How does the skill handle task dependencies?

The skill scans the .prompts/ directory for existing research or plans and builds a dependency graph using @-references to determine the correct execution order.

What is a Claude-to-Claude pipeline?

It is a multi-stage workflow where the output of one Claude prompt is structured (often in XML) to be consumed as the input or context for a subsequent Claude prompt.

Can I run multiple prompts at the same time?

Yes, the skill includes an execution engine that supports parallel processing for independent tasks and sequential processing for dependent chains.

Why does it create a SUMMARY.md file?

While the main outputs are structured for AI consumption, the SUMMARY.md provides a high-level executive summary for humans to quickly scan outcomes, findings, and next steps.

Meta-Prompt Orchestrator

Name: Meta-Prompt Orchestrator
Author: glittercowboy

byglittercowboy

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770

Productivity & Workflow

Generates and manages optimized prompt chains for multi-stage Claude-to-Claude workflows including research, planning, and implementation phases.

About

The Meta-Prompt Orchestrator is a sophisticated framework for building complex AI pipelines within Claude Code. It automates the 'Intake-to-Execution' lifecycle by categorizing tasks into Research, Plan, Do, or Refine stages and generating specialized prompts optimized for inter-agent communication. By enforcing a standardized .prompts/ directory structure, the skill ensures clear provenance, manages dependencies between tasks, and provides human-readable SUMMARY.md files alongside machine-ready XML outputs. This is ideal for developers tackling non-trivial features that require deep analysis before code is written.

Key Features

Automated dependency detection for sequential or parallel task execution
Automated folder organization and versioned prompt archiving
Multi-stage workflow generation (Research, Plan, Implement, Refine)
Human-readable SUMMARY.md generation for quick human oversight
770 GitHub stars
Structured XML outputs optimized for Claude-to-Claude parsing

Use Cases

Managing large-scale refactors where architectural plans must be validated before implementation
Developing complex features that require a research and planning phase before coding
Creating automated documentation or testing pipelines that consume output from previous steps

About

Key Features

Automated dependency detection for sequential or parallel task execution
Automated folder organization and versioned prompt archiving
Multi-stage workflow generation (Research, Plan, Implement, Refine)
Human-readable SUMMARY.md generation for quick human oversight
770 GitHub stars
Structured XML outputs optimized for Claude-to-Claude parsing

Use Cases

Managing large-scale refactors where architectural plans must be validated before implementation
Developing complex features that require a research and planning phase before coding
Creating automated documentation or testing pipelines that consume output from previous steps