AgentSkillsCN

codex

向 OpenAI Codex 寻求第二意见——无论是代码审查、解释说明、方案评估、性能分析，还是各类通用问题。

SKILL.md
--- frontmatter
name: codex
description: Ask OpenAI Codex for a second opinion — code reviews, explanations, plan critiques, performance analysis, or general questions
argument-hint: "<task or question>"
allowed-tools: "Read, Glob, Grep, Bash, mcp__codex__codex_query, mcp__codex__codex_review_code, mcp__codex__codex_review_plan, mcp__codex__codex_explain_code, mcp__codex__codex_plan_perf, mcp__codex__codex_implement"

You are invoking Codex to get a second opinion. Route the user's request to the most appropriate Codex MCP tool.

Tool Selection

Pick the best tool based on the user's request:

Request TypeToolKey Parameters
Code review, diff reviewmcp__codex__codex_review_codetarget (diff range or file), focusAreas
Plan critiquemcp__codex__codex_review_planplan, codebasePath
Explain codemcp__codex__codex_explain_codetarget (file/function), depth
Performance analysismcp__codex__codex_plan_perftarget, metrics
Implement/fix (writes code)mcp__codex__codex_implementtask
General questionmcp__codex__codex_queryprompt

Instructions

  1. •Parse the user's argument to determine the task type
  2. •If the user references files, read them first for context
  3. •Call the most specific Codex tool — prefer specialized tools over codex_query
  4. •Always pass workingDirectory to every tool call
  5. •Synthesize the response: summarize key findings, highlight important points, give actionable recommendations
  6. •Only use codex_implement if the user explicitly asks Codex to make changes

Examples

  • •/codex review my recent changes → codex_review_code with target "HEAD~1..HEAD"
  • •/codex explain src/lib/exec.ts → codex_explain_code with target "src/lib/exec.ts"
  • •/codex is my approach to caching correct? → codex_query with the question
  • •/codex optimize the response parsing → codex_plan_perf with target
  • •/codex implement error handling for timeouts → codex_implement with task