claude-context-local

🥈Silver

Claude Context Local enables coding agents to search and reference an entire codebase as context. Operations teams benefit from faster code generation and reduced API costs. It integrates with Python-based workflows and supports Claude agents.

205220Updated 1w ago

Intermediate30min to implementautomation

Saves ~180 min per use

Quick InstallView Source

git clone https://github.com/FarhanAliRaza/claude-context-local.git

Works with:

Claude

Overview

About This Skill

How to Use

["Identify the specific task or problem you need to solve in your codebase (e.g., 'Implement a caching layer for API responses').","Use the claude-context-local tool to search for relevant files, functions, or classes by specifying keywords or patterns (e.g., 'cache', 'memoization', 'Redis').","Review the tool's output to understand existing patterns, dependencies, or gaps in the codebase related to your task.","Refine your search if needed by adjusting keywords or adding constraints (e.g., 'Python', 'FastAPI', 'Django').","Use the insights to draft a solution, ensuring you reference specific files or functions for context.","Test your solution in a development environment and iterate based on feedback or errors."]

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/FarhanAliRaza/claude-context-local

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

Act as a coding agent with access to the local codebase. Use the claude-context-local tool to search for [TARGET_FILES_OR_FUNCTIONS] related to [SPECIFIC_TASK]. Analyze the codebase to identify patterns, dependencies, or best practices for [TASK_DESCRIPTION]. Provide a concise summary of findings and suggest a high-level approach to implement [SOLUTION]. Reference specific files, classes, or functions where relevant.

Example Output

After invoking the claude-context-local tool, I analyzed the codebase for files related to user authentication, specifically focusing on JWT token handling. The search revealed three key files: `auth/jwt.py`, `services/auth_service.py`, and `models/user.py`. In `jwt.py`, I found a utility function `generate_token()` that creates JWT tokens with a 1-hour expiration, while `auth_service.py` contains `validate_token()` which checks token validity and refreshes expired tokens. The `user.py` model includes a `last_login` field that isn't currently updated during token validation. Based on this, I recommend implementing a feature to update the `last_login` timestamp whenever `validate_token()` is called. This would require modifying `auth_service.py` to include a call to `user.update_last_login()` after successful validation. The existing token generation logic in `jwt.py` appears robust and aligns with security best practices, so no changes are needed there. This approach would enhance user activity tracking without introducing new dependencies.