v2.16.3 · MIT
Safari browser automation for AI agents — native macOS, zero Chrome overhead. 97 tools via AppleScript + JavaScript.
v0.2.3 · MIT
Claude Code usage governor: compact professional output, context slimming, tool-output filtering, telemetry, and drift guardrails.
v2.0.2 · Apache-2.0
Official Pulumi Agent Skills for writing, migrating, and operating infrastructure with AI coding agents
v2.5.3 · MIT
Turn your local Claude Code / Codex CLI history into a shareable, anonymized AI-Native developer profile + viral SVG poster. A skill, not a script — 100% local & read-only.
— · SEE LICENSE IN LICENSE
Code intelligence graph — MCP server + AI agent skills + visualization UI
v2.9.2 · Apache-2.0
Search ClinicalTrials.gov trials, retrieve study details and results, and match patients to eligible trials via MCP. STDIO or Streamable HTTP.
v1.0.0 · MIT
Evidence-first deep reading for AI agents — trace claims, evidence, confidence and knowledge maps across articles, books and PDFs.
v1.7.0 · MIT
DeepSeek Harness (DSH) academic writing guard for papers — 论文去AI味 / AI-writing style detection, evidence preservation, journal-fit calibration, manuscript proofreading, writing_audit & automatic checks. Local, zero network, zero LLM.
v0.6.0 · MIT
给 HR / 猎头的 AI 招聘工作流:岗位标准梳理、Boss直聘 + 猎聘双通道寻源初筛、市场人才盘点、简历评估、约面试、候选人台账与日报。可装成 Claude Code 插件或 DeepSeek Harness (dsh) 插件——后者自带可直接上手操作的「招聘浏览器」面板;也能配合任意读 AGENTS.md 的 AI 编程助手使用。
v0.3.0 · MIT
GitHub Issues-backed agent orchestration for Claude Code – a single Claude wears persona hats (Orchestrator, CEO, workers) routed by issue labels, driven by a heartbeat loop
v0.2.3 · MIT
A portable memory protocol for AI agents — load it as standing rules; a curation discipline + reference spec + optional cap hook.
v5.1.0 · MIT
You say it. AutoCode ships it. 48 skills. Code to deployment in one session. I-Lang v5.0 judgment + secret-safe deploys. Free forever.
v0.24.1 · MIT
Multi-LLM MCP server for Claude Code & Codex — route AI agent work across 20+ low-cost provider buckets with round-robin dispatch and quota-aware fallback.
v2.4.0 · MIT
Complete Kaggle integration plugin/skill for AI coding agents — competition reports, dataset/model downloads, notebook execution, and badge collection. Works with Claude Code, Gemini CLI, Cursor, Codex, OpenClaw, and 35+ agents via skills.sh.
v2.0.4 · MIT
GeneXus 18 MCP server — read, edit, and analyze GeneXus knowledge base objects (transactions, web panels, procedures, SDTs) directly from Claude, Cursor, and other AI agents over the Model Context Protocol.
v3.38.20 · MIT
🌊 The original agent meta-harness. Deploy intelligent multi-player swarms, coordinate autonomous workflows, and build conversational AI systems. Features adaptive memory, self-learning intelligence, RAG integration, and native Claude Code / Codex / Hermes and many more Integrated
v5.2.8 · MIT
A one-of-a-kind resume builder that keeps your privacy in mind. Completely secure, customizable, portable, open-source and free forever. Try it out today!
v0.6.0 · Apache-2.0
Second-model AI auto-review for DeepSeek Harness approval requests: a read-only reviewer subagent returns structured allow/deny verdicts with reasons, fail-closed by default, fully auditable from the session log (approval/asked -> autoReview/verdict -> approval/decided).
— · MIT
WorkOS Skills for AI coding agents — AuthKit, SSO, Directory Sync, RBAC, and more
v3.38.20 · MIT
🌊 The original agent meta-harness. Deploy intelligent multi-player swarms, coordinate autonomous workflows, and build conversational AI systems. Features adaptive memory, self-learning intelligence, RAG integration, and native Claude Code / Codex / Hermes and many more Integrated
— · Apache-2.0
88 installable open-source Agent Skills for research, social intelligence, marketing, and business workflows—compatible with Codex, Claude Code, Cursor, Gemini CLI, and DeepSeek Harness.
— · Apache-2.0
Spec-driven development and context engineering for Claude Code, Cursor, Codex, and GitHub Copilot — backed by project context in Git.
v2.4.2 · MIT
A Claude Code plugin whose workshop of expert agents learns as it builds: repeated fixes become permanent rules, loved tweaks become taste it remembers - and every change waits behind a write gate you control.
— · MIT
Cut context bloat in your AI-agent stack: find and safely prune unused skills, MCP servers and subagents from real transcript evidence