Claude-skill-registry code-with-codex
Write and generate code using memex-cli with Codex backend. Use when (1) Generating code files and scripts, (2) Refactoring existing code, (3) Writing tests, (4) Creating project scaffolds, (5) Implementing algorithms or features, (6) Code review and optimization, (7) Complex multi-file projects.
git clone https://github.com/majiayu000/claude-skill-registry
T=$(mktemp -d) && git clone --depth=1 https://github.com/majiayu000/claude-skill-registry "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/data/code-with-codex" ~/.claude/skills/majiayu000-claude-skill-registry-code-with-codex && rm -rf "$T"
skills/data/code-with-codex/SKILL.mdCode 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:
- Identify all components/modules/files to be created
- Split into independent subtasks (each <300 lines output)
- Assign unique task IDs
- 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:
- File dependencies: Which files import/require others?
- Task dependencies: Which tasks must complete before others?
- 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
| Level | Model | files-mode | Dependency Analysis | Task Decomposition | Execution |
|---|---|---|---|---|---|
| L1 | | ref | ❌ | ❌ | Serial |
| L2 | | ref | ✅ | ❌ | Parallel |
| L3 | | ref | ✅ | ✅ | Parallel |
| L4 | | ref | ✅ | ✅ | Parallel |
| L5 | | ref | ✅ | ✅ | Parallel |
Automated Capabilities
| Capability | Description | Active Level |
|---|---|---|
| Auto Model Selection | Automatically select optimal model based on complexity | L1-L5 |
| Auto Grading | Evaluate task complexity via Decision Tree | L1-L5 |
| Dependency Analysis | Analyze task/file dependencies, build DAG | L2+ |
| Task Decomposition | Auto-split large tasks into subtasks | L3+ |
| Parallel Execution | Execute independent subtasks in parallel | L2+ |
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
| Type | Detection Method | Example |
|---|---|---|
| Explicit | field | |
| File-based | Output→Input file match | Task A outputs → Task B imports it |
| Import-based | Module import analysis | → depends on utils |
| Sequential | Keyword detection | "based on", "after", "using result of" |
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
| Trigger | Detection | Action |
|---|---|---|
| Multi-file | "create X files", file list | Split by file |
| Multi-component | "module with A, B, C" | Split by component |
| Layered | "model, service, controller" | Split by layer |
| Test + Impl | "implement and test" | Split impl → test |
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
| Model | Best For | Complexity |
|---|---|---|
| gpt-5.1-codex-mini | Simple scripts, quick fixes | ⭐ |
| gpt-5.1-codex-max | Utilities, production modules | ⭐⭐-⭐⭐⭐ |
| gpt-5.2-codex | Code review, refactoring, testing | ⭐⭐⭐ |
| gpt-5.2 | Complex algorithms, architecture | ⭐⭐⭐⭐-⭐⭐⭐⭐⭐ |
Auto selection rules:
- Model is automatically selected based on task complexity level
- Manual override available via
field when neededmodel - 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
| Field | Description | Example |
|---|---|---|
| Unique task identifier | , |
| Always for code generation | |
| Working directory path | , |
Optional Fields
| Field | Default | Description |
|---|---|---|
| gpt-5.2-codex | Model selection (see complexity guide) |
| 1800 | Max execution time (seconds, 30min base, +30min per level) |
| - | Comma-separated task IDs |
| - | Source files to reference |
| ref | (path only) - unified across all levels |
| 0 | Retry count on failure |
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
| Task Type | Level | Model | Example Link |
|---|---|---|---|
| Batch rename script | 1 | codex-mini | Level 1 |
| Email validator | 2 | codex-max | Level 2 |
| HTTP client with retry | 3 | gpt-5.2-codex | Level 3 |
| Code review | 3 | gpt-5.2-codex | Level 3 |
| Refactoring | 3-4 | gpt-5.2-codex / gpt-5.2 | Level 3 |
| Unit testing | 2-3 | codex-max / gpt-5.2-codex | Level 3 |
| Skip list algorithm | 4 | gpt-5.2 | Level 4 |
| Auth microservice | 5 | gpt-5.2 | Level 5 |
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
-
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
-
Use files for context
- Code review:
(files-mode defaults tofiles: ./src/auth.py
)ref - Refactoring: Reference source files for analysis
- Unit testing: Reference module to test
- Code review:
-
Break down large tasks
- Split Level 5 projects into parallel Level 3-4 subtasks
- Use DAG workflows for dependencies
- See memex-cli advanced usage
-
Include context in prompts
- Specify language, framework, coding standards
- Mention target Python/Node.js version
- Include expected output format
-
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