Imported from David-Li0406/meta-skill-evloving (skill-flow/data/skills-refined-agentskillos-36k/skillsmp/code-with-codex/SKILL.md). Install upstream with npx skills add David-Li0406/meta-skill-evloving --skill code-with-codex. Copyright stays with the author.

Code with Codex

Use memex-cli to leverage Codex for code generation with memory and resume support.

Mandatory Execution Protocol

⚠️ CRITICAL: Claude MUST complete ALL applicable steps below BEFORE invoking memex-cli. Skipping any step is a protocol violation.

Step 1: Complexity Assessment (ALL Levels)

Required for: L1-L5

Use decision tree to determine complexity level:

Start
  ├─ Single file, <100 lines? → L1
  ├─ Reusable functions, no external deps? → L2
  ├─ Production module with tests?
  │   ├─ Standard CRUD/API? → L3
  │   └─ Complex algorithm? → L4
  └─ Multi-module/microservice? → L5

Output: Determined level (L1-L5) with reasoning.

Step 2: Task Decomposition (L3+ MANDATORY)

Required for: L3, L4, L5

Claude MUST decompose the task into subtasks:

1. Identify all components/modules/files to be created
2. Split into independent subtasks (each <300 lines output)
3. Assign unique task IDs
4. Establish dependency relationships

Skip condition: Only if task is truly atomic (single file, single responsibility)

Step 3: Dependency Analysis (L2+ MANDATORY)

Required for: L2, L3, L4, L5

Claude MUST analyze dependencies:

1. File dependencies: Which files import/require others?
2. Task dependencies: Which tasks must complete before others?
3. Build DAG: Create directed acyclic graph of execution order

Output: Dependency graph showing parallel groups.

Step 4: Execution Plan Report (ALL Levels)

Required for: L1-L5

Claude MUST report to user before execution:

## 📋 Execution Plan Report

### Complexity Assessment
- **Level**: L[X] ([level name])
- **Model**: [selected model]
- **Reasoning**: [why this level]

### Task Decomposition (L3+)
| ID | Description | Est. Lines | Dependencies |
|----|-------------|------------|--------------|
| task-1 | [desc] | ~100 | - |
| task-2 | [desc] | ~150 | task-1 |

### Dependency Graph (L2+)

Phase 1 (Parallel): [task-1] [task-2] ↓ ↓ Phase 2 (Sequential): [task-3 depends on 1,2]

### Execution Summary
- **Total subtasks**: N
- **Parallel groups**: M
- **Estimated phases**: P

Step 5: Workdir Resolution (AUTO)

Required for: ALL tasks

Claude MUST resolve workdir to project root:

git rev-parse --show-toplevel

Rule: workdir = Git 项目根目录（绝对路径）

Output: Report resolved workdir in Execution Plan.

Pre-Execution Checklist

Before invoking memex-cli, Claude MUST confirm:

• ✅ Complexity level determined (L1-L5)
• ✅ Model selected based on level
• ✅ (L2+) Dependencies analyzed
• ✅ (L3+) Task decomposed into subtasks
• ✅ Workdir resolved (via git root)
• ✅ Execution plan reported to user

⛔ VIOLATION: Directly passing L3/L4/L5 task to Codex without decomposition is a protocol violation. Always decompose first.

Execution Strategy

Automated Capabilities

Dependency Analysis Guide (L2+)

System automatically analyzes dependencies between tasks/files and builds execution DAG.

How It Works

Input: Multiple related tasks
         ↓
┌─────────────────────────────┐
│ 1. Parse task descriptions  │
│ 2. Identify file references │
│ 3. Detect implicit deps     │
│ 4. Build dependency graph   │
└─────────────────────────────┘
         ↓
Output: Execution DAG with parallel groups

Dependency Detection Rules

L2 Example: Parallel Validators with Dependencies

memex-cli run --backend codex --stdin <<'EOF'
---TASK---
id: email-validator
backend: codex
model: gpt-5.1-codex-max
workdir: ./utils
---CONTENT---
编写邮箱验证函数 (validators/email.py)
---END---
---TASK---
id: phone-validator
backend: codex
model: gpt-5.1-codex-max
workdir: ./utils
---CONTENT---
编写手机号验证函数 (validators/phone.py)
---END---
---TASK---
id: validator-index
backend: codex
model: gpt-5.1-codex-max
workdir: ./utils
dependencies: email-validator, phone-validator
---CONTENT---
创建 validators/__init__.py，导出所有验证函数
---END---
EOF

Execution Flow:

┌─────────────────┐  ┌─────────────────┐
│ email-validator │  │ phone-validator │  ← Parallel (no deps)
└────────┬────────┘  └────────┬────────┘
         │                    │
         └──────────┬─────────┘
                    ↓
         ┌─────────────────┐
         │ validator-index │  ← Sequential (depends on both)
         └─────────────────┘

Task Decomposition Guide (L3+)

System automatically decomposes large tasks into manageable subtasks.

How It Works

Input: Complex task description
         ↓
┌─────────────────────────────┐
│ 1. Analyze task scope       │
│ 2. Identify components      │
│ 3. Generate subtask list    │
│ 4. Establish dependencies   │
│ 5. Assign to parallel groups│
└─────────────────────────────┘
         ↓
Output: DAG of subtasks

Decomposition Triggers

L3 Example: HTTP Client with Auto-Decomposition

Input Task:

memex-cli run --backend codex --stdin <<'EOF'
---TASK---
id: http-client-module
backend: codex
model: gpt-5.2-codex
workdir: ./lib
timeout: 5400
---CONTENT---
创建完整的 HTTP 客户端模块：
1. 核心客户端类 (http_client.py)
2. 重试策略 (retry.py)
3. 拦截器系统 (interceptors.py)
4. 单元测试 (test_http_client.py)
---END---
EOF

Auto-Decomposed Execution:

Phase 1 (Parallel - No deps):
┌──────────────┐  ┌──────────────┐  ┌──────────────────┐
│ http_client  │  │    retry     │  │   interceptors   │
│    .py       │  │    .py       │  │       .py        │
└──────┬───────┘  └──────┬───────┘  └────────┬─────────┘
       │                 │                   │
       └─────────────────┼───────────────────┘
                         ↓
Phase 2 (Sequential - Depends on all above):
              ┌─────────────────────┐
              │ test_http_client.py │
              └─────────────────────┘

L4/L5 Example: Microservice with Full Decomposition

Input Task:

memex-cli run --backend codex --stdin <<'EOF'
---TASK---
id: auth-service
backend: codex
model: gpt-5.2
workdir: ./services/auth
timeout: 9000
---CONTENT---
设计用户认证微服务：
- 数据模型 (models/)
- 业务逻辑 (services/)
- API 端点 (api/)
- 数据库迁移 (migrations/)
- 完整测试套件 (tests/)
---END---
EOF

Auto-Decomposed Execution:

Phase 1: Foundation (Parallel)
┌──────────┐  ┌──────────┐
│ models/  │  │ schemas/ │
│ user.py  │  │ auth.py  │
└────┬─────┘  └────┬─────┘
     │             │
     └──────┬──────┘
            ↓
Phase 2: Business Logic (Parallel, depends on Phase 1)
┌─────────────┐  ┌─────────────┐  ┌─────────────┐
│ services/   │  │ services/   │  │ services/   │
│ auth.py     │  │ token.py    │  │ password.py │
└──────┬──────┘  └──────┬──────┘  └──────┬──────┘
       │                │                │
       └────────────────┼────────────────┘
                        ↓
Phase 3: API Layer (Sequential, depends on Phase 2)
┌─────────────────────────────────┐
│ api/routes.py, api/middleware.py│
└────────────────┬────────────────┘
                 ↓
Phase 4: Database & Tests (Parallel, depends on Phase 3)
┌─────────────┐  ┌─────────────┐
│ migrations/ │  │   tests/    │
└─────────────┘  └─────────────┘

Model Selection Guide

Auto selection rules:

• Model is automatically selected based on task complexity level
• Manual override available via model field when needed
• System optimizes for cost-efficiency while maintaining quality

Complexity Levels Overview

Level 1: Simple Scripts (⭐)

Quick utilities, single-file scripts (20-100 lines). Use gpt-5.1-codex-mini.

Examples: Batch file rename, CSV processing, disk monitoring

Quick example:

memex-cli run --backend codex --stdin <<'EOF'
---TASK---
id: batch-rename
backend: codex
model: gpt-5.1-codex-mini
workdir: /path/to/scripts
---CONTENT---
Python脚本：批量重命名文件，添加日期前缀
---END---
EOF

➜ Detailed examples: examples/level1-simple-scripts.md

Level 2: Utility Functions (⭐⭐)

Reusable functions, data transformations (100-300 lines). Use gpt-5.1-codex-max.

Examples: Data validators, format converters, simple unit tests

Quick example:

memex-cli run --backend codex --stdin <<'EOF'
---TASK---
id: validators
backend: codex
model: gpt-5.1-codex-max
workdir: /path/to/utils
---CONTENT---
编写邮箱、手机号、身份证号验证函数
---END---
EOF

➜ Detailed examples: examples/level2-utilities.md

Level 3: Complete Modules (⭐⭐⭐)

Production-ready modules with error handling, logging, tests (300-800 lines). Use gpt-5.2-codex.

Examples: HTTP clients, database helpers, API wrappers

Special tasks at Level 3:

• Code Review: Analyze code for security/performance issues
• Refactoring: Apply design patterns, improve testability
• Unit Testing: Comprehensive test coverage (>80%)

Quick example:

memex-cli run --backend codex --stdin <<'EOF'
---TASK---
id: http-client
backend: codex
model: gpt-5.2-codex
workdir: /path/to/lib
timeout: 5400
---CONTENT---
Python HTTP客户端：支持重试、超时、拦截器
---END---
EOF

Code review example:

memex-cli run --backend codex --stdin <<'EOF'
---TASK---
id: review
backend: codex
model: gpt-5.2-codex
files: ./src/auth.py
files-mode: ref
workdir: /path/to/project
---CONTENT---
审查代码：安全隐患、性能瓶颈、改进建议
---END---
EOF

➜ Detailed examples: examples/level3-modules.md

Level 4: Complex Algorithms (⭐⭐⭐⭐)

Advanced data structures, optimized algorithms (500-1500 lines). Use gpt-5.2 with extended timeout.

Examples: Skip lists, pathfinding (Dijkstra, A*), expression parsers

Quick example:

memex-cli run --backend codex --stdin <<'EOF'
---TASK---
id: skiplist
backend: codex
model: gpt-5.2
workdir: /path/to/algorithms
timeout: 7200
---CONTENT---
实现跳表：支持插入、删除、搜索，O(log n)复杂度
---END---
EOF

➜ Detailed examples: examples/level4-algorithms.md

Level 5: System Design & Architecture (⭐⭐⭐⭐⭐)

Multi-module projects, microservices, complete applications (2000+ lines). Use gpt-5.2 with 300-600s timeout.

Examples: Authentication microservices, event-driven systems, full-stack apps

Quick example:

memex-cli run --backend codex --stdin <<'EOF'
---TASK---
id: auth-service
backend: codex
model: gpt-5.2
workdir: /path/to/services/auth
timeout: 9000
---CONTENT---
设计用户认证微服务：JWT、OAuth2、RBAC权限模型
---END---
EOF

➜ Detailed examples: examples/level5-architecture.md

Basic Usage

Single Task

memex-cli run --backend codex --stdin <<'EOF'
---TASK---
id: task-id
backend: codex
workdir: /working/directory
model: gpt-5.2-codex
---CONTENT---
[Your task description]
---END---
EOF

Required Fields

Optional Fields

Quick Reference

Complexity Decision Tree

Start
  ├─ Single file, <100 lines? → Level 1 (codex-mini)
  ├─ Reusable functions, no external deps? → Level 2 (codex)
  ├─ Production module with tests?
  │   ├─ Standard CRUD/API? → Level 3 (codex-max)
  │   └─ Complex algorithm? → Level 4 (gpt-5.2)
  └─ Multi-module/microservice? → Level 5 (gpt-5.2)

Task Type Classification

Additional Resources

Progressive Disclosure Documentation

• HOW_TO_USE.md - Complete usage guide

  • When to use this skill
  • Relationship with memex-cli
  • Model selection tips
  • Workflow references

• references/complexity-guide.md - Detailed complexity selection

  • In-depth explanation of 5 levels
  • Model performance comparison
  • Decision tree and classification
  • Best practices by task type

• examples/ - Runnable code examples

  • level1-simple-scripts.md - Quick utilities
  • level2-utilities.md - Reusable functions
  • level3-modules.md - Production modules, code review, refactoring
  • level4-algorithms.md - Complex algorithms
  • level5-architecture.md - System design

Advanced Workflows

For multi-task workflows, parallel execution, and resume functionality, refer to memex-cli skill:

• Multi-task DAG workflows: memex-cli/references/advanced-usage.md
• Parallel execution patterns: memex-cli/examples/parallel-tasks.md
• Resume interrupted runs: memex-cli/examples/resume-workflow.md

Tips

1. Match model to task complexity

   • Start with lightweight models for simple tasks
   • Upgrade to powerful models only when needed
   • Save costs by not over-provisioning

2. Use files for context

   • Code review: files: ./src/auth.py (files-mode defaults to ref)
   • Refactoring: Reference source files for analysis
   • Unit testing: Reference module to test

3. Break down large tasks

   • Split Level 5 projects into parallel Level 3-4 subtasks
   • Use DAG workflows for dependencies
   • See memex-cli advanced usage

4. Include context in prompts

   • Specify language, framework, coding standards
   • Mention target Python/Node.js version
   • Include expected output format

5. Leverage examples

   • Browse examples/ directory for similar tasks
   • Copy and customize example commands
   • Follow established patterns

SKILL Reference

• skills/memex-cli/SKILL.md - Memex CLI full documentation
• HOW_TO_USE.md - Detailed usage guide for this skill