context-engineering

🥈Silver

Context Engineering enhances coding agents like Claude Code and GitHub Copilot by providing precise context. It benefits developers and operations teams by improving code accuracy and reducing debugging time. Integrates with IDEs and version control systems.

3950Updated 2mo ago

Intermediate30min to implementautomation

Saves ~60 min per use

Quick InstallView Source

git clone https://github.com/wmeints/context-engineering.git

Works with:

Claude

Overview

About This Skill

Context Engineering is a systematic approach to improving AI agent performance in software development by preparing comprehensive, layered context before tasks begin. Rather than relying on ad-hoc prompts, it uses structured files like TASK.md and custom instructions to provide agents with architectural patterns, documentation, and project-specific knowledge. The methodology combines research-driven plan generation with self-validating workflows, allowing developers to review implementation plans before execution. This approach reduces iteration cycles, improves code consistency, and produces documentation as a natural byproduct. Context Engineering supports both Claude Code and GitHub Copilot in Visual Studio Code.

How to Use

1. **Identify Context Sources:** Gather files, logs, and config paths relevant to your task (e.g., `src/`, `logs/`, `.env`). Use `git log --oneline -n 10` to find recent commits. 2. **Structure the Prompt:** Fill the template with placeholders like `[TASK]`, `[FILES_OR_MODULES]`, and `[KEYWORD]`. For example: `[TASK] = "Debug memory leak in API gateway"`, `[FILES_OR_MODULES] = "src/gateway/handler.py"`. 3. **Use IDE Shortcuts:** In VS Code, highlight code snippets and use `Ctrl+Shift+P` > "Claude: Add Context" to auto-populate the prompt. For GitHub Copilot, prefix comments with `# Context:` to trigger context injection. 4. **Iterate with Feedback:** After the AI generates a response, review its output and refine the context. For instance, if the AI misses a dependency, add it to `[CONFIG_FILE]` and regenerate. 5. **Automate Context Collection:** Use scripts like `find . -name "*.py" -exec grep -l "oauth2" {} \;` to dynamically populate `[FILES_OR_MODULES]` before pasting into the prompt.

Use Cases

Generating detailed implementation plans before agent-assisted coding

Documenting project architecture and patterns for consistent code generation

Reducing debugging time by providing agents comprehensive codebase context

Validating agent-generated code quality through structured workflows

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/wmeints/context-engineering

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

Generate precise context for [TASK] in [PROJECT_NAME]. Include: 1) Relevant code snippets from [FILES_OR_MODULES], 2) Recent commit messages or PR descriptions related to [KEYWORD], 3) Error logs or test failures from [TEST_SUITE], and 4) Dependencies or environment variables from [CONFIG_FILE]. Format as a structured context brief for [AI_CODING_TOOL].

Example Output

### Context Brief for Implementing OAuth2 in `auth-service`

**1. Code Snippets:**
From `src/auth/oauth2.py` (v1.2.3):
```python
class OAuth2Client:
    def __init__(self, client_id, client_secret):
        self.token_url = "https://auth.example.com/oauth/token"
        self.scope = ["read:user", "write:repo"]
```

**2. Recent Commits:**
- `feat: add refresh token support` (PR #45, 2024-05-12)
- `fix: validate token expiry before use` (Commit 7a8b9c1, 2024-05-10)

**3. Error Logs:**
```
ERROR: OAuth2Client - Token refresh failed: 401 Unauthorized
Request: POST https://auth.example.com/oauth/token
Headers: {'Content-Type': 'application/x-www-form-urlencoded'}
Body: client_id=...&client_secret=...&grant_type=refresh_token
```

**4. Dependencies:**
- `requests>=2.31.0` (from `requirements.txt`)
- `python-dotenv>=1.0.0` (for `.env` file parsing)

**Task:** Implement a retry mechanism for token refresh failures with exponential backoff. Prioritize handling 401 errors first.