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salmansrabon

codex-mcp

by salmansrabon

codex_qualify

Validate candidate test cases and bug findings pre-publication via independent read-only repository inspection, returning a review delta with cited evidence to confirm or reject each claim.

Instructions

Independently qualify candidate test cases and/or bug findings before you write your final artifact.

Send the candidate result you are holding in memory — do not write it to a file first, and do not call this after the report is published. codex-mcp runs Codex as a separate reviewer that inspects the repository itself, derives its own expected coverage or verdict, and only then compares that against your candidate. It returns a review delta.

What comes back is a second opinion, not a ruling. Verify each objection against the cited evidence: apply the ones the evidence supports, reject the ones it does not and record why, investigate the rest. You own the final artifact; codex-mcp never writes it.

The reviewer is strictly read-only: it cannot edit files, commit, push, modify issues, or write to any database or external system.

Required: reviewType, project.root, and a matching candidate set. Everything else — task context, blast-radius, test-charter, connectors — is optional and never blocks a review.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
taskNo
optionsNo
projectYes
artifactsNo
candidateNo
reviewTypeYes
Behavior5/5

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

The description explicitly states the tool is read-only ('cannot edit files, commit, push, modify issues, or write to any database or external system'), describes what it returns ('review delta'), and explains the review process (inspects repository, derives expected coverage, compares). This fully discloses behavioral traits without needing annotations.

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 well-structured with clear paragraphs: purpose, usage instructions, process explanation, and side-effect transparency. It is informative without being verbose, each sentence adds value, and it avoids redundancy.

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 tool's complexity (multiple parameters, review types, and candidate structures), the description covers the essential aspects: what it does, how to use it, its read-only nature, and the expected outcome (review delta). It also guides post-review actions ('verify each objection'), making it complete for an agent to decide when and how to invoke it.

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

Parameters4/5

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

The description clarifies required vs optional parameters: 'Required: reviewType, project.root, and a matching candidate set' and 'Everything else is optional.' This adds meaningful context beyond the schema. However, the schema marks candidate as optional (default {}), while the description implies it is required, a minor inconsistency that slightly reduces clarity.

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?

The description clearly states the tool's purpose: independently qualify candidate test cases and/or bug findings. It uses specific verbs (qualify, inspect, compare) and identifies the resource (candidate test cases/bugs) and distinguishes itself from sibling tools (auth/capabilities) by focusing on review.

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

Usage Guidelines5/5

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

Provides explicit usage timing: 'before you write your final artifact' and 'do not call this after the report is published.' It also instructs to send the candidate in memory rather than writing to a file first, and clarifies that it is a second opinion, giving clear when-to-use guidance.

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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