create-agent-skills
Expert guidance for creating, writing, building, and refining Claude Code Skills. Use when working with SKILL.md files, authoring…
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).
$ npx -y skills add glittercowboy/taches-cc-resources --skill create-meta-prompts --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/create-meta-promptsContext 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).
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:
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:
→ 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:
If topic identifier not obvious, ask:
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:
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:
</contextual_questioning>
<decision_gate> After receiving answers, present decision gate using AskUserQuestion:
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:
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