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itto-ki
by itto-ki

codex_review

Review code for a feature, component, or Git changes. Analyzes relevant implementation or modified files to provide contextual feedback and improvement suggestions.

Instructions

Review code for a feature, component, or Git changes. Codex analyzes the relevant implementation or modified files, providing contextual feedback and improvement suggestions

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
focusNoSpecific areas to focus on
modelNoAI model to use
targetYesWhat to review - feature/component (e.g., "user authentication"), or Git context (e.g., "git diff", "staged changes", "changes in feature-branch"). Codex will identify relevant files automatically
languagesNoProgramming languages involved (e.g., ["typescript", "python"])

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.2.1

TDQS

A3.8/5.0
Behavior4/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure, and it handles this well: it states that Codex analyzes relevant files automatically and produces contextual feedback and improvement suggestions. It does not mention potential side effects, permissions, or output format, but for a read-oriented code review tool the described behavior is largely sufficient.

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 with no filler. The primary action and target scope are front-loaded, and the behavioral outcome is stated in the second sentence. Every clause earns its place.

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

Completeness4/5

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

The description is sufficiently complete for a tool with four well-documented parameters and no output schema: it explains the input target types and the expected result of the review. It could be stronger with explicit guidance about when to prefer this tool over codex_explain or codex_consult, but the core invocation context is adequately covered.

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?

Schema description coverage is 100%, so the schema already documents all four parameters including target's examples and the automatic file-identification behavior. The top-level description adds no new parameter-level meaning beyond what is already in the schema, so it stays at the baseline score.

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 verb ('Review code') and the resource ('a feature, component, or Git changes'), making the tool's purpose immediately understandable. It does not explicitly differentiate from sibling tools codex_explain and codex_consult, but the review-specific language is distinct enough for a competent agent.

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 by listing valid targets: feature, component, or Git changes. However, it provides no explicit exclusions or comparison to alternatives such as codex_explain or codex_consult, leaving the agent to infer the boundary between these tools.

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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