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create-meta-prompts

majiayu000
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Metaaiautomation

About

This skill generates structured prompts optimized for Claude-to-Claude communication in multi-stage workflows and pipelines. It's designed for complex scenarios requiring XML-formatted outputs with metadata for efficient parsing by subsequent prompts. Key features include automatic organization into versioned folders and the creation of a `SUMMARY.md` for quick human review.

Quick Install

Claude Code

Recommended
Plugin CommandRecommended
/plugin add https://github.com/majiayu000/claude-skill-registry
Git CloneAlternative
git clone https://github.com/majiayu000/claude-skill-registry.git ~/.claude/skills/create-meta-prompts

Copy and paste this command in Claude Code to install this skill

Documentation

Objective Create prompts optimized for Claude-to-Claude communication in multi-stage workflows. Outputs are structured with XML and metadata for efficient parsing by subsequent prompts. Every execution produces a SUMMARY.md for quick human scanning without reading full outputs. Each prompt gets its own folder in .claude/workspace/prompts/ with its output artifacts, enabling clear provenance and chain detection.

Quick Start

Workflow

  1. Intake: Determine purpose (Do/Plan/Research/Refine), 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 .claude/workspace/prompts/{number}-{topic}-{purpose}/
  5. Present: Show decision tree for running
  6. Execute: Run prompt(s) with dependency-aware execution engine
  7. Summarize: Create SUMMARY.md for human scanning

Folder Structure

.claude/workspace/prompts/
├── 001-auth-research/
│   ├── completed/
│   │   └── 001-auth-research.md    # Prompt (archived after run)
│   ├── auth-research.md            # Full output (XML for Claude)
│   └── SUMMARY.md                  # Executive summary (markdown for human)
├── 002-auth-plan/
│   ├── completed/
│   │   └── 002-auth-plan.md
│   ├── auth-plan.md
│   └── SUMMARY.md
├── 003-auth-implement/
│   ├── completed/
│   │   └── 003-auth-implement.md
│   └── SUMMARY.md                  # Do prompts create code elsewhere
├── 004-auth-research-refine/
│   ├── completed/
│   │   └── 004-auth-research-refine.md
│   ├── archive/
│   │   └── auth-research-v1.md     # Previous version
│   └── SUMMARY.md

Context Prompts directory: ![ -d ./.claude/planning/prompts ] && echo "exists" || echo "missing" Existing research/plans: !find ./.claude/planning/prompts -name "*-research.md" -o -name "*-plan.md" 2>/dev/null | head -10 Next prompt number: !ls -d ./.claude/workspace/prompts/*/ 2>/dev/null | wc -l | xargs -I {} expr {} + 1

Automated Workflow

0. Intake Gate

Adaptive Requirements Gathering

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
    • "Refine" - Improve an existing research or plan output 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
  • refine, improve, deepen, expand, iterate, update → Refine → If unclear, ask the Purpose question above as first contextual question → If clear, proceed to adaptive_analysis with inferred purpose
Adaptive Analysis

Extract and infer:

  • Purpose: Do, Plan, Research, or Refine
  • 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
  • Target (Refine only): Which existing output to improve 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) For Refine purpose, also identify target output from .claude/workspace/prompts/*/ to improve.
Chain Detection

Scan .claude/workspace/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).
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
  • Refine → target selection, feedback, preservation
Decision Gate

After receiving answers, present decision gate using AskUserQuestion:

  • header: "Ready"
  • question: "Ready to create the prompt?"
  • options:
    • "Proceed" - Create the prompt with current context
    • "Ask more questions" - I have more details to clarify
    • "Let me add context" - I want to provide additional information Loop until "Proceed" selected.
Finalization

After "Proceed" selected, state confirmation: "Creating a {purpose} prompt for: {topic} Folder: .claude/workspace/prompts/{number}-{topic}-{purpose}/ References: {list any chained files}" Then proceed to generation.

1. Generate

Generate Prompt

Load purpose-specific patterns:

Prompt Structure

All generated prompts include:

  1. Objective: What to accomplish, why it matters
  2. Context: Referenced files (@), dynamic context (!)
  3. Requirements: Specific instructions for the task
  4. Output specification: Where to save, what structure
  5. Metadata requirements: For research/plan outputs, specify XML metadata structure
  6. SUMMARY.md requirement: All prompts must create a SUMMARY.md file
  7. Success criteria: How to know it worked For Research and Plan prompts, output must include:
  • <confidence> - How confident in findings
  • <dependencies> - What's needed to proceed
  • <open_questions> - What remains uncertain
  • <assumptions> - What was assumed All prompts must create SUMMARY.md with:
  • One-liner - Substantive description of outcome
  • Version - v1 or iteration info
  • Key Findings - Actionable takeaways
  • Files Created - (Do prompts only)
  • Decisions Needed - What requires user input
  • Blockers - External impediments
  • Next Step - Concrete forward action

File Creation

  1. Create folder: .claude/workspace/prompts/{number}-{topic}-{purpose}/
  2. Create completed/ subfolder
  3. Write prompt to: .claude/workspace/prompts/{number}-{topic}-{purpose}/{number}-{topic}-{purpose}.md
  4. Prompt instructs output to: .claude/workspace/prompts/{number}-{topic}-{purpose}/{topic}-{purpose}.md

2. Present

Present Decision Tree

After saving prompt(s), present inline (not AskUserQuestion):

Single Prompt Presentation

Prompt created: .claude/workspace/prompts/{number}-{topic}-{purpose}/{number}-{topic}-{purpose}.md
What's next?
1. Run prompt now
2. Review/edit prompt first
3. Save for later
4. Other
Choose (1-4): _

Multi-Prompt Presentation

Prompts created:
- .claude/workspace/prompts/001-auth-research/001-auth-research.md
- .claude/workspace/prompts/002-auth-plan/002-auth-plan.md
- .claude/workspace/prompts/003-auth-implement/003-auth-implement.md
Detected execution order: Sequential (002 references 001 output, 003 references 002 output)
What's next?
1. Run all prompts (sequential)
2. Review/edit prompts first
3. Save for later
4. Other
Choose (1-4): _

3. Execute

Execution Engine

Execution Modes

Single Prompt

Straightforward execution of one prompt.

  1. Read prompt file contents
  2. Spawn Task agent with subagent_type="general-purpose"
  3. Include in task prompt:
    • The complete prompt contents
    • Output location: .claude/workspace/prompts/{number}-{topic}-{purpose}/{topic}-{purpose}.md
  4. Wait for completion
  5. Validate output (see validation section)
  6. Archive prompt to completed/ subfolder
  7. Report results with next-step options
Sequential Execution

For chained prompts where each depends on previous output.

  1. Build execution queue from dependency order
  2. For each prompt in queue: a. Read prompt file b. Spawn Task agent c. Wait for completion d. Validate output e. If validation fails → stop, report failure, offer recovery options f. If success → archive prompt, continue to next
  3. Report consolidated results
Progress Reporting

Show progress during execution:

Executing 1/3: 001-auth-research... ✓
Executing 2/3: 002-auth-plan... ✓
Executing 3/3: 003-auth-implement... (running)
Parallel Execution

For independent prompts with no dependencies.

  1. Read all prompt files
  2. CRITICAL: Spawn ALL Task agents in a SINGLE message
    • This is required for true parallel execution
    • Each task includes its output location
  3. Wait for all to complete
  4. Validate all outputs
  5. Archive all prompts
  6. Report consolidated results (successes and failures)
Failure Handling

Unlike sequential, parallel continues even if some fail:

  • Collect all results
  • Archive successful prompts
  • Report failures with details
  • Offer to retry failed prompts
Mixed Dependencies

For complex DAGs (e.g., two parallel research → one plan).

  1. Analyze dependency graph from @ references
  2. Group into execution layers:
    • Layer 1: No dependencies (run parallel)
    • Layer 2: Depends only on layer 1 (run after layer 1 completes)
    • Layer 3: Depends on layer 2, etc.
  3. Execute each layer:
    • Parallel within layer
    • Sequential between layers
  4. Stop if any dependency fails (downstream prompts can't run)
Example
Layer 1 (parallel): 001-api-research, 002-db-research
Layer 2 (after layer 1): 003-architecture-plan
Layer 3 (after layer 2): 004-implement
Dependency Detection
Automatic Detection

Scan prompt contents for @ references to determine dependencies:

  1. Parse each prompt for @.claude/workspace/prompts/{number}-{topic}/ patterns
  2. Build dependency graph
  3. Detect cycles (error if found)
  4. Determine execution order
Inference Rules

If no explicit @ references found, infer from purpose:

  • Research prompts: No dependencies (can parallel)
  • Plan prompts: Depend on same-topic research
  • Do prompts: Depend on same-topic plan Override with explicit references when present.
Missing Dependencies

If a prompt references output that doesn't exist:

  1. Check if it's another prompt in this session (will be created)
  2. Check if it exists in .claude/workspace/prompts/*/ (already completed)
  3. If truly missing:
    • Warn user: "002-auth-plan references auth-research.md which doesn't exist"
    • Offer: Create the missing research prompt first? / Continue anyway? / Cancel?
Validation
Output Validation

After each prompt completes, verify success:

  1. File exists: Check output file was created
  2. Not empty: File has content (> 100 chars)
  3. Metadata present (for research/plan): Check for required XML tags
    • <confidence>
    • <dependencies>
    • <open_questions>
    • <assumptions>
  4. SUMMARY.md exists: Check SUMMARY.md was created
  5. SUMMARY.md complete: Has required sections (Key Findings, Decisions Needed, Blockers, Next Step)
  6. One-liner is substantive: Not generic like "Research completed"
Validation Failure

If validation fails:

  • Report what's missing
  • Offer options:
    • Retry the prompt
    • Continue anyway (for non-critical issues)
    • Stop and investigate
Failure Handling
Sequential Failure

Stop the chain immediately:

✗ Failed at 2/3: 002-auth-plan
Completed:
- 001-auth-research ✓ (archived)
Failed:
- 002-auth-plan: Output file not created
Not started:
- 003-auth-implement
What's next?
1. Retry 002-auth-plan
2. View error details
3. Stop here (keep completed work)
4. Other
Parallel Failure

Continue others, report all results:

Parallel execution completed with errors:
✓ 001-api-research (archived)
✗ 002-db-research: Validation failed - missing <confidence> tag
✓ 003-ui-research (archived)
What's next?
1. Retry failed prompt (002)
2. View error details
3. Continue without 002
4. Other
Archiving
Archive Timing
  • Sequential: Archive each prompt immediately after successful completion
    • Provides clear state if execution stops mid-chain
  • Parallel: Archive all at end after collecting results
    • Keeps prompts available for potential retry
Archive Operation

Move prompt file to completed subfolder:

mv .claude/workspace/prompts/{number}-{topic}-{purpose}/{number}-{topic}-{purpose}.md \
   .claude/workspace/prompts/{number}-{topic}-{purpose}/completed/

Output file stays in place (not moved).

Result Presentation
Single Result
✓ Executed: 001-auth-research
✓ Created: .claude/workspace/prompts/001-auth-research/SUMMARY.md
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
# Auth Research Summary
**JWT with jose library and httpOnly cookies recommended**

##
Key Findings
• jose outperforms jsonwebtoken with better TypeScript support
• httpOnly cookies required (localStorage is XSS vulnerable)
• Refresh rotation is OWASP standard

##
Decisions Needed
None - ready for planning

##
Blockers
None

##
Next Step
Create auth-plan.md
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
What's next?
1. Create planning prompt (auth-plan)
2. View full research output
3. Done
4. Other

Display the actual SUMMARY.md content inline so user sees findings without opening files.

Chain Result
✓ Chain completed: auth workflow
Results:
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
001-auth-research
**JWT with jose library and httpOnly cookies recommended**
Decisions: None • Blockers: None
002-auth-plan
**4-phase implementation: types → JWT core → refresh → tests**
Decisions: Approve 15-min token expiry • Blockers: None
003-auth-implement
**JWT middleware complete with 6 files created**
Decisions: Review before Phase 2 • Blockers: None
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
All prompts archived. Full summaries in .claude/workspace/prompts/*/SUMMARY.md
What's next?
1. Review implementation
2. Run tests
3. Create new prompt chain
4. Other

For chains, show condensed one-liner from each SUMMARY.md with decisions/blockers flagged.

Special Cases
Re-running Completed

If user wants to re-run an already-completed prompt:

  1. Check if prompt is in completed/ subfolder
  2. Move it back to parent folder
  3. Optionally backup existing output: {output}.bak
  4. Execute normally
Output Conflicts

If output file already exists:

  1. For re-runs: Backup existing → {filename}.bak
  2. For new runs: Should not happen (unique numbering)
  3. If conflict detected: Ask user - Overwrite? / Rename? / Cancel?
Commit Handling

After successful execution:

  1. Do NOT auto-commit (user controls git workflow)
  2. Mention what files were created/modified
  3. User can commit when ready Exception: If user explicitly requests commit, stage and commit:
  • Output files created
  • Prompts archived
  • Any implementation changes (for Do prompts)
Recursive Prompts

If a prompt's output includes instructions to create more prompts:

  1. This is advanced usage - don't auto-detect
  2. Present the output to user
  3. User can invoke skill again to create follow-up prompts
  4. Maintains user control over prompt creation

Reference Guides Prompt patterns by purpose:

Success Criteria Prompt Creation:

  • Intake gate completed with purpose and topic identified
  • Chain detection performed, relevant files referenced
  • Prompt generated with correct structure for purpose
  • Folder created in .claude/workspace/prompts/ with correct naming
  • Output file location specified in prompt
  • SUMMARY.md requirement included in prompt
  • Metadata requirements included for Research/Plan outputs
  • Quality controls included for Research outputs (verification checklist, QA, pre-submission)
  • Streaming write instructions included for Research outputs
  • Decision tree presented Execution (if user chooses to run):
  • Dependencies correctly detected and ordered
  • Prompts executed in correct order (sequential/parallel/mixed)
  • Output validated after each completion
  • SUMMARY.md created with all required sections
  • One-liner is substantive (not generic)
  • Failed prompts handled gracefully with recovery options
  • Successful prompts archived to completed/ subfolder
  • SUMMARY.md displayed inline in results
  • Results presented with decisions/blockers flagged Research Quality (for Research prompts):
  • Verification checklist completed
  • Quality report distinguishes verified from assumed claims
  • Sources consulted listed with URLs
  • Confidence levels assigned to findings
  • Critical claims verified with official documentation

<critical_constraint> MANDATORY: Create SUMMARY.md for every prompt execution MANDATORY: Validate output file exists and has required sections before archiving MANDATORY: Use proper XML metadata tags for research/plan outputs MANDATORY: Present decision tree before executing prompts MANDATORY: Handle validation failures gracefully with recovery options No exceptions. Meta-prompts must maintain provenance and enable human scanning. </critical_constraint>


Genetic Code

This component carries essential Seed System principles for context: fork isolation:

<critical_constraint> MANDATORY: All components MUST be self-contained (zero .claude/rules dependency) MANDATORY: Achieve 80-95% autonomy (0-5 AskUserQuestion rounds per session) MANDATORY: Description MUST use What-When-Not format in third person MANDATORY: No component references another component by name in description MANDATORY: Progressive disclosure - references/ for detailed content MANDATORY: Use XML for control (mission_control, critical_constraint), Markdown for data No exceptions. Portability invariant must be maintained. </critical_constraint>

Delta Standard: Good Component = Expert Knowledge − What Claude Already Knows

Recognition Questions:

  • "Would Claude know this without being told?" → Delete (zero delta)
  • "Can this work standalone?" → Fix if no (non-self-sufficient)
  • "Did I read the actual file, or just see it in grep?" → Verify before claiming

GitHub Repository

majiayu000/claude-skill-registry
Path: skills/create-meta-prompts

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