AI提示词工程与自动化工作流工具 - 创建元提示词与智能项目管理

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Contains Shell Commands

This skill contains shell command directives (!command``) that may execute system commands. Review carefully before installing.

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.

<quick_start>

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

<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>

<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
  • "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

→ 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

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>

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

Then proceed to generation. </step_0_intake_gate>

<step_1_generate>

Load purpose-specific patterns:

• Do: references/do-patterns.md
• Plan: references/plan-patterns.md
• Research: references/research-patterns.md
• Refine: references/refine-patterns.md

Load intelligence rules: references/intelligence-rules.md

<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 </prompt_structure>

<file_creation>

1. Create folder: .prompts/{number}-{topic}-{purpose}/
2. Create completed/ subfolder
3. Write prompt to: .prompts/{number}-{topic}-{purpose}/{number}-{topic}-{purpose}.md
4. Prompt instructs output to: .prompts/{number}-{topic}-{purpose}/{topic}-{purpose}.md </file_creation> </step_1_generate>

<step_2_present>

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

<single_prompt_presentation>

Prompt created: .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): _

</single_prompt_presentation>

<multi_prompt_presentation>

Prompts created:
- .prompts/001-auth-research/001-auth-research.md
- .prompts/002-auth-plan/002-auth-plan.md
- .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): _

</multi_prompt_presentation> </step_2_present>

<step_3_execute>

<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: .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 </single_prompt>

<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)

</progress_reporting> </sequential_execution>

<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 </failure_handling> </parallel_execution>

<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)

<dependency_detection> <automatic_detection> Scan prompt contents for @ references to determine dependencies:

1. Parse each prompt for @.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. </inference_rules> </automatic_detection>

<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 .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? </missing_dependencies> </dependency_detection>

4. File exists : Check output file was created

5. Not empty : File has content (> 100 chars)

6. Metadata present (for research/plan): Check for required XML tags

   • <confidence>
   • <dependencies>
   • <open_questions>
   • <assumptions>

7. : Check SUMMARY.md was created

<validation_failure> If validation fails:

• Report what's missing
• Offer options:
  • Retry the prompt
  • Continue anyway (for non-critical issues)
  • Stop and investigate </validation_failure> </output_validation>

<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

</sequential_failure>

<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

</parallel_failure> </failure_handling>

<archive_operation> Move prompt file to completed subfolder:

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

Output file stays in place (not moved). </archive_operation>

<result_presentation> <single_result>

✓ Executed: 001-auth-research
✓ Created: .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. </single_result>

<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 .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. </chain_result> </result_presentation>

<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 </re_running_completed>

<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? </output_conflicts>

<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) </commit_handling>

<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 </recursive_prompts> </special_cases> </step_3_execute>

</automated_workflow>

<reference_guides> Prompt patterns by purpose:

• references/do-patterns.md - Execution prompts + output structure
• references/plan-patterns.md - Planning prompts + plan.md structure
• references/research-patterns.md - Research prompts + research.md structure
• references/refine-patterns.md - Iteration prompts + versioning

Shared templates:

• references/summary-template.md - SUMMARY.md structure and field requirements
• references/metadata-guidelines.md - Confidence, dependencies, open questions, assumptions

Supporting references:

• references/question-bank.md - Intake questions by purpose
• references/intelligence-rules.md - Extended thinking, parallel tools, depth decisions </reference_guides>

<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 .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 </success_criteria>

Weekly Installs

69

Repository

glittercowboy/t…esources

GitHub Stars

1.7K

First Seen

Jan 23, 2026

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