AI Developer Tool / LLM Agent Monitoring
Runtime safety net for LLM agents that detects runaway token growth, classifies failure patterns, and suggests fixes without extra LLM calls. The project includes a Rust core, Python SDK, examples, benchmarks, and benchmark claims across multiple models and runs.
The page clearly describes a real AI developer tool with a specific job: detect agent spirals and diagnose why they happened. It shows usage, implementation details, examples, and evidence of benchmarking and integrations, which is enough for a useful public listing.
The snapshot does not show install steps, package maturity, release history, or how the Python SDK is wired into a real agent framework beyond a short code sample. It also leaves some product boundaries unclear, such as which runtime environments and orchestration stacks are officially supported.
Last evaluated 93 days ago. Current rank #158. Holding steady in the rankings.
A local-first Node.js utility that redacts emails, phone numbers, paths, secrets, URLs, and other identifiers from LLM prompts, then rehydrates responses locally using session-based mappings.
Self-hosted, OpenAI-compatible AI gateway for private RAG, natural-language data access, and tool-calling agents. It connects files, databases, vector stores, APIs, and MCP tools through one backend with auth, observability, and governance features.
A Claude Code skill that lets the model inspect live camera frames so it can verify hardware displays, spot wiring issues, and check physical UI behavior on real devices.
