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Groq Debug Bundle

Listed
jeremylongshore·vlatest·testing·MIT

Analyzes Groq model execution traces to identify performance bottlenecks and debugging insights from jeremylongshore.

Repository

Install on your platform

Showing Claude Code. One command installs this skill into any of the agents below.

  1. 1

    Run this in your project

    terminal
    $ npx skills add jeremylongshore/tons-of-skills-marketplace --skill groq-debug-bundle -a claude-code

  2. Uses the open-source skills CLI and needs Node.js. Add -g to install it for your user instead of this project.

What we know about this skill

Publisher

jeremylongshore

Taken from the source listing. We haven't verified who controls this account.

Install target

Live repository

Not pinned. Installing fetches whatever the repository holds at the time you run the command.

Nobody has reviewed this code. TrustedSkills indexes and links skills; it does not audit, run or scan them. A skill runs with whatever access you give your agent — read the source before you install it.

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scanned

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Not scanned. none of the 396 skills in the repository match this slug — it was most likely renamed or removed upstream after the registry indexed it Source recorded as jeremylongshore/claude-code-plugins-plus-skills.
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About this skill

What it does

The groq-debug-bundle skill provides tools for debugging and analyzing AI agent interactions with the Groq language model. It allows you to inspect request payloads, response headers, and other relevant data points during execution. This facilitates identifying issues related to prompt formatting, API integration, or unexpected behavior within the Groq environment.

When to use it

  • Troubleshooting Unexpected Results: When an AI agent produces incorrect or nonsensical outputs from Groq, this skill helps pinpoint the source of the problem in the request-response cycle.
  • API Integration Debugging: When integrating with the Groq API, you can use this skill to verify that requests are being formatted correctly and responses are received as expected.
  • Performance Analysis: Examine response headers to understand latency and resource utilization during Groq model inference.
  • Prompt Engineering Refinement: Inspect request payloads to ensure prompts are structured in a way that maximizes the effectiveness of the Groq model.

Key capabilities

  • Inspects request payloads sent to Groq.
  • Examines response headers received from Groq.
  • Provides visibility into API interaction details.

Example prompts

  • "Show me the last request payload sent to Groq."
  • "Display the HTTP headers in the most recent Groq response."
  • "What was the content type of the last Groq response?"

Tips & gotchas

This skill requires access to the underlying AI agent's execution environment and API calls. Ensure proper permissions are configured for debugging purposes.