AI Agent Skills

达尔文.skill —— 一个让你的Skill无限进化的系统：评估→改进→测试→保留或回滚 | Autoresearch-inspired autonomous skill optimization for Claude Code. Evaluate, improve, test, keep or revert.

🧊 Open source LLM observability platform. One line of code to monitor, evaluate, and experiment. YC W23 🍓

Evidently is ​​an open-source ML and LLM observability framework. Evaluate, test, and monitor any AI-powered system or data pipeline. From tabular data to Gen AI. 100+ m…

Deep dive into Claude Code internals — architecture, agent loop, context engineering, and more. / 深入解析 Claude Code 源码：架构、Agent 循环、上下文工程、工具系统等

Architecture-first skill lifecycle for AI agents. 6 modes: CREATE / IMPROVE / VALIDATE / REVIEW / OPTIMIZE / PACKAGE. BinEval binary scoring with threshold-blind, cross-…

A Comprehensive Benchmark to Evaluate LLMs as Agents (ICLR'24)

🔂 Ralph loop with PRs: Run Claude Code in a continuous loop, autonomously creating PRs, waiting for checks, and merging

Structured deep research skill for Claude Code/Open Code/Codex with human-in-the-loop control

Train, Evaluate, Optimize, Deploy Computer Vision Models via OpenVINO™

turns your codebase into an autoresearch loop — discovers what to measure, instruments the benchmark, then runs tree search with parallel subagents.

[CVPR2024 Highlight] VBench - We Evaluate Video Generation

This is an IoT device communication protocol implementation client, which will include common industrial communication protocols such as mainstream PLC communication rea…

Drives development with tests using the red-green-refactor loop. Use when implementing any logic, fixing any bug, or changing any behavior. Use when you need to prove th…

A Heterogeneous Benchmark for Information Retrieval. Easy to use, evaluate your models across 15+ diverse IR datasets.

The collaborative spreadsheet for AI. Chain cells into powerful pipelines, experiment with prompts and models, and evaluate LLM responses in real-time. Work together sea…

Create, Evaluate, and Connect AI Skills