Developer Tool / RAG Evaluation
A GitHub example that audits LangChain’s RAG quickstart with retrieval-quality metrics, flags off-topic and out-of-distribution queries, and surfaces ranking and calibration issues with charts and results files.
The page clearly describes an AI developer tool focused on RAG retrieval auditing. The README gives a concrete use case, explains the corpus and retriever setup, and shows the kinds of failures it detects. The snapshot also includes implementation files, result JSON, and charts, which makes it useful for a public listing.
The snapshot does not show installation or run instructions beyond the example content, and it’s hard to tell how reusable the tool is outside this specific LangChain quickstart teardown. Maintenance status, supported frameworks, and a fuller feature overview are also not visible here.
Last evaluated 73 days ago. Current rank #978. Up 4 spots in the rankings.
WebLLM is a high-performance in-browser LLM inference engine that runs locally in the browser with WebGPU acceleration. It exposes an OpenAI-compatible API, supports streaming and JSON mode, and includes examples for building chat apps and browser extensions.
Self-hosted observability and control plane for production and coding AI agents, with live timelines, fleet-wide feeds, token budgets, MCP allow/block rules, and support for Claude Code plus a Python sensor.
Mindwalk is a local Go tool that replays Claude Code and Codex sessions on a 3D map of a codebase, showing where an agent searched, read, and edited files over time.
Open-source football management simulation where AI agents manage a club through MCP while humans watch the action in a terminal TUI. The repo includes a daemon, spectator console, calibration CLI, and detailed setup and command docs.
