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By caasi
Define and validate multi-step AI agent workflows using Arrow-style DSL operators like >>> (sequence), *** (parallel), &&& (and), ||| (or), ? (conditional), loop, let...in. Validates syntax with ocaml-compose-dsl binary, plans tool calls before execution for reliable automation.
npx claudepluginhub caasi/dong3 --plugin composeA Claude Code plugin marketplace by caasi.
Delegate tasks to external OpenAI-compatible chat endpoints with capability probing, delegation patterns, and prompt injection awareness.
See plugins/chat-subagent/skills/chat-subagent/README.md for full documentation.
Describe multi-step agent workflows using an Arrow-style DSL and validate them structurally with the ocaml-compose-dsl binary. The DSL is a planning language — the agent expands it into concrete tool calls.
See plugins/compose/skills/compose/README.md for full documentation.
Reflect on human-AI stewardship through Socratic dialogue. A mirror, not a checklist — rooted in Audrey Tang's Humane Intelligence framework and Civic AI 6-Pack of Care.
See plugins/kami/skills/kami/README.md for full documentation.
claude plugin marketplace add caasi/dong3
MIT
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Based on adoption, maintenance, documentation, and repository signals. Not a security audit or endorsement.
Multi-agent workflow orchestration via YAML. Ships the conductor skill so the assistant can validate, run, debug, and author workflow files for the conductor CLI.
Workflow generation skills for Coze, Dify, and ComfyUI. Generate importable workflow definitions from natural language descriptions.
Expert LangGraph/LangChain agent builder with MCP integration, workflow orchestration, and CLI accessibility. Creates production-ready AI agents that are reachable via command line and Claude Code.
This skill should be used when the model's ROLE_TYPE is orchestrator and needs to delegate tasks to specialist sub-agents. Provides scientific delegation framework ensuring world-building context (WHERE, WHAT, WHY) while preserving agent autonomy in implementation decisions (HOW). Use when planning task delegation, structuring sub-agent prompts, or coordinating multi-agent workflows.
Design multi-agent systems, handoffs between AI agents, and human-in-the-loop workflows.
Orchestrate complex workflows with DAG-based execution, parallel tasks, and run history tracking
Socratic dialogue for reflecting on human-AI stewardship
Platform-specific fetch strategies for content that resists simple WebFetch
Delegate tasks to external chat endpoints (OpenAI-compatible and LM Studio native API) as a subagent
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