功能描述

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.

使用说明 (SKILL.md)

Advanced Skill Creator

Name: advanced-skill-creator
Author: xqicxx

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:

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

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

安全使用建议

Do not run or grant this skill elevated or automated execution rights without manual review. Steps to take before installing: - Open and read scripts/advanced_skill_processor.py line-by-line. Look for network requests, subprocess.exec/ Popen usage, file reads (e.g., ~/.ssh, /etc), or any code that posts data to external hosts. - Verify why the SKILL.md lists python3/bash as required while the registry metadata shows none — ask the publisher to explain the mismatch and provide a homepage or source repo. - Remove or sanitize any prompt-injection-like language in SKILL.md (e.g., 'you-are-now' style directives) and require the author to justify any coercive instructions. - If you must test, run the script in an isolated sandbox or VM without secrets and monitor outbound network traffic. - Prefer a policy that prevents autonomous model invocation for this skill until the behavior of the included script is positively audited; consider setting disableModelInvocation:true for safer deployment. - Ask the publisher for a verifiable homepage or source repository and for evidence that the script does not exfiltrate data. If they cannot provide this, treat the package as untrusted code.

功能分析

Type: OpenClaw Skill Name: advanced-skill-creator Version: 1.0.0 This skill is classified as suspicious due to a clear prompt injection attempt in `SKILL.md` that aims to re-program the agent's persona and decision-making process. Additionally, `SKILL.md` instructs the agent to perform broad network access to external, untrusted sources (e.g., ClawHub, GitHub for 'best practices' and 'security considerations') and potentially local file access, which are high-risk capabilities. While the accompanying Python script (`scripts/advanced_skill_processor.py`) only simulates these actions, the `SKILL.md` serves as direct instructions to the AI agent, making these behaviors a concern.

能力评估

ℹ Purpose & Capability

The declared purpose — a helper for creating/modifying OpenClaw/Moltbot/ClawDBot skills — reasonably explains needing documentation lookups, community research, and a script to assist. However the registry metadata provided to the catalog says 'no required binaries' while the SKILL.md YAML claims it requires python3 and bash (anyBins: ["python3","python"]). That inconsistency increases risk because the SKILL.md implies executable code will be run but the registry entry does not advertise that.

⚠ Instruction Scope

SKILL.md prescribes broad external research (docs, ClawHub, GitHub, web content) and enforces a strict output template. The file also contains a detected prompt-injection pattern (e.g. 'you-are-now'), which indicates the skill may include text intended to coerce the agent's behavior. The instructions demand producing full file contents and complete skill implementations — if executed automatically, that could cause the agent to fetch and re-publish external content without supervision. The instruction set is broader than a simple formatter and gives the agent substantial discretion to fetch, synthesize and output external data.

ℹ Install Mechanism

There is no install specification (no network download/install steps), which lowers supply-chain risk. However the package includes a non-trivial script (scripts/advanced_skill_processor.py) that looks intended to be executed. Because there is no controlled install step, executing that included code would run arbitrary local Python code from the package — review of that file is required before running.

✓ Credentials

No environment variables, credentials, or config paths are required by the registry metadata. The SKILL.md metadata only lists required binaries (python3, bash) and sets primaryEnv to null. There are no explicit requests for unrelated secrets in the manifest. Still, included script execution could access local environment or network at runtime — confirm script behavior before granting execution.

✓ Persistence & Privilege

The skill does not set always:true and does not declare special privileges. Model invocation is not disabled by the manifest, so the skill could be callable by the agent per normal rules. This is typical, but combined with a supplied executable script and the prompt-injection patterns, it increases the need for manual review and possibly disabling autonomous invocation until validated.

版本历史

v1.0.0

- Initial release of advanced-skill-creator. - Automates and enforces the official 5-step research flow for OpenClaw/Moltbot/ClawDBot skill creation and modification. - Ensures strict adherence to best practices, comprehensive analysis, and official documentation. - Provides standardized output structure with proper YAML frontmatter, metadata, and security considerations. - Integrates community-approved methodologies and thorough example use cases. - Implements advanced system prompt integration for enhanced AI-driven skill development.

元数据

Slug advanced-skill-creator

版本 1.0.0

许可证 —

累计安装 17

当前安装数 17

历史版本数 1

常见问题