codeagent

cexll/myclaude · updated Apr 8, 2026

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$npx skills add https://github.com/cexll/myclaude --skill codeagent
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summary

Execute codeagent-wrapper commands with pluggable AI backends (Codex, Claude, Gemini). Supports file references via @ syntax, parallel task execution with backend selection, and configurable security controls.

skill.md

Codeagent Wrapper Integration

Overview

Execute codeagent-wrapper commands with pluggable AI backends (Codex, Claude, Gemini). Supports file references via @ syntax, parallel task execution with backend selection, and configurable security controls.

When to Use

  • Complex code analysis requiring deep understanding
  • Large-scale refactoring across multiple files
  • Automated code generation with backend selection

Usage

HEREDOC syntax (recommended):

codeagent-wrapper --backend codex - [working_dir] <<'EOF'
<task content here>
EOF

With backend selection:

codeagent-wrapper --backend claude - . <<'EOF'
<task content here>
EOF

Simple tasks:

codeagent-wrapper --backend codex "simple task" [working_dir]
codeagent-wrapper --backend gemini "simple task" [working_dir]

Backends

Backend Command Description Best For
codex --backend codex OpenAI Codex (default) Code analysis, complex development
claude --backend claude Anthropic Claude Simple tasks, documentation, prompts
gemini --backend gemini Google Gemini UI/UX prototyping

Backend Selection Guide

Codex (default):

  • Deep code understanding and complex logic implementation
  • Large-scale refactoring with precise dependency tracking
  • Algorithm optimization and performance tuning
  • Example: "Analyze the call graph of @src/core and refactor the module dependency structure"

Claude:

  • Quick feature implementation with clear requirements
  • Technical documentation, API specs, README generation
  • Professional prompt engineering (e.g., product requirements, design specs)
  • Example: "Generate a comprehensive README for @package.json with installation, usage, and API docs"

Gemini:

  • UI component scaffolding and layout prototyping
  • Design system implementation with style consistency
  • Interactive element generation with accessibility support
  • Example: "Create a responsive dashboard layout with sidebar navigation and data visualization cards"

Backend Switching:

  • Start with Codex for analysis, switch to Claude for documentation, then Gemini for UI implementation
  • Use per-task backend selection in parallel mode to optimize for each task's strengths

Parameters

  • task (required): Task description, supports @file references
  • working_dir (optional): Working directory (default: current)
  • --backend (required): Select AI backend (codex/claude/gemini)
    • Note: Claude backend only adds --dangerously-skip-permissions when explicitly enabled

Return Format

Agent response text here...

---
SESSION_ID: 019a7247-ac9d-71f3-89e2-a823dbd8fd14

Resume Session

# Resume with codex backend
codeagent-wrapper --backend codex resume <session_id> - <<'EOF'
<follow-up task>
EOF

# Resume with specific backend
codeagent-wrapper --backend claude resume <session_id> - <<'EOF'
<follow-up task>
EOF

Parallel Execution

Default (summary mode - context-efficient):

codeagent-wrapper --parallel <<'EOF'
---TASK---
id: task1
backend: codex
workdir: /path/to/dir
---CONTENT---
task content
---TASK---
id: task2
dependencies: task1
---CONTENT---
dependent task
EOF

Full output mode (for debugging):

codeagent-wrapper --parallel --full-output <<'EOF'
...
EOF

Output Modes:

  • Summary (default): Structured report with changes, output, verification, and review summary.
  • Full (--full-output): Complete task messages. Use only when debugging specific failures.

With per-task backend:

codeagent-wrapper --parallel <<'EOF'
---TASK---
id: task1
backend: codex
workdir: /path/to/dir
---CONTENT---
analyze code structure
---TASK---
id: task2
backend: claude
dependencies: task1
---CONTENT---
design architecture based on analysis
---TASK---
id: task3
backend: gemini
dependencies: task2
---CONTENT---
generate implementation code
EOF

Concurrency Control: Set CODEAGENT_MAX_PARALLEL_WORKERS to limit concurrent tasks (default: unlimited).

Environment Variables

  • CODEX_TIMEOUT: Override timeout in milliseconds (default: 7200000 = 2 hours)
  • CODEAGENT_SKIP_PERMISSIONS: Control Claude CLI permission checks
    • For Claude backend: Set to true/1 to add --dangerously-skip-permissions (default: disabled)
    • For Codex/Gemini backends: Currently has no effect
  • CODEAGENT_MAX_PARALLEL_WORKERS: Limit concurrent tasks in parallel mode (default: unlimited, recommended: 8)

Invocation Pattern

Single Task:

Bash tool parameters:
- command: codeagent-wrapper --backend <backend> - [working_dir] <<'EOF'
  <task content>
  EOF
- timeout: 7200000
- description: <brief description>

Note: --backend is required (codex/claude/gemini)

Parallel Tasks:

Bash tool parameters:
- command: codeagent-wrapper --parallel --backend <backend> <<'EOF'
  ---TASK---
  id: task_id
  backend: <backend>  # Optional, overrides global
  workdir: /path
  dependencies: dep1, dep2
  ---CONTENT---
  task content
  EOF
- timeout: 7200000
- description: <brief description>

Note: Global --backend is required; per-task backend is optional

Critical Rules

NEVER kill codeagent processes. Long-running tasks are normal. Instead:

  1. Check task status via log file:

    # View real-time output
    tail -f /tmp/claude/<workdir>/tasks/<task_id>.output
    
    # Check if task is still running
    cat /tmp/claude/<workdir>/tasks/<task_id>.output | tail -50
    
  2. Wait with timeout:

    # Use TaskOutput tool with block=true and timeout
    TaskOutput(task_id="<id>", block=true, timeout=300000)
    
  3. Check process without killing:

    ps aux | grep codeagent-wrapper | grep -v grep
    

Why: codeagent tasks often take 2-10 minutes. Killing them wastes API costs and loses progress.

Security Best Practices

  • Claude Backend: Permission checks enabled by default
    • To skip checks: set CODEAGENT_SKIP_PERMISSIONS=true or pass --skip-permissions
  • Concurrency Limits: Set CODEAGENT_MAX_PARALLEL_WORKERS in production to prevent resource exhaustion
  • Automation Context: This wrapper is designed for AI-driven automation where permission prompts would block execution

Recent Updates

  • Multi-backend support for all modes (workdir, resume, parallel)
  • Security controls with configurable permission checks
  • Concurrency limits with worker pool and fail-fast cancellation
how to use codeagent

How to use codeagent on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add codeagent
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/cexll/myclaude --skill codeagent

The skills CLI fetches codeagent from GitHub repository cexll/myclaude and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/codeagent

Reload or restart Cursor to activate codeagent. Access the skill through slash commands (e.g., /codeagent) or your agent's skill management interface.

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

List & Monetize Your Skill

Submit your Claude Code skill and start earning

GET_STARTED →

Use Cases

User Story & Requirements Generation

Create detailed user stories, acceptance criteria, and feature specs

Example

Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios

Reduce spec writing time by 50%, ensure comprehensive coverage

Competitive Analysis

Research competitors, compare features, identify gaps

Example

Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities

Complete competitive research in 2 hours instead of 2 days

Roadmap Prioritization

Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs

Example

Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale

Make data-driven prioritization decisions faster

Stakeholder Communication

Draft PRDs, status updates, and stakeholder presentations

Example

Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement

Save 3-5 hours/week on communication overhead

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client
  • Access to product documentation and roadmap tools (Jira, Notion, etc.)
  • Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
  • Stakeholder contact information and communication channels

Time Estimate

30-60 minutes to see productivity improvements

Installation Steps

  1. 1.Install product management skill
  2. 2.Start with user story generation for known feature
  3. 3.Progress to competitive analysis: research 2-3 competitors
  4. 4.Use for roadmap prioritization: apply RICE/ICE scoring
  5. 5.Draft stakeholder communications and refine based on feedback
  6. 6.Build template library for recurring PM tasks
  7. 7.Share effective prompts with product team

Common Pitfalls

  • Not validating competitive research—verify facts before sharing
  • Accepting user stories without involving engineering team
  • Over-relying on frameworks without qualitative judgment
  • Not customizing outputs to company culture and communication style
  • Skipping stakeholder validation of generated requirements

Best Practices

✓ Do

  • +Validate research and competitive analysis with real data
  • +Collaborate with engineering when generating technical requirements
  • +Customize frameworks and templates to your company context
  • +Use skill for first drafts, refine with stakeholder input
  • +Document successful prompt patterns for PM tasks
  • +Combine AI efficiency with human judgment and intuition

✗ Don't

  • Don't publish competitive analysis without fact-checking
  • Don't finalize user stories without engineering review
  • Don't make prioritization decisions solely on AI scoring
  • Don't skip customer validation of generated requirements
  • Don't ignore company-specific context and culture

💡 Pro Tips

  • Provide context: company goals, constraints, customer feedback
  • Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
  • Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
  • Use skill for 70% generation + 30% customization to company needs

When to Use This

✓ Use When

Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.

✗ Avoid When

Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.

Learning Path

  1. 1Basic: user stories, feature specs, status updates
  2. 2Intermediate: competitive analysis, prioritization frameworks, PRDs
  3. 3Advanced: product strategy, go-to-market planning, OKR setting
  4. 4Expert: product vision, market positioning, business model innovation

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.
general reviews

Ratings

4.828 reviews
  • Pratham Ware· Dec 16, 2024

    Useful defaults in codeagent — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Dhruvi Jain· Dec 8, 2024

    Keeps context tight: codeagent is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Kwame Sanchez· Dec 4, 2024

    I recommend codeagent for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Oshnikdeep· Nov 27, 2024

    Registry listing for codeagent matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Ganesh Mohane· Oct 18, 2024

    codeagent reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Aanya Yang· Sep 25, 2024

    codeagent is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Sakshi Patil· Sep 9, 2024

    codeagent has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Henry Chawla· Sep 9, 2024

    Keeps context tight: codeagent is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Chaitanya Patil· Aug 28, 2024

    Solid pick for teams standardizing on skills: codeagent is focused, and the summary matches what you get after install.

  • Mia White· Aug 28, 2024

    codeagent is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

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