Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
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.
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.
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Then review README.md for any prerequisites, environment setup, or post-install checks. Tell me what you changed and call out any manual steps you could not complete.
I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Then review README.md for any prerequisites, environment setup, or post-install checks. Summarize what changed and any follow-up checks I should run.
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 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
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)
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
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)
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
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
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
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
GitHub popular OpenClaw skill project structures Community-recommended security practices (input validation, error handling) Optimal metadata configuration methods Effective trigger word definition patterns
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
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
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."
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
Code helpers, APIs, CLIs, browser automation, testing, and developer operations.
Largest current source with strong distribution and engagement signals.