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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).

DeepseekModel 官方收录技能 质量 优秀 · 78 v1.0.0

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https://deepseekmodel.com/api/download.php?id=marcusgoll-spec-flow-claude-skills-create-meta-prompts-skill-md&format=skill
下载 .skill 标准格式,含 system_prompt 与 model_config,导入任意 Agent 框架即可使用
.skill 文件中 system_prompt 字段的实际内容。
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). Create prompts optimized for Claude-to-Claude communication in multi-stage workflows. Outputs (research.md, plan.md) are structured with XML and metadata for efficient parsing by subsequent prompts. Each prompt gets its own folder in .prompts/ with its output artifacts, enabling clear provenance and chain detection. <quick_start> Intake : Determine purpose (Do/Plan/Research), gather requirements Chain detection : Check for existing research/plan files to reference Generate : Create prompt using purpose-specific patterns Save : Create folder in .prompts/{number}-{topic}-{purpose}/ Present : Show decision tree for running 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> 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` <automated_workflow> <step_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 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: List them: "Found existing files: auth-research.md (in 001-auth-research/), stripe-plan.md (in 005-stripe-plan/)" 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: 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> 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. </step_0_intake_gate> <step_1_generate> Generate Prompt Load purpose-specific patterns: Do: references/do-patterns.md Plan: references/plan-patterns.md Research: references/research-patterns.md Load intelligence rules: references/intelligence-rules.md <prompt_structure> All generated prompts include: Objective : What to accomplish, why it matters Context : Referenced files (@), dynamic context (!) Requirements : Specific instructions for the task Output specification : Where to save, what structure Metadata requirements : For research/plan outputs, specify XML metadata structure 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 </prompt_structure> <file_creation> Create folder: .prompts/{number}-{topic}-{purpose}/ Create completed/ subfolder Write prompt to: .prompts/{number}-{topic}-{purpose}/{number}-{topic}-{purpose}.md Prompt instructs output to: .prompts/{number}-{topic}-{purpose}/{topic}-{purpose}.md </file_creation> </step_1_generate> <step_2_present> Present Decision Tree 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 Engine <execution_modes> <single_prompt> Straightforward execution of one prompt. Read prompt file contents Spawn Task agent with subagent_type="general-purpose" Include in task prompt: The complete prompt contents Output location: .prompts/{number}-{topic}-{purpose}/{topic}-{purpose}.md Wait for completion Validate output (see validation section) Archive prompt to completed/ subfolder Report results with next-step options </single_prompt> <sequential_execution> For chained prompts where each depends on previous output. Build execution queue from dependency order 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 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. Read all prompt files CRITICAL : Spawn ALL Task agents in a SINGLE message This is required for true parallel execution Each task includes its output location Wait for all to complete Validate all outputs Archive all prompts 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). Analyze dependency graph from @ references 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. Execute each layer: Parallel within layer Sequential between layers Stop if any dependency fails (downstream prompts can't run) ``` 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: Parse each prompt for @.prompts/{number}-{topic}/ patterns Build dependency graph Detect cycles (error if found) 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: Check if it's another prompt in this session (will be created) Check if it exists in .prompts/*/ (already completed) 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> After each prompt completes, verify success: File exists : Check output file was created Not empty : File has content (> 100 chars) Metadata present (for research/plan): Check for required XML tags <confidence> <dependencies> <open_questions> <assumptions> <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> - **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 .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 ✓ Output: .prompts/001-auth-research/auth-research.md ✓ Archived to: .prompts/001-auth-research/completed/ Summary: [Brief description of what was produced] What's next? 1. View the output 2. Create follow-up prompt (plan based on this research) 3. Done 4. Other </single_result> <chain_result> ✓ Chain completed: auth workflow Results: 1. 001-auth-research → .prompts/001-auth-research/auth-research.md [One-line summary] 2. 002-auth-plan → .prompts/002-auth-plan/auth-plan.md
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下载的 .skill 包内含以下字段。
字段 说明
format格式标识(skill/v1)
skill_id技能唯一 ID
name技能名称
version版本号
description技能描述
category所属分类(数组)
trigger_words触发词列表
tags标签列表
source来源标识
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exported_at导出时间(每次下载生成)
system_prompt系统提示词正文
model_config模型参数:provider / model / temperature / max_tokens / top_p
examples示例
install_guide各平台导入说明(Coze / Dify / Claude / 自定义框架)
同一份技能可按不同平台格式导出。
.skill 标准格式,含 system_prompt 与 model_config,导入任意 Agent 框架即可使用 下载
.skillpro 增强格式,额外含脚本 / 工具 / 依赖 / 钩子占位 下载
.json 纯 JSON 导出,只含 system_prompt 与模型参数 下载
Coze 带 frontmatter 的 Markdown,Coze 平台导入用 下载
Dify Dify DSL,创建应用后直接导入 下载

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