Execute deterministic multi-agent workflows defined in JSON and Markdown.
npx skills add https://github.com/choru-k/skills-for-ai --skill pi-flow
Please help me install this Agent Skill. Skill: pi-flow Source: https://github.com/choru-k/skills-for-ai/tree/main/public/pi/pi-flow Command: npx skills add https://github.com/choru-k/skills-for-ai --skill pi-flow
This Skill provides a robust engine for defining, executing, and inspecting complex multi-agent workflows, moving beyond simple agent-to-agent communication to structured, deterministic, and resumable process orchestration.
flow.json) and agent behavior in Markdown (agents/*.md).flow.step) or until completion (flow.run.until_wait), ensuring predictable outcomes.Use the pi_flow skill to start a new workflow run named 'code-review-process' using the 'code-review-workflow' definition.
High-intent search queries and answers about installing and using this skill.
You can orchestrate multi-agent workflows by defining process topology in strict JSON and agent behavior in Markdown, executing them step-by-step or until completion for deterministic outcomes.
Yes, agent coordination tasks support resumable runs through runtime state persistence, allowing workflows to be paused and resumed during long-running tasks or interruptions.
Complex agent coordination patterns are defined using strict JSON for workflow topology and Markdown files for agent behavior, enabling specialized agents like planners and reviewers to collaborate.
Yes, workflow state can be inspected during execution using a live TUI inspector, allowing users to monitor agent spawning, message routing, and artifact validation in real-time.
The best way to validate artifacts is by using result contracts within the workflow definition, ensuring deterministic execution and predictable outcomes across coordinated agents.
Yes, workflows can be executed step-by-step using specific execution commands, ensuring deterministic execution and allowing users to inspect agent state before proceeding to the next phase.
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