mcp-review

Official

by apatureai

Overview Schema Source Related Servers Discussions Admin

TypeScript

Hybrid

Act on a review panel finding

design_review_panel_action

Read-onlyIdempotent

Returns grounded fix suggestions or re-verification refs from review interactions; read-only, never edits code.

Instructions

Route an interaction from the interactive review panel: return a grounded finding's fix for the coding agent to apply, or the refs to re-verify. This tool never edits code. An advisory finding returns human_only, never an automatic fix, and a review nothing judged returns unjudged with no fix at all. Reads only; consumes no review units.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`action`	Yes
`job_id`	Yes
`finding_id`	No

Output Schema

TableJSON Schema

Name	Required	Description
`error`	No	Typed tool error, returned with isError: true instead of the result envelope. The full code and next_action vocabularies are in schemas/review-error.schema.json.
`job_id`	No
`response`	No	The panel reducer's routed response: a grounded fix for the coding agent, a human_only referral, an unjudged refusal when nothing judged the review, or the recheck refs.
`review_id`	No
`provenance`	No	Where the review this action was routed from came from. A routed fix is a string the caller is expected to act on, so the payload says in-band whether anything judged the review that produced it. When model_backed is false, response.type is "unjudged" and no fix is returned.
`schema_version`	No

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.2Sep 8, 2026

TDQS

B3.1/5.0

Behavior4/5

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

The description aligns with the readOnlyHint and destructiveHint annotations by stating it never edits code and reads only. It also discloses specific edge-case behaviors for advisory findings and unjudged reviews, adding detail beyond the annotations.

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

Conciseness3/5

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

The description is somewhat repetitive, repeating the read-only idea in multiple phrases ('never edits code', 'Reads only', 'consumes no review units'). It is not excessively long but could be more streamlined.

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

Completeness3/5

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

The description explains return outcomes and read-only behavior, but it lacks details about parameter meaning, error cases, or output structure. Given an output schema exists, the description is adequate but not fully complete.

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

Parameters2/5

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

Schema coverage is 0%, and the description only indirectly references 'finding' without clearly defining job_id, action, or finding_id. The action enum values are not explained, leaving parameter semantics largely unspecified.

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 clearly states the tool routes an interaction from the review panel and returns either a fix or refs to re-verify. It also clarifies the read-only nature, distinguishing it from action-oriented tools.

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 gives some usage context ('interactive review panel') and mentions outcomes like advisory findings, but it does not explicitly state when to choose this tool over siblings such as design_review_get or design_recheck. No direct alternative guidance is provided.

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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