← 返回
数据分析

advanced-skill-creator

Advanced OpenClaw skill creation handler that executes the official 5-step research flow with comprehensive analysis and best practices. Ensures proper methodology when users request to create or modify OpenClaw/Moltbot/ClawDBot skills following official standards.
高级OpenClaw技能创建处理器,执行官方五步研究流程并提供全面分析与最佳实践。确保用户按官方标准创建或修改OpenClaw/Moltbot/ClawDBot技能时遵循正确的方法论。
xqicxx
数据分析 clawhub v1.0.0 1 版本 99809.1 Key: 无需
★ 2
Stars
📥 3,619
下载
💾 19
安装
1
版本
#latest

概述

Advanced Skill Creator

Advanced skill creation handler that executes the official 5-step research flow with comprehensive analysis and best practices. Ensures proper methodology and standards compliance by following the complete research process, applicable to all timeframes and use cases.

When to use

  • When user mentions "写一个触发", "写skill", "claw skill", "openclaw skill", "moltbot skill", "创建技能", or "写一个让它..."
  • When proper skill creation methodology needs to be followed according to official standards
  • When ensuring adherence to 5-step research flow (documentation, ClawHub, community, fusion, output)
  • For comprehensive skill analysis and creation with best practices

5-Step Research Flow Execution

Step 1: Consult Official Documentation

Comprehensively access official documentation:

  • https://docs.clawd.bot/tools/skills
  • https://docs.openclaw.ai/tools/skills
  • /tools/clawhub
  • /tools/skills-config

Extract key information:

  • SKILL.md format requirements
  • YAML frontmatter specifications (name, description, when, examples, metadata.openclaw.*, requires)
  • Trigger mechanisms (natural language triggers, when conditions)
  • Tool calling conventions (exec, browser, read, write, nodes, MCP)
  • Loading precedence (workspace > ~/.openclaw/skills > bundled)
  • ClawHub installation methods
  • Breaking changes (latest versions)

Step 2: Research Related Public Skills on ClawHub/ClawdHub

Thoroughly query ClawHub/ClawdHub for relevant skills:

  • Search keywords: weather, reminder, schedule, translate, image, cron, memory, task-tracker, notification, backup, automation
  • Select 2-4 most relevant skills with high downloads/recent updates/community ratings
  • Analyze:
  • Trigger descriptions (when, examples)
  • YAML metadata
  • Pure Markdown vs. scripts/ structure
  • Dependency declarations
  • Error handling recommendations
  • Community feedback (why popular or criticized)
  • Security considerations

Step 3: Search Best Practices

Use comprehensive keyword combinations for GitHub searches:

  • "OpenClaw SKILL.md" OR "ClawDBot skill example" OR "Moltbot create skill"
  • "SKILL.md" "when:" OR "metadata.openclaw" site:github.com
  • "clawhub install" "custom skill" OR "openclaw skill tutorial"
  • "skill security" OR "prompt injection prevention" OR "skill best practices"

Focus on:

  • Active GitHub repositories
  • Recent commits
  • Blog/Reddit/X content
  • Security best practices
  • Known security pitfalls (prompt injection, exec abuse)

Step 4: Solution Fusion & Comparison

Comprehensively summarize implementation approaches from all three sources:

Compare across key dimensions:

  • Trigger precision (false positive rate)
  • Maintainability/readability
  • Loading speed/memory impact
  • Compatibility (different gateways/channels/versions)
  • Security & error isolation
  • Upgrade friendliness (dependency on specific tools)
  • Dependency management complexity
  • Performance optimization
  • Error handling robustness

Select optimal solution for current context with 4-7 clear reasons prioritized:

  • Official documentation > High-quality ClawHub skills > Active community solutions > Self-optimization

Step 5: Proper Output Structure

Output must follow exact structure without adding extra headers or showing raw search logs:

  • Use the exact headings: 【最终推荐方案】, 【文件结构预览】, 【完整文件内容】
  • Provide complete file contents with proper formatting
  • Include tree-style directory structure preview
  • Use proper YAML frontmatter in SKILL.md examples
  • Ensure comprehensive documentation

Resource Utilization

Documentation Features Utilized

  • YAML frontmatter format (name, description, when, examples, metadata.openclaw.*)
  • Trigger mechanism definition (when field)
  • Example specification (examples field)
  • Metadata definition (metadata.openclaw.requires)
  • Standardized skill description structure

Skills Referenced

  • system-monitor: Structure and functional organization
  • security-monitor: Metadata definition format
  • integrated-system-monitor: Script organization and implementation
  • Other existing skills: YAML frontmatter best practices

Community Practices Integrated

  • GitHub popular OpenClaw skill project structures
  • Community-recommended security practices (input validation, error handling)
  • Optimal metadata configuration methods
  • Effective trigger word definition patterns

Custom Scripts Created

  • advanced_skill_processor.py: Implements complete 5-step research flow automation
  • Automated documentation query, public skill research, best practice search
  • Solution fusion and comparison functionality
  • Standardized output generation
  • Error handling and logging features

Implementation Requirements

  1. Execute all 5 steps in strict sequence - no skipping allowed
  2. Do not rely on memory or "approximately correct" code
  3. Demonstrate research → comparison → selection logical chain
  4. Show evidence of consulting official documentation
  5. Include proper metadata and security considerations
  6. Provide complete, functional skill implementations with proper structure
  7. Ensure all outputs follow the exact template structure required
  8. Apply universally regardless of timeframe or version
  9. Include security best practices and error handling
  10. Provide comprehensive examples and use cases
  11. Include system prompt integration for enhanced AI interaction
  12. Incorporate thinking model framework for improved decision-making

System Prompt Integration

When creating new skills, include system prompt elements that enhance AI interaction:

"You are now an OpenClaw (formerly ClawDBot / Moltbot) skill development expert, implementing advanced thinking models for enhanced decision-making. Apply structured cognitive processing while balancing speed and accuracy based on specific situational requirements."

Skill Creation Guidelines

  • Apply the multi-stage cognitive processing pipeline during skill design
  • Integrate memory systems for continuous learning and improvement
  • Balance speed optimization with accuracy enhancement in skill functionality
  • Include appropriate system prompts for AI assistants using the skill
  • Document decision-making processes for future reference and learning

版本历史

共 1 个版本

  • v1.0.0 当前
    2026-03-28 11:36 安全 安全

安全检测

腾讯云安全 (Keen)

安全,无风险
查看报告

腾讯云安全 (Sanbu)

安全,无风险
查看报告

🔗 相关推荐

developer-tools

thinking-model-enhancer

xqicxx
高级思维模型,提升决策速度与准确性。集成记忆系统,通过比较和整合过往思维模型实现持续增强。
★ 7 📥 3,073
data-analysis

A股量化 AkShare

mbpz
A股量化数据分析工具,基于AkShare库获取A股行情、财务数据、板块信息等。用于回答关于A股股票查询、行情数据、财务分析、选股等问题。
★ 163 📥 59,735
data-analysis

Excel / XLSX

ivangdavila
创建、检查和编辑 Microsoft Excel 工作簿及 XLSX 文件,支持可靠的公式、日期、类型、格式、重算及模板保留功能。
★ 367 📥 140,067