motion workflow review

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

Annotations only declare this is a non-idempotent, non-destructive write; the description adds real behavioral context beyond that: failed/unknown verdicts keep the stage active, three attempts force a rethink, and AI reviews are advisory only. These consequences of recording a review are exactly the kind of disclosure annotations cannot carry.

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

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

Four short sentences, front-loaded with the core action, then stage consequences and guardrails. The user-feedback warning overlaps with the schema's reviewer description, a minor redundancy, but overall it is dense and efficient.

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

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

An output schema exists, so return values need no explanation, and the revision-staleness and ID semantics are covered in the schema. The description supplies the workflow-stage and evidence-quality context needed to call a complex nested write correctly; only the gap in sibling differentiation keeps it from full completeness.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 50%, and the description reinforces the schema's own reviewer guidance ('Do not claim user feedback unless the user actually supplied it') and adds the expectation that findings must be 'evidence-backed' and cover 'every requirement and exclusion,' mapping conceptually to the findings/exclusions arrays. It adds some meaning but does not document the undocumented half of parameters, so a mid-range score fits.

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

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

The description gives a specific verb+resource: 'Record evidence-backed findings for every requirement and exclusion,' which clearly identifies this as a review-recording tool. It does not explicitly name sibling tools such as motion_review_start or motion_review_feedback, so differentiation relies on the name and surrounding context rather than the description itself.

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

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

It implies usage context via the workflow-stage rules ('Fails or unknowns keep the stage active; three attempts require rethinking the approach'), which tells the agent what happens when verdicts are fail/unknown. However, it never states when to choose this tool over alternatives like motion_review_start or the review feedback tool, leaving routing to inference.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.