ambiguous regarding whether it produces full content or an outline.

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 like 'social_generate_tweet' (single tweets) or 'social_content_calendar' (scheduling). It omits prerequisites, content constraints, or workflow integration hints entirely.

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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