#pytest

AI Testing Agent Framework · 16 experts + 32 skills + 49 utils · Multi-LLM (Claude/OpenAI/Qwen/etc) · MCP-native · Open-source · Learn-while-using

AI Quality Engineering framework for evaluating LLM and RAG applications using automated prompt testing, hallucination detection, and AI evaluation metrics.

AI-powered resume and job-description analysis platform with document parsing, skill-gap detection, ATS insights, and structured evaluation.

Local-first AgentOps control plane prototype for safe AI-to-agent command validation, policy evaluation, and redacted audit logging.

Turn failing pytest runs into structured repair reports: failure parsing, root-cause diagnosis, flaky detection, dry-run fix diffs, and an optional LLM layer. 把失败的 pytest 运行转化为结构化修复报告。

Pytest fixtures for the fakellm mock OpenAI/Anthropic server

AI-powered workload analyzer with AFI, OPE, capacity planning, and AI-assisted prioritization for students.

Autonomous coding agent that fixes buggy repos by iterating against their pytest suite in an isolated Docker sandbox provider-agnostic LLM layer, 22-task eval harness, and OpenTelemetry→Langfuse tracing.

Production-oriented AI inspection platform combining Computer Vision, LLMs, FastAPI, and Docker to generate automated engineering reports from industrial images.

End-to-end RAG system built from scratch with recursive chunking, persistent indexing, vector + BM25 hybrid retrieval, evaluation, FastAPI, Docker, and AWS deployment testing.

A CLI developer tool for running custom evaluation suites to OpenAI-compatible APIs (MiMo, Claude, GPT, etc.), outputting Markdown research reports + JSON traces. Useful for developers who want to benchmark models before production. Suitable for Data/Research + Dev tools, and a natural fit using the MiMo API + Hermes Agent workflow.

A lightweight local Coding Agent harness inspired by learn-claude-code s20, featuring a minimal LLM tool-use loop, workspace-safe file access, command execution, and pytest-verified Phase 1 tools.

A thin, CI-gated evaluation gate for RAG & LLM systems — golden set, band-based pass/warn/fail gates, LLM-judge or heuristic scorers. pip install raggate

Skill de Claude Code que audita si tus pruebas sabrían ponerse rojas. Instalable como plugin desde el marketplace. La misma herramienta que el repositorio hermano, empaquetada para que la use tu asistente.

Claude Code skills, MCP server kits, GitHub Actions, CLI tools — production-ready developer resources

API REST de gestión de tareas con FastAPI, CRUD, endpoints de IA con Azure OpenAI y tests con pytest.

Small FastMCP-based corpus project exploring tested MCP tools, readable resources, and local AI-client workflows.