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review_changes

Run OpenAI Codex to review code changes in git repos or directories. Select unstaged, staged, or last-commit changes to receive AI-generated feedback.

Instructions

Review code using OpenAI Codex. Works with git repos (reviews diff) or plain directories (reviews all source files).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cwdNoPath to the directory or git repository (defaults to server working directory)
typeNoWhich changes to review: unstaged working-tree changes, staged (cached) changes, or the last commit. Only used for git repos.
modelNoOverride the Codex model (e.g. "o3", "gpt-4.1")
instructionsNoAdditional review focus or instructions to append to the review prompt
Behavior2/5

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

With no annotations, the description bears the full burden of disclosing behavioral traits. It reveals that the tool uses an external AI service (OpenAI Codex) but does not mention important traits like non-destructiveness, network/cost implications, privacy considerations, or what the output looks like. The two-mode behavior is useful but insufficient.

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 two concise sentences that front-load the core purpose and quickly explain the two operational modes. Every sentence adds value, with no unnecessary words or repetition.

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 the core functionality and two usage modes, and the schema covers all parameters. However, with no output schema and no annotations, the description is incomplete regarding what the tool returns, potential side effects, and external service implications. It is adequate but leaves clear gaps.

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

Parameters3/5

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

The input schema provides 100% coverage with clear descriptions for all four parameters, so the baseline is 3. The description reinforces the diff vs. all-files distinction relevant to the 'type' parameter but does not add additional semantic meaning beyond what the schema already states.

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 reviews code using OpenAI Codex and distinguishes it from retrieval-only sibling tools by specifying it works on git diffs or all files in plain directories. The verb 'review' plus the two operation modes give a precise, specific purpose.

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

Usage Guidelines3/5

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

The description implies when to use the tool (for code review) and explains the two modes (git repos vs. plain directories), but it does not explicitly contrast it with get_diff or get_changed_files, nor does it state when not to use it. This is useful contextual guidance but lacks explicit alternatives or exclusions.

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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