create-meta-prompts

Each prompt gets its own folder in .prompts/ with its output artifacts, enabling clear provenance and chain detection.

<quick_start>

1. Intake: Determine purpose (Do/Plan/Research), gather requirements
2. Chain detection: Check for existing research/plan files to reference
3. Generate: Create prompt using purpose-specific patterns
4. Save: Create folder in .prompts/{number}-{topic}-{purpose}/
5. Present: Show decision tree for running
6. Execute: Run prompt(s) with dependency-aware execution engine

<folder_structure>

.prompts/
├── 001-auth-research/
│   ├── completed/
│   │   └── 001-auth-research.md    # Prompt (moved after run)
│   └── auth-research.md            # Output
├── 002-auth-plan/
│   ├── completed/
│   │   └── 002-auth-plan.md
│   └── auth-plan.md
├── 003-auth-implement/
│   ├── 003-auth-implement.md       # Prompt
│   └── (implementation artifacts)

</folder_structure> </quick_start>

<automated_workflow>

<step_0_intake_gate>

<critical_first_action> BEFORE analyzing anything, check if context was provided.

IF no context provided (skill invoked without description): → IMMEDIATELY use AskUserQuestion with:

• header: "Purpose"
• question: "What is the purpose of this prompt?"
• options:
  • "Do" - Execute a task, produce an artifact
  • "Plan" - Create an approach, roadmap, or strategy
  • "Research" - Gather information or understand something

After selection, ask: "Describe what you want to accomplish" (they select "Other" to provide free text).

IF context was provided: → Check if purpose is inferable from keywords:

• implement, build, create, fix, add, refactor → Do
• plan, roadmap, approach, strategy, decide, phases → Plan
• research, understand, learn, gather, analyze, explore → Research

→ If unclear, ask the Purpose question above as first contextual question → If clear, proceed to adaptive_analysis with inferred purpose </critical_first_action>

<adaptive_analysis> Extract and infer:

• Purpose: Do, Plan, or Research
• Topic identifier: Kebab-case identifier for file naming (e.g., auth, stripe-payments)
• Complexity: Simple vs complex (affects prompt depth)
• Prompt structure: Single vs multiple prompts

If topic identifier not obvious, ask:

• header: "Topic"
• question: "What topic/feature is this for? (used for file naming)"
• Let user provide via "Other" option
• Enforce kebab-case (convert spaces/underscores to hyphens) </adaptive_analysis>

<chain_detection> Scan .prompts/*/ for existing *-research.md and *-plan.md files.

If found:

1. List them: "Found existing files: auth-research.md (in 001-auth-research/), stripe-plan.md (in 005-stripe-plan/)"
2. Use AskUserQuestion:
   • header: "Reference"
   • question: "Should this prompt reference any existing research or plans?"
   • options: List found files + "None"
   • multiSelect: true

Match by topic keyword when possible (e.g., "auth plan" → suggest auth-research.md). </chain_detection>

<contextual_questioning> Generate 2-4 questions using AskUserQuestion based on purpose and gaps.

Load questions from: references/question-bank.md

Route by purpose:

• Do → artifact type, scope, approach
• Plan → plan purpose, format, constraints
• Research → depth, sources, output format </contextual_questioning>

<decision_gate> After receiving answers, present decision gate using AskUserQuestion: