Developer Tools / AI Evaluation
A GitHub repository that proposes a practical methodology for evaluating how AI systems behave during real work, with quick-start, practitioner, and methodology guides included.
The page clearly describes an AI-adjacent tool for evaluating model behavior in realistic workflows, and the repository includes concrete materials a visitor can use: a quick start guide, practitioner’s guide, methodology PDF, and a report aid. The purpose is specific, the target users are named, and the repo provides enough evidence for a useful public listing.
The crawl does not show the actual contents of the PDFs, so it’s hard to tell how actionable the evaluation steps are or what exact scoring criteria it uses. There are also no visible examples, screenshots, or implementation details showing how the methodology is applied in practice.
Last evaluated 104 days ago. Current rank #1610. Up 6 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.
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.
Single-binary CLI that builds an AI agent knowledge base from git repos, Claude Code/Codex sessions, and saved links. It generates a portable markdown wiki, runs on cron, supports local Ollama mode, and exposes the result for agents via CLAUDE.md/AGENTS.md and MCP.
A lightweight React Markdown renderer with built-in LaTeX, syntax highlighting, streaming-safe rendering, and security-focused defaults.
