v0.54.0 · MIT
OMK — Observe. Measure. Know. Evidence-backed knowledge changes for AI applications.
v0.20.2 · MIT
Design I/O for coding agents: controllable UI generation via declarations (spec/domain/craft/design/components/template) and contracts (skill/evaluator). Use for product UI—console, dashboard, agent-ops, CJK-first apps.
v0.157.3 · Apache-2.0
Signet native CLI installer wrapper
v2.67.2 · MIT
Workflow-continuity bridge for AI coding agents. Wrap Claude Code or Codex in a PTY and supervise, approve, and redirect the session from any device — async. The terminal companion for CodeAgent Mobile.
v0.2.0 · MIT
The Feishu UI for DeepSeek Harness — a panel-driven control console: every slash command a button on the ⚙️ control-panel card, in-card approvals & questions, live streaming cards, one-QR setup. | DeepSeek Harness 的飞书 UI:面板驱动控制台——每个命令都是卡片按钮,卡内审批与提问,流式卡片,扫码一键配置。
v0.1.14 · MIT
Autonomous (auto) mode permission classifier for DeepSeek Harness: a Claude-Code-auto-mode-like classifier over tools/pre-execute and approval/request, a selectable 'auto' permission preset, LLM semantic judge, git checkpointing, agent discipline guidance
— · no license
Opinionated AI agent skills for building applications with MotherDuck
v0.20.0 · Apache-2.0
Scaffolding skill + always-on conventions (CLAUDE.md/AGENTS.md) for Quarkus + LangChain4j agentic AI apps: AI services, multi-agent workflows, and RAG. Installable in Claude Code, Codex, Copilot, Cursor, and any Agent Skills-compatible agent.
v0.3.74 · MIT
One macOS app for Claude Code, Codex, and every agent runtime you use — scheduled runs, global hotkey launcher, per-run git worktrees, one review board.
v1.0.0 · MIT
Deploy files, sites, and Dockerfile apps to live URLs + private drives for agent memory.
v0.2.1 · MIT
Agentic SEO operating system as a Claude Code plugin: project Wiki, DataForSEO workflows, content briefs, technical SEO, and human-approval gates.
— · MIT
27 scope-enforced AI agents that run the full pentest kill-chain (recon → exploit → post-ex → DFIR → report) as a one-command Claude Code plugin. Backed by 754 MITRE-mapped skills.
v0.1.20 · MIT
Self-evolving memory for DeepSeek Harness (DSH): earned experiences, diary/fact semantic memory, concern tracking, and an append-only audit ledger.
— · MIT
Agent Alchemy is a curated collection of plugins, apps, and extensions designed to elevate your agentic engineering workflows. Built for Claude Code and other AI coding agents, these tools help developers work smarter and ship faster.
— · Apache-2.0
One portable memory layer for every AI agent: local-first, Markdown-native, user-owned, and self-evolving across apps, tools, and workflows.
v0.3.1 · Apache-2.0
Log Claude Code sessions to Opik, the open-source LLM observability and evaluation platform, built by Comet. Tracing, evaluation, and skills for observable AI applications.
v0.6.3 · no license
A Unified MCP Server Management App (MCP Manager).
— · Apache-2.0
Lemonade helps users discover and run local AI apps by serving optimized LLMs right from their own GPUs and NPUs. Join our discord: https://discord.gg/5xXzkMu8Zk
v0.1.0 · Apache-2.0
The Forge Skills Plugin bundles several Forge-focused skills plus MCP-backed tooling so your agent can scaffold apps, review them before deploy, debug production issues, and stay current on Forge APIs and the Atlassian Design System.
v1.5.9 · MIT
clawdcursor compiles whatever's on screen into one UI map — accessibility tree and OCR fused into stable, addressable elements, with a screenshot only when needed — then drives apps through reusable scripts, verifying every action and routing it through a single safety gate.
v3.1.0 · MIT
Reverse engineer anything with agents, from app behavior down to native binaries.
v1.0.1 · no license
Give your AI agent a spending limit: approval controls and single-use virtual cards.
— · MIT
Runtime guardrails for Claude Code. Auto-approve what's safe, gate what's risky, block what's dangerous. Dual enforcement, full audit trail. MIT.
v4.8.1 · MIT
The agentic harness for AI coding agents — work cycles, bounded RAG context, persistent memory, guardrails, and performance evals.