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 13 days ago. Current rank #400. 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.
Claude Code plugin that blocks dependency edits until a fresh, source-cited version check is recorded, helping prevent hallucinated or stale package versions across npm, pip, Poetry/uv, Cargo, and NuGet.
An OWASP incubator project that protects AI agent memory from prompt injection, secret leakage, and tampering. It includes a Python library, policy-based controls, benchmarks, and integrations for agent frameworks like LangChain and AutoGen.
CLI for catching AI-generated code smells and regressions in code. It scans changes with 40+ rules across 7 languages, offers fixes, CI gating, hooks, and MCP tools.
