Developer Tools / AI Evaluation
Reference implementation for building and understanding AI evaluation systems, including rule-based evaluation, human review, LLM-as-a-Judge, online evaluation, and experiment comparison for a flight search app.
The page clearly describes an AI-focused repository with a concrete goal: teaching and implementing evaluation workflows for AI applications. It shows what is implemented, how the project is structured, the prerequisites, configuration steps, and runnable commands for multiple evaluation examples, which is enough for a useful directory listing.
The snapshot does not show packaging or release maturity beyond the README examples, and it is not clear how complete the codebase is outside the documented evaluation flows or how reusable it is for other applications without adaptation.
Last evaluated 5 days ago. Current rank #360. Down 4 spots in the rankings.
CodeGraph is a local code knowledge graph for AI coding agents like Claude Code, Cursor, Codex, OpenCode, and Hermes Agent. It aims to cut token use, tool calls, and runtime by letting agents query pre-indexed code structure instead of scanning files repeatedly.
Mercemur is a store automation platform with three interfaces: a REST API, an MCP server for AI agents, and a CLI for editing storefronts as files. The docs show authentication, scopes, rate limits, error handling, pagination, idempotency, and a large API surface for catalogue, orders, customers, pricing, and money.
A zero-dependency C++23 CLI and MCP server that gives coding agents a ranked map of a repository, including call context, blast radius, and tests to run.
Traccia is an AI agent observability and governance platform with OpenTelemetry-native tracing, runtime policy enforcement, prompt registry, evals, cost attribution, and compliance evidence export.
