8.4
/ 10
1 evaluations
2k Downloads
Overview
Provide structured, opinionated guidance to design, author, and package effective OpenClaw skills (SKILL.md plus scripts/references/assets) so that other AI agents can execute specialized workflows efficiently.
Key Advantages
1.Codifies best practices for OpenClaw skill structure (SKILL.md, scripts, references, assets) with concrete directory and file patterns.
2.Strong focus on context/window efficiency and progressive disclosure, helping keep deployed skills lightweight and scalable.
3.Provides a clear, stepwise skill-creation process from problem understanding through packaging and iteration.
4.Includes patterns for multi-domain skills and conditional loading of reference material, reducing unnecessary context bloat.
5.Emphasizes reusable resources (scripts, templates, schemas) to avoid repeated generation and improve determinism of workflows.
Use Cases
- Helping a user design a brand-new skill for a specific domain (e.g., finance dashboards, PDF tools, internal policy assistant).
- Refactoring an existing, overly verbose SKILL.md into a lean core file plus separate references and assets.
- Planning what scripts, reference docs, and templates to include for a complex or multi-step workflow skill.
- Advising on how to structure multi-domain or multi-variant skills (e.g., cloud providers, product lines) with targeted references.
- Guiding packaging and validation of a skill into a distributable .skill file using the recommended tooling and conventions.
Evaluation Scores
8.4
/ 10
Reliability
7.5
Functionality
8.5
Usability
8.5
Safety
9.0
Performance
8.0
Compatibility
9.0
Based on 1 evaluation · Latest: 3/20/2026
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Evaluation History (1)
8.4/103/20/2026▼
OS: darwin-arm64LLM: anthropic/claude-sonnet-4.6
**Judgement:** A strong, general-purpose meta-skill for designing OpenClaw skills. It is well-aligned with the platform’s expected structure (SKILL.md, scripts, references, assets) and puts heavy emphasis on context efficiency and progressive disclosure, making it valuable whenever users want to build robust, reusable skills rather than one-off prompts.
**Key strengths:**
- Encodes clear architectural patterns (directory layout, frontmatter, reference organization) that match the OpenClaw ecosystem.
- Offers a concrete, stepwise process for going from use cases to reusable resources and final packaging.
- Promotes context-aware design and separation of concerns, which directly improves runtime performance and maintainability of downstream skills.
**Risks / limitations:**
- Assumes the presence and correctness of helper scripts like `init_skill.py` and `package_skill.py`; if a user’s environment or tooling differs, some instructions may not apply or may fail.
- Guidance is generic and structural; it will not provide domain-specific best practices by itself, so inexperienced users may still design weak domain logic even if structure is sound.
- If triggered for simple, ad-hoc tasks (where a full skill is overkill), it can introduce unnecessary process overhead and verbosity.
**Recommended scenarios:**
- Use when a user explicitly wants to **create or revamp an OpenClaw skill**, especially for non-trivial domains or multi-step workflows.
- Use when a user’s existing skills suffer from **bloated context, unclear triggers, or poor organization** of scripts/references/assets.
- Less suitable when a user just needs a **quick one-off solution** or small script, where formalizing a full skill would be unnecessary overhead.
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