workflow-design-bible
Reduces friction in multi-agent system design by codifying governance and communication patterns upfront, preventing coordination failures and role confusion…
A constitution generator for autonomous, agent-run projects: an interview-driven meta system prompt (and installable skill) that scaffolds a CEO-orchestrated sub-agent + skill + CLI architecture.
- Generate a constitution document that defines roles and decision-making rules for your AI agent team.
- Build a multi-agent architecture with clear hierarchies by answering guided interview questions about your project goals.
- Create reusable skill definitions and CLI commands that autonomous agents can execute without human intervention.
Reduces friction in multi-agent system design by codifying governance and communication patterns upfront, preventing coordination failures and role confusion that derail autonomous project execution.
Teams deploying multi-agent AI systems needing formal constitution frameworks and agent orchestration patterns without manual architecture redesign.
https://github.com/preangelleo/workflow-design-bible
By preangelleo
How to Get It
claude plugins install preangelleo/workflow-design-bible
Tip: Paste this into a Claude Code conversation. Verify command matches your Claude Code version.
Auto-generated from the tool's public listing — not hands-on verified. Cross-check against the source repo's README before running.
After installing, paste this into Claude:
Help me generate a constitution document that defines roles and decision-making rules for my AI agent team
Trust Signals Auto-scanned
Community Pulse New
No community discussions found yet. This doesn't mean the tool isn't good — it may be new or serve a niche use case.
Reviewer notes
Auto-scanned review. These are observations, not a security certification.
Scored from trust signals (evidence-eval-v1): 33 GitHub stars; contributors unknown; last commit 0d ago; license MIT.
Things to check
- Scanned, not hands-on tested — this entry was auto-scanned from public metadata (GitHub metrics, license, security flags). No reviewer has run it, and no tool-specific limitations have been documented yet.
How to evaluate tools before deploying →
Data shown here comes from public APIs and automated scanning. Reviewer notes reflect one person's experience. This is not a security certification or legal recommendation. Always evaluate tools according to your own organization's policies.
Evaluation
Scored from trust signals (evidence-eval-v1): 33 GitHub stars; contributors unknown; last commit 0d ago; license MIT.