Marketplace
Everything your AI needs, in one place.
Ready-made agents, skills, personas, prompts, templates and tools. Each one is checked before it goes live, works with any model, and installs in a click. Rate what you use so the best rises to the top.
- 143.8K
- listings
- 1
- installs
- 0
- reviews
- 38.7K
- publishers
A service that does a whole job for you - research, coding, support - and reports back.
Step-by-step instructions an AI follows for one kind of task. Install once, reuse everywhere.
A voice and set of rules layered onto any model: tone, audience, do's and don'ts.
A ready-to-use prompt with fill-in-the-blank variables and notes on when it works best.
A complete routing setup - models, rules and settings - in one file you can apply in a minute.
A single function an AI can call: a calculator, a search, a database lookup.
A language model endpoint with its price, speed and quality declared so the router can compare it.
init
Creates, updates, or optimizes an AGENTS.md file for a repository with minimal, high-signal instructions covering non-discoverable coding conventions, tooling quirks, workflow preferences, and project
agent-self-scheduling
Schedule AI agent runs with cron, loops, or external clocks while avoiding unsafe tight autonomous timers.
cmux
Control cmux workspaces, panes, surfaces, and agent sessions safely from macOS terminal workflows.
delegating-to-agents
Delegate bounded work to other AI agents while preserving context, ownership, and progress checks.
distribute-skill-to-all-agents
Distribute a skill across configured agent skill folders while respecting local symlink layouts.
runaway-guard
Cost-safety discipline for paid AI / inference APIs: treat $-cost as a third complexity dimension alongside time and space. Forces a written per-run $-cap, per-day $-cap, max-iterations bound, concurr
weaviate-cookbooks
Build Weaviate AI apps from official cookbook blueprints for RAG, agentic RAG, data exploration, multimodal PDF search, async clients, and frontends.
feature-dev
Automate 7-phase feature development with specialized agents (code-explorer, code-architect, code-reviewer). Use for multi-file features, architectural decisions, or encountering ambiguous requirement
composio
Use 1000+ external apps via Composio - either directly through the CLI or by building AI agents and apps with the SDK
agent-engineering-expert
Build LLM agents that use tools safely: tool design, the agent loop, memory, MCP servers, multi-agent orchestration, sandboxing and prompt-injection defence. Use when the user mentions AI agents, tool
convex-agents
Building AI agents with the Convex Agent component including thread management, tool integration, streaming responses, RAG patterns, and workflow orchestration
mpm-orchestration-demo
Reference implementation demonstrating the Command → Agent → Skill orchestration pattern in Claude MPM, showing both preloaded-skill and dynamic-skill-invocation styles
agentic-evaluation-framework
This skill should be used when the user asks to "evaluate LLM output quality", "set up LLM-as-judge", "build an eval rubric", "compare model outputs pairwise", or "measure agent quality".
computer-use-automation
This skill should be used when the user asks to "build a computer-use agent", "automate a GUI with an AI agent", "when to use computer use vs an API", "make browser automation reliable", or "design sc
extended-thinking-architect
This skill should be used when the user asks to "decide reasoning effort", "set a thinking budget", "when to use extended thinking", "tune reasoning vs cost", or "should this task use a reasoning mode
senior-prompt-engineer
Prompt engineering and LLM evaluation. Use when optimizing prompts, designing prompt templates, evaluating LLM outputs, building agentic systems, implementing RAG, creating few- shot examples, or desi
compound-engineering-2
Make your AI agent learn and improve automatically. Reviews sessions, extracts learnings, updates memory files, and compounds knowledge over time. Set up nightly review loops that make your agent smar
compound-engineering-3
Make your AI agent learn and improve automatically. Reviews sessions, extracts learnings, updates memory files, and compounds knowledge over time. Set up nightly review loops that make your agent smar
compound-engineering
Make your AI agent learn and improve automatically. Reviews sessions, extracts learnings, updates memory files, and compounds knowledge over time. Set up nightly review loops that make your agent smar
clade-architecture-variants
Build different types of Claude-powered applications — chatbots, RAG systems, Use when working with architecture-variants patterns. agents, content pipelines, and code generation tools. Trigger with "
langchain-deep-agents
Build a LangGraph 1.0 Deep Agent — planner + subagents + virtual filesystem + reflection loop — without the state-growth and prompt-inheritance traps. Use when building a long-horizon agent that must
langchain-langgraph-agents
Build a correct LangGraph 1.0 ReAct agent with create_react_agent — typed tools, error propagation, recursion caps, and stop conditions that actually stop. Use when writing a first tool-calling agent,
openrouter-function-calling
Implement function/tool calling with OpenRouter models. Use when building agents, structured output, or tool-augmented LLM workflows. Triggers: 'openrouter function calling', 'openrouter tools', 'open
artifact-creator
Create or revise Agent Skills, host plugins and subagents, MCP servers and client configurations, hooks, and marketplace catalogs against their actual specifications. Use when building reusable agent
Find
Search or browse by kind. Every card shows who made it, how many people installed it and what they think.
Install
One click. You get a manifest the router understands, plus copy-paste snippets for the CLI, Python and YAML.
Rate and publish
Leave a star rating after you have used it. Made something useful? Publish it - free listings go live immediately.
Prefer the terminal? osr stack apply registry://starter installs the starter template.