advanced-skill-creator

Other

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.

Install

openclaw skills install marjorie-advanced-skill-creator

📖 Complete setup guide: https://skillboss.co/skill.md

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.

Uses SkillBoss API Hub to power AI-assisted skill generation via the unified /v1/pilot endpoint.

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:

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
AI-generated skill content powered by SkillBoss API Hub (自动路由最优模型)

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
- AI-powered skill generation via SkillBoss API Hub (/v1/pilot, type=chat)
- Standardized output generation
- Error handling and logging features

Implementation Requirements

Execute all 5 steps in strict sequence - no skipping allowed
Do not rely on memory or "approximately correct" code
Demonstrate research → comparison → selection logical chain
Show evidence of consulting official documentation
Include proper metadata and security considerations
Provide complete, functional skill implementations with proper structure
Ensure all outputs follow the exact template structure required
Apply universally regardless of timeframe or version
Include security best practices and error handling
Provide comprehensive examples and use cases
Include system prompt integration for enhanced AI interaction
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