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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.
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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.
contract-review
Orchestrates a comprehensive multi-agent contract review that analyzes risk, plain-English translation, missing protections, and compliance in parallel. Use when a user shares a contract and wants a f
clawmail
Canonical joelclaw mail coordination protocol for all agents. Use when announcing work, checking inboxes, reserving files, releasing locks, handling task handoffs, triaging stale reservations, or audi
hive-mind-advanced
Advanced Hive Mind collective intelligence system for queen-led multi-agent coordination with consensus mechanisms and persistent memory
stream-chain
Stream-JSON chaining for multi-agent pipelines, data transformation, and sequential workflows
crewai-multi-agent
Multi-agent orchestration framework for autonomous AI collaboration. Use when building teams of specialized agents working together on complex tasks, when you need role-based agent collaboration with
firm-orchestration
Pyramid multi-agent orchestration for OpenClaw: routes objectives from a CEO agent down through departments, services and employees via sessions_send / sessions_spawn, collects and merges results, enf
crewai-multi-agent
Multi-agent orchestration framework for autonomous AI collaboration. Use when building teams of specialized agents working together on complex tasks, when you need role-based agent collaboration with
multi-agent-patterns
Design multi-agent architectures for complex tasks. Use when single-agent context limits are exceeded, when tasks decompose naturally into subtasks, or when specializing agents improves quality.
dispatching-parallel-agents
Use when facing 3+ independent failures that can be investigated without shared state or dependencies - dispatches multiple Claude agents to investigate and fix independent problems concurrently
task-orchestration
Use when coordinating complex tasks with orchestration, delegation, or parallel workstreams - provides structured workflows for orchestrate:brainstorm, orchestrate:spawn, and orchestrate:task.
hive-mind-advanced
Advanced Hive Mind collective intelligence system for queen-led multi-agent coordination with consensus mechanisms and persistent memory
qe-stream-chain
Stream-JSON chaining for multi-agent pipelines, data transformation, and sequential workflows
agent-orchestration
Agent orchestration patterns for agentic loops, multi-agent coordination, alternative frameworks, and multi-scenario workflows. Use when building autonomous agent loops, coordinating multiple agents,
multi-agent-architecture-reference
Decision matrix for selecting multi-agent topologies (Supervisor, Swarm, Hierarchical, Conductor) with token economics, failure modes, and escalation paths
sparc-methodology
SPARC (Specification, Pseudocode, Architecture, Refinement, Completion) comprehensive development methodology with multi-agent orchestration
team-orchestration
6-phase multi-agent pipeline with approval gates. Orchestrates Plan→Design→Implement→Review→Test→Deploy phases with explicit entry/exit criteria, phase-level agent assignment, and human-in-the-loop ap
hive-mind-advanced
Advanced Hive Mind collective intelligence system for queen-led multi-agent coordination with consensus mechanisms and persistent memory
sparc-methodology
SPARC (Specification, Pseudocode, Architecture, Refinement, Completion) comprehensive development methodology with multi-agent orchestration
stream-chain
Stream-JSON chaining for multi-agent pipelines, data transformation, and sequential workflows
agentic-workflow
Practical AI agent workflows and productivity techniques. Provides optimized patterns for daily development tasks such as commands, shortcuts, Git integration, MCP usage, and session management.
ohmg
Ultimate multi-agent framework for Google Antigravity. Orchestrates specialized domain agents (PM, Frontend, Backend, Mobile, QA, Debug) via Serena Memory.
omc
oh-my-claudecode — Teams-first multi-agent orchestration layer for Claude Code. 32 specialized agents, smart model routing, persistent execution loops, and real-time HUD visibility. Zero learning curv
opencontext
Persistent memory and context management for AI agents using OpenContext. Keep context across sessions/repos/dates, store conclusions, and provide document search workflows.
vibe-kanban
Manage AI coding agents on a visual Kanban board. Run parallel agents through a To Do→In Progress→Review→Done flow with automatic git worktree isolation and GitHub PR creation.
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.