Intercept, debug, and analyze Claude Code API requests using mitmproxy. Ideal for operations teams to troubleshoot and optimize API interactions. Connects to Claude Code CLI for seamless debugging workflows.
git clone https://github.com/alexfazio/cc-trace.gitThe cc-trace skill is a powerful tool designed for developers and AI practitioners who need to intercept, debug, analyze, and review Claude Code API requests. Utilizing mitmproxy, this interactive assistant allows users to gain insights into API interactions, making it easier to identify issues and optimize workflows. By streamlining the debugging process, cc-trace enhances the development experience and promotes efficient troubleshooting. One of the key benefits of using cc-trace is its ability to save time during the debugging phase of API development. Although specific time savings are currently unknown, the skill's intermediate complexity suggests that it can significantly reduce the time spent on manual debugging tasks. By automating the interception and analysis of API requests, developers can focus on building robust applications rather than getting bogged down in troubleshooting. This skill is particularly suited for developers and product managers who are involved in API development and integration. As organizations increasingly adopt AI automation and workflow automation strategies, having tools like cc-trace becomes essential for maintaining high-quality code and efficient development processes. Practical use cases include debugging API calls during the development of AI agents or ensuring the reliability of data pipelines in data engineering projects. Implementing cc-trace is straightforward, with an estimated time of 30 minutes to set up. While the skill is categorized as intermediate in difficulty, it requires no specific department or role expertise, making it accessible to a wide range of users. By incorporating cc-trace into your AI-first workflows, you can enhance your debugging capabilities and ensure that your Claude Code applications run smoothly.
No install command available. Check the GitHub repository for manual installation instructions.
git clone https://github.com/alexfazio/cc-traceCopy the install command above and run it in your terminal.
Launch Claude Code, Cursor, or your preferred AI coding agent.
Use the prompt template or examples below to test the skill.
Adapt the skill to your specific use case and workflow.
Act as an interactive assistant for intercepting, debugging, analyzing, and reviewing Claude Code API requests using mitmproxy. I'm working with [COMPANY] in the [INDUSTRY] sector. I need to [SPECIFIC TASK, e.g., 'trace API calls to identify performance bottlenecks in our data processing pipeline']. Guide me through the process step by step.
## API Request Analysis for [COMPANY] ### Intercepted Requests - **Request 1**: `POST /api/v1/data-process` - **Status**: 200 OK - **Latency**: 1.2s - **Payload Size**: 5.4 KB - **Issue**: High latency due to large payload - **Request 2**: `GET /api/v1/report` - **Status**: 404 Not Found - **Latency**: 0.3s - **Payload Size**: 0 KB - **Issue**: Endpoint not found, check API documentation ### Recommendations 1. Optimize payload size for `POST /api/v1/data-process` 2. Verify endpoint existence for `GET /api/v1/report` 3. Consider implementing request caching for frequently accessed data ### Next Steps 1. Review API documentation for correct endpoints 2. Implement payload compression for large requests 3. Monitor API performance after optimizations
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