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/create-meta-prompts

Create optimized prompts for Claude-to-Claude pipelines with research, planning, and execution stages. Use when building prompts that produce outputs for other prompts to consume, or when running multi-stage workflows (research -> plan -> implement).

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taches-cc-resources
2k12 skills3 agents39 commands
Install
$ npx -y skills add glittercowboy/taches-cc-resources --skill create-meta-prompts --agent claude-code

How it fires

How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/create-meta-prompts

Context preview

The summary Claude sees to decide when to auto-load this skill.

Create optimized prompts for Claude-to-Claude pipelines with research, planning, and execution stages. Use when building prompts that produce outputs for other prompts to consume, or when running multi-stage workflows (research -> plan -> implement).

SKILL.md

create-meta-prompts.SKILL.md
name: create-meta-prompts
description: Create optimized prompts for Claude-to-Claude pipelines with research, planning, and execution stages. Use when building prompts that produce outputs for other prompts to consume, or when running multi-stage workflows (research -> plan -> implement).

<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 `.prompts/` with its output artifacts, enabling clear provenance and chain detection. </objective>

<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 `.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 </workflow>

<folder_structure>

.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

</folder_structure> </quick_start>

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

<automated_workflow>

<step_0_intake_gate> <title>Adaptive Requirements Gathering</title>

<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 </critical_first_action>

<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 `.prompts/*/` to improve. </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](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

</contextual_questioning>

<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. </decision_gate>

<finalization> After "Proceed" selected, state confirmation:

"Creating a {purpose} prompt for: {topic} Folder: .prompts/{number}-{topic}-{purpose}/ References: {list any chained files}"

Then proceed to generation. </finalization> </step_0_intake_gate>

<step_1_generate> <title>Generate Prompt</title>

Load purpose-specific patterns:

  • Do: [references/do-patterns.md](references/do-patterns.md)
  • Plan: [references/plan-patterns.md](references/plan-patterns.md)
  • Research: [references/research-patterns.md](references/rese
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