snitch

Log and forward LLM API requests to inspect system prompts and tool schemas.

6|1|Updated Jun 23, 2026

Search Tags:#debugging #monitoring #api #llm #proxy

Ready to run

npx skills add https://github.com/JGalego/Bag-of-Tricks --skill snitch-jgalego

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: snitch
Source: https://github.com/JGalego/Bag-of-Tricks/tree/main/snitch
Command: npx skills add https://github.com/JGalego/Bag-of-Tricks --skill snitch-jgalego

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This Skill allows users to inspect the exact requests sent by LLM agents to models, revealing hidden system prompts, tool schemas, and messages, aiding in debugging and auditing.

Core Features & Use Cases

Transparent Proxy: Logs and forwards LLM requests to an API, enabling inspection of all data sent.
Live Web UI: Provides a user-friendly interface to view and interact with captured requests.
Use Case: When a user's agent behaves unexpectedly, Snitch can be used to inspect the actual requests made, revealing hidden or unexpected context.

Quick Start

Run snitch --port 8787 to start the proxy and web UI, then point your SDK to the proxy (e.g., export ANTHROPIC_BASE_URL=http://localhost:8787).

Frequently Asked Questions about snitch

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I inspect the exact requests sent to LLM APIs by my agent?▼

To inspect requests sent to LLM APIs, run a local proxy like Snitch to intercept, log, and view the exact system prompts, tool schemas, and messages forwarded to the model. This reveals hidden context for debugging.

Why does my LLM agent behave unexpectedly despite my prompt?▼

Unexpected LLM agent behavior often stems from hidden context. By monitoring API requests with a transparent proxy, you can audit the actual system prompts and tool schemas sent to the model to find discrepancies.

How do I view hidden system prompts sent to an LLM?▼

To view hidden system prompts sent to an LLM, route your agent's traffic through a monitoring proxy. This logs the complete request payload, allowing you to inspect and interact with captured data in a live web UI.

Can I debug AI agents by monitoring their API requests locally?▼

Yes, you can debug AI agents by routing their traffic to a local proxy. Point your SDK's base URL to the proxy to monitor and audit the exact LLM API requests, capturing all messages and tool schemas.

Do I need Python to run an LLM API monitoring proxy?▼

Yes, running this LLM API monitoring proxy requires Python 3.9 or higher and standard library modules. No external dependencies are needed, making it straightforward to set up in your existing environment.