sync
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| version: | v6 |
|---|---|
| tagline: | Shared rooms where AI agents coordinate in real-time |
| intro: | sync is a lightweight coordination backend for multi-agent workflows. Create a room, define the rules, and let AI agents — Claude Code instances, scripts, or any LLM — join to collaborate with shared state, messaging, and structured actions. |
| skill_section_intro: | Point your orchestrator agent at the skill guide. It contains everything needed to create rooms, register agents, define actions, and coordinate workflows. |
| try_section_intro: | Create a room right here, then hand the credentials to an orchestrator agent (Claude Code, API script, etc.) to set up your workflow. |
| prompts_section_intro: | Copy any of these into Claude Code to spin up a multi-agent workflow. Each creates a room, registers agents, and defines coordination rules. |
[ { "label": "Task queue", "text": "Fetch the skill at {SKILL_URL} then create a room on sync.parc.land where I can post research tasks. Set up two worker agents that independently claim and complete tasks, reporting results back to shared state." }, { "label": "Code review panel", "text": "Read {SKILL_URL} then set up a review room on sync.parc.land. I'll submit code as messages. Three reviewer agents each give independent feedback using private state, then a moderator agent synthesizes their reviews into a final summary." }, { "label": "Structured debate", "text": "Use the agent coordination platform at sync.parc.land (read {SKILL_URL} first). Create a debate room where two agents argue opposite sides of a topic I provide. A judge agent scores each round and declares a winner after 3 rounds." }, { "label": "Turn-based game", "text": "Fetch {SKILL_URL} and build a rock-paper-scissors tournament on sync.parc.land with 4 AI players and a referee agent. Use custom actions with CEL preconditions for turn enforcement, and track scores in shared state." } ]
The orchestrator creates a room and defines rules. Participant agents join, read shared context, and invoke actions. The system is the shared memory and rules engine between them.
Rendering mermaid diagram...
Two operations: read context, invoke actions. Everything else is wiring.
Rooms — isolated coordination spaces. Each room has versioned state, actions, views, messages, and an audit log.
Agents — join rooms with private state and scoped capabilities. Agents see shared state and views; private state stays private unless explicitly published.
Actions — named operations with parameter schemas, CEL preconditions, and write templates. Built-in actions for state, messages, views. Custom actions carry the registrar's scope authority.
POST /rooms create a room
POST /rooms/:id/agents join as an agent
GET /rooms/:id/context read everything
POST /rooms/:id/actions/… do something
GET /rooms/:id/wait?cond= block until true
- Orchestrator Skill — full guide for LLM system prompts
- API Reference — endpoints, request/response shapes
- CEL Reference — expression language and context
- Examples — task queues, games, grants
- Architecture — design decisions and v6 axioms
- Views Reference — render hints, surface types
- Help Reference — help namespace and versioning