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RyanKramer

ShipPost MCP

by RyanKramer

draft_thread

Generate a draft tweet thread on any topic in your chosen style and length. Returns a reviewable draft without posting, so you can refine and publish each tweet individually.

Instructions

Draft a tweet thread about a topic in your voice using AI.

Returns DRAFTS — does not post. Review and use post_tweet() for each.

Requires a ShipPost API key (SHIPPOST_API_KEY). Get one at https://shippost.ai

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
styleNoWriting style — "informative", "engaging", "controversial", "storytelling"informative
topicYesWhat the thread should be about
lengthNoNumber of tweets in the thread (3-15, default 5)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

With no annotations provided, the description carries the transparency burden and does it well: it states it does not post, returns drafts for review, and requires a SHIPPOST_API_KEY. It could add minor details like rate limits or cost, but the key side effects and prerequisite are disclosed.

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 compact and front-loaded: first statement defines the action, second states safety/deliverable, third covers prerequisites. Every sentence earns a purpose with no filler.

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

Completeness5/5

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

Given the output schema is present and all three parameters are reliably documented, the description has enough context. It covers what the tool does, that it doesn't post, and the required API key setup, making it complete for a drafting tool.

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 schema already provides 100% coverage with meaningful descriptions for topic, style, and length. The description adds little beyond the schema, so it doesn't meaningfully deepen parameter understanding, though no gaps exist.

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?

Starts with a specific action and resource: 'Draft a tweet thread about a topic in your voice using AI.' It also clarifies the deliverable ('Returns DRAFTS — does not post'), which distinguishes it from posting tools like post_tweet and single-tweet sibling draft_tweet.

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?

Gives clear workflow guidance: use it to create drafts, not to publish, and explicitly directs the agent to 'use post_tweet() for each' after review. It doesn't explicitly contrast with draft_tweet or draft_reply, but the thread framing and post_tweet pointer make usage context reasonably clear.

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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