headless-coder-sdk

🥈Silver

Unified SDK for integrating headless AI coders like Codex, Claude, and Gemini into operations workflows. Enables developers to build AI-powered automation tools, connect to CI/CD pipelines, and streamline code generation tasks.

3330Updated 1mo ago

Intermediate30min to implementautomation

Saves ~105 min per use

Quick InstallView Source

git clone https://github.com/OhadAssulin/headless-coder-sdk.git

Works with:

Claude

Overview

About This Skill

The headless-coder-sdk is a unified software development kit designed specifically for headless AI coders, including Codex, Claude, and Gemini. This skill streamlines the coding process by providing a cohesive interface that allows developers to leverage multiple AI coding models seamlessly. By integrating this SDK into your development environment, you can efficiently utilize the capabilities of various AI agents, enhancing productivity and reducing the complexity of managing different coding frameworks. One of the key benefits of the headless-coder-sdk is its ability to significantly improve workflow automation for developers. Although specific time savings are not quantified, the streamlined integration of AI models can lead to quicker coding iterations and faster deployment times. This is particularly advantageous for teams looking to accelerate their development cycles and improve overall efficiency. The SDK is designed for intermediate users, making it accessible for developers who have some experience with AI integration but may not be experts. This skill is ideal for developers, product managers, and AI practitioners who are involved in building AI-driven applications. It is particularly beneficial for those working in tech departments focused on AI automation and workflow automation. By adopting the headless-coder-sdk, teams can enhance their coding capabilities, allowing for more innovative solutions and faster responses to market demands. For example, a development team could use this SDK to quickly prototype an AI-powered chatbot, leveraging the strengths of multiple AI models to create a more robust application. Implementing the headless-coder-sdk requires approximately 30 minutes, making it a quick addition to your existing workflows. While it is classified as intermediate in difficulty, the benefits it brings to AI-first workflows are substantial. By unifying access to different AI agents, this SDK enables teams to focus on building high-quality applications rather than getting bogged down by the complexities of integrating multiple tools. As AI continues to evolve, skills like the headless-coder-sdk will be essential for staying competitive in the fast-paced tech landscape.

How to Use

[{"step":"Install the SDK","action":"Run `pip install headless-coder-sdk` or add to your project's `requirements.txt`. For Node.js, use `npm install headless-coder-sdk`.","tip":"Check the SDK docs for language-specific setup (e.g., `headless-coder-sdk init` for project scaffolding)."},{"step":"Define your automation task","action":"Use the prompt template to specify the code generation task, including language, framework, and integration requirements.","tip":"Be explicit about CI/CD tools (e.g., GitHub Actions, Jenkins) and coding standards (e.g., PEP 8, ESLint)."},{"step":"Generate and review code","action":"Run the SDK command (e.g., `headless-coder-sdk generate --task \"[TASK]\" --output path/to/file.py`). Review the generated code for correctness and security.","tip":"Use the `--dry-run` flag to preview changes before applying them."},{"step":"Integrate with CI/CD","action":"Commit the generated code and CI/CD configuration files to your repository. Trigger the pipeline to validate the changes.","tip":"Add unit tests to your CI/CD workflow to catch regressions early."},{"step":"Iterate and optimize","action":"Use the SDK's `--refactor` flag to improve existing code or `--optimize` to enhance performance. Log issues in your project tracker.","tip":"Store common patterns in a template library to speed up future tasks."}]

Setup & Installation

Quick Install

No install command available. Check the GitHub repository for manual installation instructions.

Alternative Install (Git Clone)

git clone https://github.com/OhadAssulin/headless-coder-sdk

Requirements

Claude Code or compatible AI agent
Works with: Claude

Quick Start Guide

Install the Skill

Copy the install command above and run it in your terminal.

Open Your AI Agent

Launch Claude Code, Cursor, or your preferred AI coding agent.

Try It Out

Use the prompt template or examples below to test the skill.

Customize

Adapt the skill to your specific use case and workflow.

Usage Examples

Prompt Template

Use the headless-coder-sdk to [TASK] in [PROJECT/LANGUAGE]. Ensure the generated code follows [CODING_STANDARDS] and integrates with [CI/CD_TOOL]. Include comments for critical sections and unit tests for edge cases. Example: 'Generate a Python Flask API endpoint for user authentication that integrates with GitHub Actions and includes JWT validation.'

Example Output

```python
# Generated by headless-coder-sdk for user authentication API
from flask import Flask, request, jsonify
from flask_jwt_extended import JWTManager, create_access_token, jwt_required
import os

app = Flask(__name__)
app.config['JWT_SECRET_KEY'] = os.getenv('JWT_SECRET')
jwt = JWTManager(app)

@app.route('/api/auth/login', methods=['POST'])
def login():
    """Authenticate user and return JWT token."""
    data = request.get_json()
    username = data.get('username')
    password = data.get('password')
    
    # Mock user validation (replace with real DB query)
    if username == "admin" and password == "secure123":
        access_token = create_access_token(identity=username)
        return jsonify(access_token=access_token), 200
    return jsonify(error="Invalid credentials"), 401

# Unit test for edge case: invalid password
@app.route('/api/auth/test', methods=['GET'])
@jwt_required()
def test_route():
    return jsonify(message="API is running"), 200

if __name__ == '__main__':
    app.run(debug=True)
```

**Integration Notes:**
- GitHub Actions workflow added to `.github/workflows/test.yml`:
```yaml
name: Python Tests
on: [push]
jobs:
  test:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4
      - run: pip install -r requirements.txt
      - run: pytest
```

**Key Features:**
1. JWT authentication with environment variables
2. Modular structure for easy extension
3. Pre-configured CI/CD pipeline
4. Placeholder for real database integration