Code, Build and Evaluate agents - excellent Model and Skills/MCP/ACP/A2A Support

Agent Skill evaluation harness for paired variants, trace artifacts, and runner adapters

Multi-tier framework for evaluating AI agent skills with quality gates, semantic overlap detection, synthetic evaluation dataset generation, and live agent evaluation that measures how skills affect agent behavior.

Playwright for coding agents. Benchmark Claude Code, Codex, Gemini, and OpenCode on your own tasks - and test that your skills, MCP servers, and CLIs work when an agent uses them. Sandboxed YAML suites, activation checks, A/B experiments, CI gates.

Agent Skills Evaluation Framework

Comet: agent skill harness for turning ideas into evaluated workflows

Optimize any AI agent’s skills, tools/MCP, and prompts against your own evals.

Testing and evaluation platform to chat, inspect, and debug MCP servers, MCP apps, and ChatGPT apps.

An evaluation and evolution tool for Agent Skills.

[COLM'26] SkillLearnBench is the first benchmark for evaluating continual learning methods that automatically generate agent skills.

Open-source observability & evaluation platform for AI agents and coding agents. Trace LLMs, tools, prompts, costs & agent workflows with OpenTelemetry.

Evaluate agent skill quality. Find the weakest link. Fix it. Prove it worked.

The Fable Workflow: how Claude Fable 5 worked, distilled into skills any model can run, with the eval that keeps it honest. Think / act / prove.

A skill creator that proves its skills work. Evidence-driven skill creation for Claude Code and Codex: baseline-tested generation, per-skill regression evals, ecosystem doctor, cross-runtime compile, and an opt-in proactive advisor.

Agent OS: the agent gets smarter on its own. We just hold the line: Interview-gated, staged evaluation, budgeted evolution loop. MCP server, 14 runtimes: Claude Code, Codex CLI, Gemini CLI, OpenCode, Copilot, Kiro and more.

Production-grade Agent Skills for AI coding agents—composable workflows for planning, TDD, debugging, review, UI/UX, releases, incidents, and evals.

One-stop handbook for building, deploying, and understanding LLM agents with 60+ skeletons, tutorials, ecosystem guides, and evaluation tools.

A local MCP runtime that attacks what you own and only reports what it proved. 17 CVEs across 9 projects came out of this repo. Install: npx -y hacker-bob@latest install /path/to/project, then run /bob-evaluate target.com

🐙 ADLC Team Skills — Agentic SDLC for Engineering Teams

SkillsVote: Lifecycle Governance of Agent Skills from Collection, Recommendation to Evolution

Skills for your skills. Create, test, audit, package, and visualize Agent Skill libraries—locally.

Use cultivar to test your Agent Skills, run them in sandboxes, and across different agents.

Multi-agent orchestration system for Claude Code with parallel execution, automated quality gates, Board of Directors, and bundled Superpowers skills

Deletion-first Agent Skill for removing test bloat, verification theater, and speculative fallbacks while preserving behavior.