Direct answer

An MCP tool specification should document one user job, when the model should and should not call it, permissions, bounded inputs, a compact output, failure behavior, risk and confirmation requirements, and a held-out evaluation set. Copy the worksheet below into design review.

Purpose and selection

Tool name: [namespace].[verb]_[object]

User job: The user is trying to…

Use when: Call this tool when…

Do not use when: Do not call it for…

Nearest competing tool: … The distinction is…

Write in task language. A model choosing among tools needs sharper boundaries than a developer browsing API docs.

Inputs and policy

Required inputs: type, range, example

Optional inputs: default and effect

Caller identity: user and workspace resolution

Permissions: exact scopes and object checks

Validation: size, format, allowlist, injection controls

Output and errors

Result: smallest fields needed next

Provenance: source ID, title, location, time

Budget: default/max result count and tokens

Pagination: cursor behavior

Empty result: explicit response and refinement

Safe errors: actionable without secrets

Use progressive disclosure. See the token guide.

Risk and evaluation

Read/write and side effect: …

Confirmation: required before…

Idempotency/rollback: …

Audit: actor, tool, target, outcome

Evaluation: 10 normal, 5 ambiguous, 5 adversarial prompts

Pass: selection, arguments, policy, usefulness

Annotations are hints, not enforcement. Read the full tool design guide for rationale.

Built for the next step

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Sources

  1. Anthropic: writing effective tools for agents — namespacing, response design and tool evaluations. Verified 13 Sep 2026
  2. MCP specification: tools — tool discovery, invocation and security considerations. Verified 13 Sep 2026
  3. MCP project: tool annotations — risk hints and their enforcement limits. Verified 13 Sep 2026