Compare commits

...

30 Commits
v4.1 ... v4.6

Author SHA1 Message Date
cexll
c96c07be2a update dev workflow 2025-11-25 22:26:56 +08:00
cexll
cee467fc0e update dev workflow 2025-11-25 21:31:31 +08:00
cexll
71305da77e fix codex skill eof 2025-11-25 21:00:12 +08:00
cexll
c4021cf58a update dev workflow plugin 2025-11-25 20:06:29 +08:00
cexll
9a18a03061 update readme 2025-11-24 21:52:24 +08:00
cexll
b5183c7711 update gemini skills 2025-11-22 14:56:31 +08:00
cexll
3fab18a6bb update dev workflow 2025-11-22 13:18:38 +08:00
cexll
12af992d8c fix codex skill timeout and add more log 2025-11-20 20:28:44 +08:00
cexll
bbd2f50c38 update codex skills model config 2025-11-19 23:57:52 +08:00
cexll
3f7652f992 Merge branch 'master' of github.com:cexll/myclaude 2025-11-19 23:06:43 +08:00
cexll
2cbe36b532 fix codex skill 2025-11-19 23:06:37 +08:00
cexll
fdb152872d Merge pull request #24 from cexll/swe-agent/23-1763544297
feat: 支持通过环境变量配置 skills 模型
2025-11-19 21:35:27 +08:00
swe-agent[bot]
916b970665 feat: 支持通过环境变量配置 skills 模型
- 新增 CODEX_MODEL 环境变量覆盖 codex 默认模型
- 新增 GEMINI_MODEL 环境变量覆盖 gemini 默认模型
- 更新文档说明环境变量用法
- 保持向后兼容,未设置环境变量时使用原默认值

修复 #23

Generated by swe-agent
2025-11-19 09:27:15 +00:00
cexll
10070a9bef update skills plugin 2025-11-19 16:14:33 +08:00
cexll
b18439f268 update gemini 2025-11-19 16:14:22 +08:00
cexll
4230479ff4 fix codex skills running 2025-11-19 14:54:45 +08:00
cexll
18c26a252a update doc 2025-11-18 21:12:52 +08:00
cexll
f6fc9a338f feat simple dev workflow 2025-11-17 22:14:48 +08:00
cexll
6223d59042 Add Gemini CLI integration skill
Implement gemini skill following codex pattern with Python wrapper supporting multiple execution modes (uv run, python3, direct), configurable models (gemini-2.5-pro/flash/1.5-pro), timeout control, and zero-dependency cross-platform compatibility.

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-16 00:04:33 +08:00
cexll
e6b229645a update codex skills 2025-11-15 23:14:35 +08:00
cexll
9dc3e8f43d Merge pull request #21 from Tshoiasc/master
Enhance codex.py to auto-detect long inputs and switch to stdin mode,…
2025-11-14 09:45:24 +08:00
cexll
e9faa0bc2d Merge branch 'master' into master 2025-11-14 09:45:04 +08:00
swe-agent[bot]
70caa8d7fc Change default model to gpt-5.1-codex
- Update SKILL.md documentation
- Update codex.py DEFAULT_MODEL constant

Generated by swe-agent
2025-11-14 01:40:23 +00:00
Tshoiasc
4f74d5afa1 Enhance codex.py to auto-detect long inputs and switch to stdin mode, improving handling of shell argument issues. Updated build_codex_args to support stdin and added relevant logging for task length warnings. 2025-11-14 09:33:34 +08:00
cexll
7f61437eea fix codex.py wsl run err 2025-11-13 15:41:54 +08:00
swe-agent[bot]
ed604f6db7 optimize codex skills 2025-11-11 18:10:11 +08:00
swe-agent[bot]
fb66b52b68 Merge branch 'master' of github.com:cexll/myclaude 2025-11-11 16:47:13 +08:00
swe-agent[bot]
05e32203ee optimize codex skills 2025-11-11 16:47:04 +08:00
cexll
1bf7dd9a83 Rename SKILLS.md to SKILL.md 2025-11-10 19:09:31 +08:00
swe-agent[bot]
19aa237d47 feat codex skills 2025-11-10 19:00:21 +08:00
11 changed files with 1250 additions and 4 deletions

View File

@@ -175,6 +175,90 @@
"skills": [
"./skills/SKILL.md"
]
},
{
"name": "codex-cli",
"source": "./skills/codex/",
"description": "Execute Codex CLI for code analysis, refactoring, and automated code changes with file references (@syntax) and structured output",
"version": "1.0.0",
"author": {
"name": "Claude Code Dev Workflows",
"url": "https://github.com/cexll/myclaude"
},
"homepage": "https://github.com/cexll/myclaude",
"repository": "https://github.com/cexll/myclaude",
"license": "MIT",
"keywords": [
"codex",
"code-analysis",
"refactoring",
"automation",
"gpt-5",
"ai-coding"
],
"category": "essentials",
"strict": false,
"skills": [
"./SKILL.md"
]
},
{
"name": "gemini-cli",
"source": "./skills/gemini/",
"description": "Execute Gemini CLI for AI-powered code analysis and generation with Google's latest Gemini models",
"version": "1.0.0",
"author": {
"name": "Claude Code Dev Workflows",
"url": "https://github.com/cexll/myclaude"
},
"homepage": "https://github.com/cexll/myclaude",
"repository": "https://github.com/cexll/myclaude",
"license": "MIT",
"keywords": [
"gemini",
"google-ai",
"code-analysis",
"code-generation",
"ai-reasoning"
],
"category": "essentials",
"strict": false,
"skills": [
"./SKILL.md"
]
},
{
"name": "dev-workflow",
"source": "./dev-workflow/",
"description": "Minimal lightweight development workflow with requirements clarification, parallel codex execution, and mandatory 90% test coverage",
"version": "1.0.0",
"author": {
"name": "Claude Code Dev Workflows",
"url": "https://github.com/cexll/myclaude"
},
"homepage": "https://github.com/cexll/myclaude",
"repository": "https://github.com/cexll/myclaude",
"license": "MIT",
"keywords": [
"dev",
"workflow",
"codex",
"testing",
"coverage",
"concurrent",
"lightweight"
],
"category": "workflows",
"strict": false,
"commands": [
"./commands/dev.md"
],
"agents": [
"./agents/dev-plan-generator.md"
],
"skills": [
"../skills/codex/SKILL.md"
]
}
]
}

3
.gitignore vendored
View File

@@ -1,4 +1,3 @@
CLAUDE.md
.claude/
.claude-trace

View File

@@ -2,7 +2,7 @@
[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)
[![Claude Code](https://img.shields.io/badge/Claude-Code-blue)](https://claude.ai/code)
[![Version](https://img.shields.io/badge/Version-3.2-green)](https://github.com/cexll/myclaude)
[![Version](https://img.shields.io/badge/Version-4.4-green)](https://github.com/cexll/myclaude)
[![Plugin Ready](https://img.shields.io/badge/Plugin-Ready-purple)](https://docs.claude.com/en/docs/claude-code/plugins)
> Enterprise-grade agile development automation with AI-powered multi-agent orchestration
@@ -44,6 +44,7 @@ make install
|--------|-------------|--------------|
| **[bmad-agile-workflow](docs/BMAD-WORKFLOW.md)** | Complete BMAD methodology with 6 specialized agents | `/bmad-pilot` |
| **[requirements-driven-workflow](docs/REQUIREMENTS-WORKFLOW.md)** | Streamlined requirements-to-code workflow | `/requirements-pilot` |
| **[dev-workflow](dev-workflow/README.md)** | Extreme lightweight end-to-end development workflow | `/dev` |
| **[development-essentials](docs/DEVELOPMENT-COMMANDS.md)** | Core development slash commands | `/code` `/debug` `/test` `/optimize` |
| **[advanced-ai-agents](docs/ADVANCED-AGENTS.md)** | GPT-5 deep reasoning integration | Agent: `gpt5` |
| **[requirements-clarity](docs/REQUIREMENTS-CLARITY.md)** | Automated requirements clarification with 100-point scoring | Auto-activated skill |

View File

@@ -2,7 +2,7 @@
[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)
[![Claude Code](https://img.shields.io/badge/Claude-Code-blue)](https://claude.ai/code)
[![Version](https://img.shields.io/badge/Version-3.2-green)](https://github.com/cexll/myclaude)
[![Version](https://img.shields.io/badge/Version-4.4-green)](https://github.com/cexll/myclaude)
[![Plugin Ready](https://img.shields.io/badge/Plugin-Ready-purple)](https://docs.claude.com/en/docs/claude-code/plugins)
> 企业级敏捷开发自动化与 AI 驱动的多智能体编排
@@ -44,6 +44,7 @@ make install
|------|------|---------|
| **[bmad-agile-workflow](docs/BMAD-WORKFLOW.md)** | 完整 BMAD 方法论包含6个专业智能体 | `/bmad-pilot` |
| **[requirements-driven-workflow](docs/REQUIREMENTS-WORKFLOW.md)** | 精简的需求到代码工作流 | `/requirements-pilot` |
| **[dev-workflow](dev-workflow/README.md)** | 极简端到端开发工作流 | `/dev` |
| **[development-essentials](docs/DEVELOPMENT-COMMANDS.md)** | 核心开发斜杠命令 | `/code` `/debug` `/test` `/optimize` |
| **[advanced-ai-agents](docs/ADVANCED-AGENTS.md)** | GPT-5 深度推理集成 | 智能体: `gpt5` |
| **[requirements-clarity](docs/REQUIREMENTS-CLARITY.md)** | 自动需求澄清100分制质量评分 | 自动激活技能 |

163
dev-workflow/README.md Normal file
View File

@@ -0,0 +1,163 @@
# /dev - Minimal Dev Workflow
## Overview
A freshly designed lightweight development workflow with no legacy baggage, focused on delivering high-quality code fast.
## Flow
```
/dev trigger
AskUserQuestion (requirements clarification)
Codex analysis (extract key points and tasks)
develop-doc-generator (create dev doc)
Codex concurrent development (25 tasks)
Codex testing & verification (≥90% coverage)
Done (generate summary)
```
## The 6 Steps
### 1. Clarify Requirements
- Use **AskUserQuestion** to ask the user directly
- No scoring system, no complex logic
- 23 rounds of Q&A until the requirement is clear
### 2. Codex Analysis
- Call codex to analyze the request
- Extract: core functions, technical points, task list (25 items)
- Output a structured analysis
### 3. Generate Dev Doc
- Call the **develop-doc-generator** agent
- Produce a single `dev-plan.md`
- Include: task breakdown, file scope, dependencies, test commands
### 4. Concurrent Development
- Work from the task list in dev-plan.md
- Independent tasks → run in parallel
- Conflicting tasks → run serially
### 5. Testing & Verification
- Each codex task:
- Implements the feature
- Writes tests
- Runs coverage
- Reports results (≥90%)
### 6. Complete
- Summarize task status
- Record coverage
## Usage
```bash
/dev "Implement user login with email + password"
```
**No options**, fixed workflow, works out of the box.
## Output Structure
```
.claude/specs/{feature_name}/
└── dev-plan.md # Dev document generated by agent
```
Only one file—minimal and clear.
## Core Components
### Tools
- **AskUserQuestion**: interactive requirement clarification
- **codex**: analysis, development, testing
- **develop-doc-generator**: generate dev doc (subagent, saves context)
## Key Features
### ✅ Fresh Design
- No legacy project residue
- No complex scoring logic
- No extra abstraction layers
### ✅ Minimal Orchestration
- Orchestrator controls the flow directly
- Only three tools/components
- Steps are straightforward
### ✅ Concurrency
- 25 tasks in parallel
- Auto-detect dependencies and conflicts
- Codex executes independently
### ✅ Quality Assurance
- Enforces 90% coverage
- Codex tests and verifies its own work
- Automatic retry on failure
## Example
```bash
# Trigger
/dev "Add user login feature"
# Step 1: Clarify requirements
Q: What login methods are supported?
A: Email + password
Q: Should login be remembered?
A: Yes, use JWT token
# Step 2: Codex analysis
Output:
- Core: email/password login + JWT auth
- Task 1: Backend API
- Task 2: Password hashing
- Task 3: Frontend form
# Step 3: Generate doc
dev-plan.md generated ✓
# Step 4-5: Concurrent development
[task-1] Backend API → tests → 92% ✓
[task-2] Password hashing → tests → 95% ✓
[task-3] Frontend form → tests → 91% ✓
```
## Directory Structure
```
dev-workflow/
├── README.md # This doc
├── commands/
│ └── dev.md # Workflow definition
└── agents/
└── develop-doc-generator.md # Doc generator
```
Minimal structure, only three files.
## When to Use
**Good for**:
- Any feature size
- Fast iterations
- High test coverage needs
- Wanting concurrent speed-up
## Design Principles
1. **KISS**: keep it simple
2. **Disposable**: no persistent config
3. **Quality first**: enforce 90% coverage
4. **Concurrency first**: leverage codex
5. **No legacy baggage**: clean-slate design
---
**Philosophy**: zero tolerance for complexity—ship the smallest usable solution, like Linus would.

View File

@@ -0,0 +1,114 @@
---
name: dev-plan-generator
description: Use this agent when you need to generate a structured development plan document (`dev-plan.md`) that breaks down a feature into concrete implementation tasks with testing requirements and acceptance criteria. This agent should be called after requirements analysis and before actual implementation begins.\n\n<example>\nContext: User is orchestrating a feature development workflow and needs to create a development plan after Codex analysis is complete.\nuser: "Create a development plan for the user authentication feature based on the requirements and analysis"\nassistant: "I'll use the Task tool to launch the dev-plan-generator agent to create the structured development plan document."\n<commentary>\nThe user needs a dev-plan.md document generated from requirements and analysis. Use the dev-plan-generator agent to create the structured task breakdown.\n</commentary>\n</example>\n\n<example>\nContext: Orchestrator has completed requirements gathering and Codex analysis for a new feature and needs to generate the development plan before moving to implementation.\nuser: "We've completed the analysis for the payment integration feature. Generate the development plan."\nassistant: "I'm going to use the Task tool to launch the dev-plan-generator agent to create the dev-plan.md document with task breakdown and testing requirements."\n<commentary>\nThis is the step in the workflow where the development plan document needs to be generated. Use the dev-plan-generator agent to create the structured plan.\n</commentary>\n</example>\n\n<example>\nContext: User is working through a requirements-driven workflow and has just approved the technical specifications.\nuser: "The specs look good. Let's move forward with creating the implementation plan."\nassistant: "I'll use the Task tool to launch the dev-plan-generator agent to generate the dev-plan.md document with the task breakdown."\n<commentary>\nAfter spec approval, the next step is generating the development plan. Use the dev-plan-generator agent to create the structured document.\n</commentary>\n</example>
tools: Glob, Grep, Read, Edit, Write, TodoWrite
model: sonnet
color: green
---
You are a specialized Development Plan Document Generator. Your sole responsibility is to create structured, actionable development plan documents (`dev-plan.md`) that break down features into concrete implementation tasks.
## Your Role
You receive context from an orchestrator including:
- Feature requirements description
- Codex analysis results (feature highlights, task decomposition)
- Feature name (in kebab-case format)
Your output is a single file: `./.claude/specs/{feature_name}/dev-plan.md`
## Document Structure You Must Follow
```markdown
# {Feature Name} - Development Plan
## Overview
[One-sentence description of core functionality]
## Task Breakdown
### Task 1: [Task Name]
- **ID**: task-1
- **Description**: [What needs to be done]
- **File Scope**: [Directories or files involved, e.g., src/auth/**, tests/auth/]
- **Dependencies**: [None or depends on task-x]
- **Test Command**: [e.g., pytest tests/auth --cov=src/auth --cov-report=term]
- **Test Focus**: [Scenarios to cover]
### Task 2: [Task Name]
...
(2-5 tasks)
## Acceptance Criteria
- [ ] Feature point 1
- [ ] Feature point 2
- [ ] All unit tests pass
- [ ] Code coverage ≥90%
## Technical Notes
- [Key technical decisions]
- [Constraints to be aware of]
```
## Generation Rules You Must Enforce
1. **Task Count**: Generate 2-5 tasks (no more, no less unless the feature is extremely simple or complex)
2. **Task Requirements**: Each task MUST include:
- Clear ID (task-1, task-2, etc.)
- Specific description of what needs to be done
- Explicit file scope (directories or files affected)
- Dependency declaration ("None" or "depends on task-x")
- Complete test command with coverage parameters
- Testing focus points (scenarios to cover)
3. **Task Independence**: Design tasks to be as independent as possible to enable parallel execution
4. **Test Commands**: Must include coverage parameters (e.g., `--cov=module --cov-report=term` for pytest, `--coverage` for npm)
5. **Coverage Threshold**: Always require ≥90% code coverage in acceptance criteria
## Your Workflow
1. **Analyze Input**: Review the requirements description and Codex analysis results
2. **Identify Tasks**: Break down the feature into 2-5 logical, independent tasks
3. **Determine Dependencies**: Map out which tasks depend on others (minimize dependencies)
4. **Specify Testing**: For each task, define the exact test command and coverage requirements
5. **Define Acceptance**: List concrete, measurable acceptance criteria including the 90% coverage requirement
6. **Document Technical Points**: Note key technical decisions and constraints
7. **Write File**: Use the Write tool to create `./.claude/specs/{feature_name}/dev-plan.md`
## Quality Checks Before Writing
- [ ] Task count is between 2-5
- [ ] Every task has all 6 required fields (ID, Description, File Scope, Dependencies, Test Command, Test Focus)
- [ ] Test commands include coverage parameters
- [ ] Dependencies are explicitly stated
- [ ] Acceptance criteria includes 90% coverage requirement
- [ ] File scope is specific (not vague like "all files")
- [ ] Testing focus is concrete (not generic like "test everything")
## Critical Constraints
- **Document Only**: You generate documentation. You do NOT execute code, run tests, or modify source files.
- **Single Output**: You produce exactly one file: `dev-plan.md` in the correct location
- **Path Accuracy**: The path must be `./.claude/specs/{feature_name}/dev-plan.md` where {feature_name} matches the input
- **Language Matching**: Output language matches user input (Chinese input → Chinese doc, English input → English doc)
- **Structured Format**: Follow the exact markdown structure provided
## Example Output Quality
Refer to the user login example in your instructions as the quality benchmark. Your outputs should have:
- Clear, actionable task descriptions
- Specific file paths (not generic)
- Realistic test commands for the actual tech stack
- Concrete testing scenarios (not abstract)
- Measurable acceptance criteria
- Relevant technical decisions
## Error Handling
If the input context is incomplete or unclear:
1. Request the missing information explicitly
2. Do NOT proceed with generating a low-quality document
3. Do NOT make up requirements or technical details
4. Ask for clarification on: feature scope, tech stack, testing framework, file structure
Remember: Your document will be used by other agents to implement the feature. Precision and completeness are critical. Every field must be filled with specific, actionable information.

View File

@@ -0,0 +1,101 @@
---
description: Extreme lightweight end-to-end development workflow with requirements clarification, parallel codex execution, and mandatory 90% test coverage
---
You are the /dev Workflow Orchestrator, an expert development workflow manager specializing in orchestrating minimal, efficient end-to-end development processes with parallel task execution and rigorous test coverage validation.
**Core Responsibilities**
- Orchestrate a streamlined 6-step development workflow:
1. Requirement clarification through targeted questioning
2. Technical analysis using Codex
3. Development documentation generation
4. Parallel development execution
5. Coverage validation (≥90% requirement)
6. Completion summary
**Workflow Execution**
- **Step 1: Requirement Clarification**
- Use AskUserQuestion to clarify requirements directly
- Focus questions on functional boundaries, inputs/outputs, constraints, testing
- Iterate 2-3 rounds until clear; rely on judgment; keep questions concise
- **Step 2: Codex Deep Analysis (Plan Mode Style)**
Use Codex Skill to perform deep analysis. Codex should operate in "plan mode" style:
**When Deep Analysis is Needed** (any condition triggers):
- Multiple valid approaches exist (e.g., Redis vs in-memory vs file-based caching)
- Significant architectural decisions required (e.g., WebSockets vs SSE vs polling)
- Large-scale changes touching many files or systems
- Unclear scope requiring exploration first
**What Codex Does in Analysis Mode**:
1. **Explore Codebase**: Use Glob, Grep, Read to understand structure, patterns, architecture
2. **Identify Existing Patterns**: Find how similar features are implemented, reuse conventions
3. **Evaluate Options**: When multiple approaches exist, list trade-offs (complexity, performance, security, maintainability)
4. **Make Architectural Decisions**: Choose patterns, APIs, data models with justification
5. **Design Task Breakdown**: Produce 2-5 parallelizable tasks with file scope and dependencies
**Analysis Output Structure**:
```
## Context & Constraints
[Tech stack, existing patterns, constraints discovered]
## Codebase Exploration
[Key files, modules, patterns found via Glob/Grep/Read]
## Implementation Options (if multiple approaches)
| Option | Pros | Cons | Recommendation |
## Technical Decisions
[API design, data models, architecture choices made]
## Task Breakdown
[2-5 tasks with: ID, description, file scope, dependencies, test command]
```
**Skip Deep Analysis When**:
- Simple, straightforward implementation with obvious approach
- Small changes confined to 1-2 files
- Clear requirements with single implementation path
- **Step 3: Generate Development Documentation**
- invoke agent dev-plan-generator
- **Step 4: Parallel Development Execution**
- For each task in `dev-plan.md`, invoke Codex with this brief:
```
Task: [task-id]
Reference: @.claude/specs/{feature_name}/dev-plan.md
Scope: [task file scope]
Test: [test command]
Deliverables: code + unit tests + coverage ≥90% + coverage summary
```
- Execute independent tasks concurrently; serialize conflicting ones; track coverage reports
- **Step 5: Coverage Validation**
- Validate each tasks coverage:
- All ≥90% → pass
- Any <90% → request more tests (max 2 rounds)
- **Step 6: Completion Summary**
- Provide completed task list, coverage per task, key file changes
**Error Handling**
- Codex failure: retry once, then log and continue
- Insufficient coverage: request more tests (max 2 rounds)
- Dependency conflicts: serialize automatically
**Quality Standards**
- Code coverage ≥90%
- 2-5 genuinely parallelizable tasks
- Documentation must be minimal yet actionable
- No verbose implementations; only essential code
**Communication Style**
- Be direct and concise
- Report progress at each workflow step
- Highlight blockers immediately
- Provide actionable next steps when coverage fails
- Prioritize speed via parallelization while enforcing coverage validation

191
skills/codex/SKILL.md Normal file
View File

@@ -0,0 +1,191 @@
---
name: codex
description: Execute Codex CLI for code analysis, refactoring, and automated code changes. Use when you need to delegate complex code tasks to Codex AI with file references (@syntax) and structured output.
---
# Codex CLI Integration
## Overview
Execute Codex CLI commands and parse structured JSON responses. Supports file references via `@` syntax, multiple models, and sandbox controls.
## When to Use
- Complex code analysis requiring deep understanding
- Large-scale refactoring across multiple files
- Automated code generation with safety controls
## Usage
**Mandatory**: Run every automated invocation through the Bash tool in the foreground with **HEREDOC syntax** to avoid shell quoting issues, keeping the `timeout` parameter fixed at `7200000` milliseconds (do not change it or use any other entry point).
```bash
uv run ~/.claude/skills/codex/scripts/codex.py - [working_dir] <<'EOF'
<task content here>
EOF
```
**Why HEREDOC?** Tasks often contain code blocks, nested quotes, shell metacharacters (`$`, `` ` ``, `\`), and multiline text. HEREDOC (Here Document) syntax passes these safely without shell interpretation, eliminating quote-escaping nightmares.
**Foreground only (no background/BashOutput)**: Never set `background: true`, never accept Claude's "Running in the background" mode, and avoid `BashOutput` streaming loops. Keep a single foreground Bash call per Codex task; if work might be long, split it into smaller foreground runs instead of offloading to background execution.
**Simple tasks** (backward compatibility):
For simple single-line tasks without special characters, you can still use direct quoting:
```bash
uv run ~/.claude/skills/codex/scripts/codex.py "simple task here" [working_dir]
```
**Resume a session with HEREDOC:**
```bash
uv run ~/.claude/skills/codex/scripts/codex.py resume <session_id> - [working_dir] <<'EOF'
<task content>
EOF
```
**Cross-platform notes:**
- **Bash/Zsh**: Use `<<'EOF'` (single quotes prevent variable expansion)
- **PowerShell 5.1+**: Use `@'` and `'@` (here-string syntax)
```powershell
uv run ~/.claude/skills/codex/scripts/codex.py - @'
task content
'@
```
## Environment Variables
- **CODEX_TIMEOUT**: Override timeout in milliseconds (default: 7200000 = 2 hours)
- Example: `export CODEX_TIMEOUT=3600000` for 1 hour
## Timeout Control
- **Built-in**: Script enforces 2-hour timeout by default
- **Override**: Set `CODEX_TIMEOUT` environment variable (in milliseconds, e.g., `CODEX_TIMEOUT=3600000` for 1 hour)
- **Behavior**: On timeout, sends SIGTERM, then SIGKILL after 5s if process doesn't exit
- **Exit code**: Returns 124 on timeout (consistent with GNU timeout)
- **Bash tool**: Always set `timeout: 7200000` parameter for double protection
### Parameters
- `task` (required): Task description, supports `@file` references
- `working_dir` (optional): Working directory (default: current)
### Return Format
Extracts `agent_message` from Codex JSON stream and appends session ID:
```
Agent response text here...
---
SESSION_ID: 019a7247-ac9d-71f3-89e2-a823dbd8fd14
```
Error format (stderr):
```
ERROR: Error message
```
Return only the final agent message and session ID—do not paste raw `BashOutput` logs or background-task chatter into the conversation.
### Invocation Pattern
All automated executions must use HEREDOC syntax through the Bash tool in the foreground, with `timeout` fixed at `7200000` (non-negotiable):
```
Bash tool parameters:
- command: uv run ~/.claude/skills/codex/scripts/codex.py - [working_dir] <<'EOF'
<task content>
EOF
- timeout: 7200000
- description: <brief description of the task>
```
Run every call in the foreground—never append `&` to background it—so logs and errors stay visible for timely interruption or diagnosis.
**Important:** Use HEREDOC (`<<'EOF'`) for all but the simplest tasks. This prevents shell interpretation of quotes, variables, and special characters.
### Examples
**Basic code analysis:**
```bash
# Recommended: via uv run with HEREDOC (handles any special characters)
uv run ~/.claude/skills/codex/scripts/codex.py - <<'EOF'
explain @src/main.ts
EOF
# timeout: 7200000
# Alternative: simple direct quoting (if task is simple)
uv run ~/.claude/skills/codex/scripts/codex.py "explain @src/main.ts"
```
**Refactoring with multiline instructions:**
```bash
uv run ~/.claude/skills/codex/scripts/codex.py - <<'EOF'
refactor @src/utils for performance:
- Extract duplicate code into helpers
- Use memoization for expensive calculations
- Add inline comments for non-obvious logic
EOF
# timeout: 7200000
```
**Multi-file analysis:**
```bash
uv run ~/.claude/skills/codex/scripts/codex.py - "/path/to/project" <<'EOF'
analyze @. and find security issues:
1. Check for SQL injection vulnerabilities
2. Identify XSS risks in templates
3. Review authentication/authorization logic
4. Flag hardcoded credentials or secrets
EOF
# timeout: 7200000
```
**Resume previous session:**
```bash
# First session
uv run ~/.claude/skills/codex/scripts/codex.py - <<'EOF'
add comments to @utils.js explaining the caching logic
EOF
# Output includes: SESSION_ID: 019a7247-ac9d-71f3-89e2-a823dbd8fd14
# Continue the conversation with more context
uv run ~/.claude/skills/codex/scripts/codex.py resume 019a7247-ac9d-71f3-89e2-a823dbd8fd14 - <<'EOF'
now add TypeScript type hints and handle edge cases where cache is null
EOF
# timeout: 7200000
```
**Task with code snippets and special characters:**
```bash
uv run ~/.claude/skills/codex/scripts/codex.py - <<'EOF'
Fix the bug in @app.js where the regex /\d+/ doesn't match "123"
The current code is:
const re = /\d+/;
if (re.test(input)) { ... }
Add proper escaping and handle $variables correctly.
EOF
```
### Large Task Protocol
- For every large task, first produce a canonical task list that enumerates the Task ID, description, file/directory scope, dependencies, test commands, and the expected Codex Bash invocation.
- Tasks without dependencies should be executed concurrently via multiple foreground Bash calls (you can keep separate terminal windows) and each run must log start/end times plus any shared resource usage.
- Reuse context aggressively (such as @spec.md or prior analysis output), and after concurrent execution finishes, reconcile against the task list to report which items completed and which slipped.
| ID | Description | Scope | Dependencies | Tests | Command |
| --- | --- | --- | --- | --- | --- |
| T1 | Review @spec.md to extract requirements | docs/, @spec.md | None | None | `uv run ~/.claude/skills/codex/scripts/codex.py - <<'EOF'`<br/>`analyze requirements @spec.md`<br/>`EOF` |
| T2 | Implement the module and add test cases | src/module | T1 | npm test -- --runInBand | `uv run ~/.claude/skills/codex/scripts/codex.py - <<'EOF'`<br/>`implement and test @src/module`<br/>`EOF` |
## Notes
- **Recommended**: Use `uv run` for automatic Python environment management (requires uv installed)
- **Alternative**: Direct execution `./codex.py` (uses system Python via shebang)
- Python implementation using standard library (zero dependencies)
- All automated runs must use the Bash tool with the fixed timeout to provide dual timeout protection and unified logging/exit semantics; any alternative approach is limited to manual foreground execution.
- Cross-platform compatible (Windows/macOS/Linux)
- PEP 723 compliant (inline script metadata)
- Runs with `--dangerously-bypass-approvals-and-sandbox` for automation (new sessions only)
- Uses `--skip-git-repo-check` to work in any directory
- Streams progress, returns only final agent message
- Every execution returns a session ID for resuming conversations
- Requires Codex CLI installed and authenticated

332
skills/codex/scripts/codex.py Executable file
View File

@@ -0,0 +1,332 @@
#!/usr/bin/env python3
# /// script
# requires-python = ">=3.8"
# dependencies = []
# ///
"""
Codex CLI wrapper with cross-platform support and session management.
**FIXED**: Auto-detect long inputs and use stdin mode to avoid shell argument issues.
Usage:
New session: uv run codex.py "task" [workdir]
Stdin mode: uv run codex.py - [workdir]
Resume: uv run codex.py resume <session_id> "task" [workdir]
Resume stdin: uv run codex.py resume <session_id> - [workdir]
Alternative: python3 codex.py "task"
Direct exec: ./codex.py "task"
Model configuration: Set CODEX_MODEL environment variable (default: gpt-5.1-codex)
"""
import subprocess
import json
import sys
import os
from typing import Optional
DEFAULT_MODEL = os.environ.get('CODEX_MODEL', 'gpt-5.1-codex')
DEFAULT_WORKDIR = '.'
DEFAULT_TIMEOUT = 7200 # 2 hours in seconds
FORCE_KILL_DELAY = 5
def log_error(message: str):
"""输出错误信息到 stderr"""
sys.stderr.write(f"ERROR: {message}\n")
def log_warn(message: str):
"""输出警告信息到 stderr"""
sys.stderr.write(f"WARN: {message}\n")
def log_info(message: str):
"""输出信息到 stderr"""
sys.stderr.write(f"INFO: {message}\n")
def resolve_timeout() -> int:
"""解析超时配置(秒)"""
raw = os.environ.get('CODEX_TIMEOUT', '')
if not raw:
return DEFAULT_TIMEOUT
try:
parsed = int(raw)
if parsed <= 0:
log_warn(f"Invalid CODEX_TIMEOUT '{raw}', falling back to {DEFAULT_TIMEOUT}s")
return DEFAULT_TIMEOUT
# 环境变量是毫秒,转换为秒
return parsed // 1000 if parsed > 10000 else parsed
except ValueError:
log_warn(f"Invalid CODEX_TIMEOUT '{raw}', falling back to {DEFAULT_TIMEOUT}s")
return DEFAULT_TIMEOUT
def normalize_text(text) -> Optional[str]:
"""规范化文本:字符串或字符串数组"""
if isinstance(text, str):
return text
if isinstance(text, list):
return ''.join(text)
return None
def parse_args():
"""解析命令行参数"""
if len(sys.argv) < 2:
log_error('Task required')
sys.exit(1)
# 检测是否为 resume 模式
if sys.argv[1] == 'resume':
if len(sys.argv) < 4:
log_error('Resume mode requires: resume <session_id> <task>')
sys.exit(1)
task_arg = sys.argv[3]
return {
'mode': 'resume',
'session_id': sys.argv[2],
'task': task_arg,
'explicit_stdin': task_arg == '-',
'workdir': sys.argv[4] if len(sys.argv) > 4 else DEFAULT_WORKDIR,
}
task_arg = sys.argv[1]
return {
'mode': 'new',
'task': task_arg,
'explicit_stdin': task_arg == '-',
'workdir': sys.argv[2] if len(sys.argv) > 2 else DEFAULT_WORKDIR,
}
def read_piped_task() -> Optional[str]:
"""
从 stdin 读取任务文本:
- 如果 stdin 是管道(非 tty且存在内容返回读取到的字符串
- 否则返回 None
"""
stdin = sys.stdin
if stdin is None or stdin.isatty():
log_info("Stdin is tty or None, skipping pipe read")
return None
log_info("Reading from stdin pipe...")
data = stdin.read()
if not data:
log_info("Stdin pipe returned empty data")
return None
log_info(f"Read {len(data)} bytes from stdin pipe")
return data
def should_stream_via_stdin(task_text: str, piped: bool) -> bool:
"""
判定是否通过 stdin 传递任务:
- 有管道输入
- 文本包含换行
- 文本包含反斜杠
- 文本长度 > 800
"""
if piped:
return True
if '\n' in task_text:
return True
if '\\' in task_text:
return True
if len(task_text) > 800:
return True
return False
def build_codex_args(params: dict, target_arg: str) -> list:
"""
构建 codex CLI 参数
Args:
params: 参数字典
target_arg: 最终传递给 codex 的参数('-' 或具体 task 文本)
"""
if params['mode'] == 'resume':
return [
'codex', 'e',
'-m', DEFAULT_MODEL,
'--skip-git-repo-check',
'--json',
'resume',
params['session_id'],
target_arg
]
else:
base_args = [
'codex', 'e',
'-m', DEFAULT_MODEL,
'--dangerously-bypass-approvals-and-sandbox',
'--skip-git-repo-check',
'-C', params['workdir'],
'--json',
target_arg
]
return base_args
def run_codex_process(codex_args, task_text: str, use_stdin: bool, timeout_sec: int):
"""
启动 codex 子进程,处理 stdin / JSON 行输出和错误,成功时返回 (last_agent_message, thread_id)。
失败路径上负责日志和退出码。
"""
thread_id: Optional[str] = None
last_agent_message: Optional[str] = None
process: Optional[subprocess.Popen] = None
try:
# 启动 codex 子进程(文本模式管道)
log_info(f"Starting codex with args: {' '.join(codex_args[:5])}...")
process = subprocess.Popen(
codex_args,
stdin=subprocess.PIPE if use_stdin else None,
stdout=subprocess.PIPE,
stderr=sys.stderr,
text=True,
bufsize=1,
)
log_info(f"Process started with PID: {process.pid}")
# 如果使用 stdin 模式,写入任务到 stdin 并关闭
if use_stdin and process.stdin is not None:
log_info(f"Writing {len(task_text)} chars to stdin...")
process.stdin.write(task_text)
process.stdin.flush() # 强制刷新缓冲区,避免大任务死锁
process.stdin.close()
log_info("Stdin closed")
# 逐行解析 JSON 输出
if process.stdout is None:
log_error('Codex stdout pipe not available')
sys.exit(1)
log_info("Reading stdout...")
for line in process.stdout:
line = line.strip()
if not line:
continue
try:
event = json.loads(line)
# 捕获 thread_id
if event.get('type') == 'thread.started':
thread_id = event.get('thread_id')
# 捕获 agent_message
if (event.get('type') == 'item.completed' and
event.get('item', {}).get('type') == 'agent_message'):
text = normalize_text(event['item'].get('text'))
if text:
last_agent_message = text
except json.JSONDecodeError:
log_warn(f"Failed to parse line: {line}")
# 等待进程结束并检查退出码
returncode = process.wait(timeout=timeout_sec)
if returncode != 0:
log_error(f'Codex exited with status {returncode}')
sys.exit(returncode)
if not last_agent_message:
log_error('Codex completed without agent_message output')
sys.exit(1)
return last_agent_message, thread_id
except subprocess.TimeoutExpired:
log_error('Codex execution timeout')
if process is not None:
process.kill()
try:
process.wait(timeout=FORCE_KILL_DELAY)
except subprocess.TimeoutExpired:
pass
sys.exit(124)
except FileNotFoundError:
log_error("codex command not found in PATH")
sys.exit(127)
except KeyboardInterrupt:
log_error("Codex interrupted by user")
if process is not None:
process.terminate()
try:
process.wait(timeout=FORCE_KILL_DELAY)
except subprocess.TimeoutExpired:
process.kill()
sys.exit(130)
def main():
log_info("Script started")
params = parse_args()
log_info(f"Parsed args: mode={params['mode']}, task_len={len(params['task'])}")
timeout_sec = resolve_timeout()
log_info(f"Timeout: {timeout_sec}s")
explicit_stdin = params.get('explicit_stdin', False)
if explicit_stdin:
log_info("Explicit stdin mode: reading task from stdin")
task_text = sys.stdin.read()
if not task_text:
log_error("Explicit stdin mode requires task input from stdin")
sys.exit(1)
piped = not sys.stdin.isatty()
else:
piped_task = read_piped_task()
piped = piped_task is not None
task_text = piped_task if piped else params['task']
use_stdin = explicit_stdin or should_stream_via_stdin(task_text, piped)
if use_stdin:
reasons = []
if piped:
reasons.append('piped input')
if explicit_stdin:
reasons.append('explicit "-"')
if '\n' in task_text:
reasons.append('newline')
if '\\' in task_text:
reasons.append('backslash')
if len(task_text) > 800:
reasons.append('length>800')
if reasons:
log_warn(f"Using stdin mode for task due to: {', '.join(reasons)}")
target_arg = '-' if use_stdin else params['task']
codex_args = build_codex_args(params, target_arg)
log_info('codex running...')
last_agent_message, thread_id = run_codex_process(
codex_args=codex_args,
task_text=task_text,
use_stdin=use_stdin,
timeout_sec=timeout_sec,
)
# 输出 agent_message
sys.stdout.write(f"{last_agent_message}\n")
# 输出 session_id如果存在
if thread_id:
sys.stdout.write(f"\n---\nSESSION_ID: {thread_id}\n")
sys.exit(0)
if __name__ == '__main__':
main()

120
skills/gemini/SKILL.md Normal file
View File

@@ -0,0 +1,120 @@
---
name: gemini
description: Execute Gemini CLI for AI-powered code analysis and generation. Use when you need to leverage Google's Gemini models for complex reasoning tasks.
---
# Gemini CLI Integration
## Overview
Execute Gemini CLI commands with support for multiple models and flexible prompt input. Integrates Google's Gemini AI models into Claude Code workflows.
## When to Use
- Complex reasoning tasks requiring advanced AI capabilities
- Code generation and analysis with Gemini models
- Tasks requiring Google's latest AI technology
- Alternative perspective on code problems
## Usage
**Mandatory**: Run via uv with fixed timeout 7200000ms (foreground):
```bash
uv run ~/.claude/skills/gemini/scripts/gemini.py "<prompt>" [working_dir]
```
**Optional** (direct execution or using Python):
```bash
~/.claude/skills/gemini/scripts/gemini.py "<prompt>" [working_dir]
# or
python3 ~/.claude/skills/gemini/scripts/gemini.py "<prompt>" [working_dir]
```
## Environment Variables
- **GEMINI_MODEL**: Configure model (default: `gemini-3-pro-preview`)
- Example: `export GEMINI_MODEL=gemini-3`
## Timeout Control
- **Fixed**: 7200000 milliseconds (2 hours), immutable
- **Bash tool**: Always set `timeout: 7200000` for double protection
### Parameters
- `prompt` (required): Task prompt or question
- `working_dir` (optional): Working directory (default: current directory)
### Return Format
Plain text output from Gemini:
```text
Model response text here...
```
Error format (stderr):
```text
ERROR: Error message
```
### Invocation Pattern
When calling via Bash tool, always include the timeout parameter:
```yaml
Bash tool parameters:
- command: uv run ~/.claude/skills/gemini/scripts/gemini.py "<prompt>"
- timeout: 7200000
- description: <brief description of the task>
```
Alternatives:
```yaml
# Direct execution (simplest)
- command: ~/.claude/skills/gemini/scripts/gemini.py "<prompt>"
# Using python3
- command: python3 ~/.claude/skills/gemini/scripts/gemini.py "<prompt>"
```
### Examples
**Basic query:**
```bash
uv run ~/.claude/skills/gemini/scripts/gemini.py "explain quantum computing"
# timeout: 7200000
```
**Code analysis:**
```bash
uv run ~/.claude/skills/gemini/scripts/gemini.py "review this code for security issues: $(cat app.py)"
# timeout: 7200000
```
**With specific working directory:**
```bash
uv run ~/.claude/skills/gemini/scripts/gemini.py "analyze project structure" "/path/to/project"
# timeout: 7200000
```
**Using python3 directly (alternative):**
```bash
python3 ~/.claude/skills/gemini/scripts/gemini.py "your prompt here"
```
## Notes
- **Recommended**: Use `uv run` for automatic Python environment management (requires uv installed)
- **Alternative**: Direct execution `./gemini.py` (uses system Python via shebang)
- Python implementation using standard library (zero dependencies)
- Cross-platform compatible (Windows/macOS/Linux)
- PEP 723 compliant (inline script metadata)
- Requires Gemini CLI installed and authenticated
- Supports all Gemini model variants (configure via `GEMINI_MODEL` environment variable)
- Output is streamed directly from Gemini CLI

140
skills/gemini/scripts/gemini.py Executable file
View File

@@ -0,0 +1,140 @@
#!/usr/bin/env python3
# /// script
# requires-python = ">=3.8"
# dependencies = []
# ///
"""
Gemini CLI wrapper with cross-platform support.
Usage:
uv run gemini.py "<prompt>" [workdir]
python3 gemini.py "<prompt>"
./gemini.py "your prompt"
"""
import subprocess
import sys
import os
DEFAULT_MODEL = os.environ.get('GEMINI_MODEL', 'gemini-3-pro-preview')
DEFAULT_WORKDIR = '.'
TIMEOUT_MS = 7_200_000 # 固定 2 小时,毫秒
DEFAULT_TIMEOUT = TIMEOUT_MS // 1000
FORCE_KILL_DELAY = 5
def log_error(message: str):
"""输出错误信息到 stderr"""
sys.stderr.write(f"ERROR: {message}\n")
def log_warn(message: str):
"""输出警告信息到 stderr"""
sys.stderr.write(f"WARN: {message}\n")
def log_info(message: str):
"""输出信息到 stderr"""
sys.stderr.write(f"INFO: {message}\n")
def parse_args():
"""解析位置参数"""
if len(sys.argv) < 2:
log_error('Prompt required')
sys.exit(1)
return {
'prompt': sys.argv[1],
'workdir': sys.argv[2] if len(sys.argv) > 2 else DEFAULT_WORKDIR
}
def build_gemini_args(args) -> list:
"""构建 gemini CLI 参数"""
return [
'gemini',
'-m', DEFAULT_MODEL,
'-p', args['prompt']
]
def main():
log_info('Script started')
args = parse_args()
log_info(f"Prompt length: {len(args['prompt'])}")
log_info(f"Working dir: {args['workdir']}")
gemini_args = build_gemini_args(args)
timeout_sec = DEFAULT_TIMEOUT
log_info(f"Timeout: {timeout_sec}s")
# 如果指定了工作目录,切换到该目录
if args['workdir'] != DEFAULT_WORKDIR:
try:
os.chdir(args['workdir'])
except FileNotFoundError:
log_error(f"Working directory not found: {args['workdir']}")
sys.exit(1)
except PermissionError:
log_error(f"Permission denied: {args['workdir']}")
sys.exit(1)
log_info('Changed working directory')
try:
log_info(f"Starting gemini with model {DEFAULT_MODEL}")
process = None
# 启动 gemini 子进程,直接透传 stdout 和 stderr
process = subprocess.Popen(
gemini_args,
stdout=subprocess.PIPE,
stderr=subprocess.PIPE,
text=True,
bufsize=1 # 行缓冲
)
# 实时输出 stdout
for line in process.stdout:
sys.stdout.write(line)
sys.stdout.flush()
# 等待进程结束
returncode = process.wait(timeout=timeout_sec)
# 读取 stderr
stderr_output = process.stderr.read()
if stderr_output:
sys.stderr.write(stderr_output)
# 检查退出码
if returncode != 0:
log_error(f'Gemini exited with status {returncode}')
sys.exit(returncode)
sys.exit(0)
except subprocess.TimeoutExpired:
log_error(f'Gemini execution timeout ({timeout_sec}s)')
if process is not None:
process.kill()
try:
process.wait(timeout=FORCE_KILL_DELAY)
except subprocess.TimeoutExpired:
pass
sys.exit(124)
except FileNotFoundError:
log_error("gemini command not found in PATH")
log_error("Please install Gemini CLI: https://github.com/google/generative-ai-python")
sys.exit(127)
except KeyboardInterrupt:
if process is not None:
process.terminate()
try:
process.wait(timeout=FORCE_KILL_DELAY)
except subprocess.TimeoutExpired:
process.kill()
sys.exit(130)
if __name__ == '__main__':
main()