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- merceralex397-collab/codex-claude-integration
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- 2026년 2월 1일 12:38
- 감지된 SKILL.md 언어
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설치 방법
기본적으로 소스를 먼저 확인하는 Prompt가 선택됩니다. 직접 명령으로 전환하거나 로컬 사본을 다운로드할 수도 있습니다.
소스 파일 검토
설치 여부를 결정하기 전에 SKILL.md와 SkillsMP에 표시된 보조 파일을 읽어 보세요.
메뉴
기본적으로 소스를 먼저 확인하는 Prompt가 선택됩니다. 직접 명령으로 전환하거나 로컬 사본을 다운로드할 수도 있습니다.
설치 여부를 결정하기 전에 SKILL.md와 SkillsMP에 표시된 보조 파일을 읽어 보세요.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
직접 명령은 검토 Prompt를 거치지 않습니다. 실행하기 전에 소스를 확인하세요.
npx skills add https://github.com/merceralex397-collab/codex-claude-integration --skill codex명령은 한 줄로 유지됩니다. 복사하기 전에 가로로 스크롤해 전체 내용을 확인하세요.
로컬 사본을 원하시나요? SkillsMP에서 현재 제공할 수 있는 파일을 다운로드하세요.
SOC 직업 분류 기준
SKILL.md 표시 중
| name | codex |
| description | Unified Codex command with auto-detection, intent routing, and quality gates |
| user-invocable | true |
| allowed-tools | ["mcp__codex__codex","mcp__codex__codex-reply","Bash","Read","Glob","Grep","Write","Task"] |
One command to rule them all. Auto-detects project context, routes by intent, iterates until green.
/codex <natural language task>
/codex implement a rate limiter for the API
/codex fix the auth bug and add tests
/codex review the payment module for security issues
/codex refactor UserService to use repository pattern
| Flag | Effect |
|---|---|
--no-iterate | Skip quality gates, just execute |
--gates=test,lint | Only run specified gates |
--model=<model> | Override model selection |
--reasoning=<level> | Override reasoning effort (low/medium/high/xhigh) |
--profile=<name> | Use specific profile (quick/standard/deep/review) |
--verbose | Show detailed output |
--quiet | Minimal output |
Load settings from ~/.claude/codex-settings.toml (if exists):
python scripts/settings_loader.py --json
This returns user's preferred defaults, gate configuration, and profile definitions. If no settings file exists, sensible defaults are used.
Run project detection (cached for session):
python scripts/project_dna.py --json
This returns framework, patterns, test commands, lint commands.
Run intent analysis on the user's prompt:
python scripts/task-analyzer.py "<user prompt>"
This returns JSON with:
intent.type: generate, debug, review, refactor, test, or chainintent.steps: ordered list of operations (for chain type)complexity: 1-5 scalecodex_params.profile: quick, standard, or deepcodex_params.model: gpt-5.1-codex-mini, gpt-5.2-codex, or gpt-5.1-codex-maxcodex_params.model_reasoning_effort: low, medium, high, or xhighBased on intent type, route to the appropriate subagent:
| Intent | Route To | Sandbox |
|---|---|---|
| generate, debug, refactor, test | codex-coder | workspace-write |
| review, analyze, audit | codex-reviewer | read-only |
| chain | Sequential execution | Depends on step |
For write operations (generate/debug/refactor/test): Use the Task tool to spawn a codex-coder agent:
Task tool with subagent_type: "codex-coder"
For read operations (review/analyze/audit): Use the Task tool to spawn a codex-reviewer agent:
Task tool with subagent_type: "codex-reviewer"
For direct execution (simple tasks or when agents unavailable): Continue with steps 5-7 below.
Combine DNA context with user's task:
PROJECT CONTEXT (auto-detected):
[DNA output here]
USER SETTINGS:
Model: [from settings or flag]
Reasoning: [from settings or flag]
TASK: [user's original prompt]
INSTRUCTIONS:
- Follow existing project patterns
- [Intent-specific instructions]
Start with the model based on complexity and user settings:
| Complexity | Profile | Model | Reasoning | Escalation |
|---|---|---|---|---|
| 1-2 | quick | gpt-5.1-codex-mini | low | -> standard |
| 3 | standard | gpt-5.2-codex | medium | -> deep |
| 4-5 | deep | gpt-5.1-codex-max | high/xhigh | (none) |
User settings override these defaults. Flag overrides take highest priority.
Call Codex:
Use mcp__codex__codex with:
- prompt: [enhanced prompt]
- cwd: "."
- model: [from settings/analysis]
- sandbox: [from intent - workspace-write or read-only]
- approval-policy: "never" (REQUIRED for MCP stdio)
If the response indicates struggle or failure, escalate to next model and retry.
For generate/debug/refactor/test intents, run quality gates based on user settings:
# Check which gates are enabled
python scripts/settings_loader.py --gates --json
# Run enabled gates
python scripts/quality_gates.py --gate test --command "<test command>" --json
python scripts/quality_gates.py --gate lint --command "<lint command>" --fix "<fix command>" --json
If a gate fails:
mcp__codex__codex-replyOn success:
Complete: [summary of changes]
- Files modified: [list]
- Tests: passing
- Lint: passing
On partial success:
Partially complete: [what was done]
- Remaining issue: [what's failing]
- Suggested fix: [recommendation]
For prompts like "fix X and add tests":
| Error | Response |
|---|---|
| DNA detection fails | Use defaults, warn user |
| Intent unclear | Ask clarifying question |
| Model unavailable | Fall back to available model |
| Gate max retries | Report blocker, suggest manual fix |
| Codex timeout | Offer retry with longer timeout |
| Settings load fails | Use built-in defaults, warn user |
| Command | Description |
|---|---|
/codex-config | View and modify settings |
/codex-coder <task> | Direct access to coding agent |
/codex-reviewer <target> | Direct access to review agent |
Old skills still work:
/codex-delegate X -> redirects to /codex implement X/codex-review X -> redirects to /codex review X