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Install in OpenClaw
/install xiaobai-skill-quality-eval
Description
Skill Quality Evaluator - Score any skill on 6 dimensions. Catch 30% of skills that look good but fail silently. Based on Tessl Research 2026 findings.
Usage Guidance
This is an instruction-only evaluator and appears coherent with its purpose. Before installing: confirm the agent has only intended read access to the skills/ directory and that writing evaluation files to memory/evaluations/ is acceptable for your privacy/policy needs. Run it first on a small, non-sensitive set of skills to verify outputs and ensure reports don't accidentally record secrets from evaluated SKILL.md files. If you rely on automated batch runs, consider restricting which directories it can read and where it can write reports.
Capability Analysis
Type: OpenClaw Skill
Name: xiaobai-skill-quality-eval
Version: 1.0.0
The skill bundle consists of a metadata file and a markdown-based instruction set (SKILL.md) designed to guide an AI agent in evaluating the quality of other skills. It defines a structured framework for scoring skills across six dimensions (e.g., reliability, clarity, and leakage) and provides templates for reporting. There is no executable code, no network activity, and no evidence of malicious intent or prompt injection aimed at compromising the agent or environment.
Capability Assessment
Purpose & Capability
The skill's name/description (skill-quality-eval) matches the runtime instructions: read a skill's SKILL.md, evaluate on six dimensions, and generate/save a report. There are no unrelated requirements (no binaries, env vars, or installs) that would be disproportionate to the stated purpose.
Instruction Scope
SKILL.md instructs the agent to read SKILL.md files, evaluate them, and save reports (e.g., memory/evaluations/*.md). This is appropriate for an evaluator, but it assumes the agent has read access to the skills/ directory and write access to its memory or filesystem. If those paths include sensitive files or skills, the operator should verify permissions and review produced reports before persistent storage.
Install Mechanism
No install spec and no code files — instruction-only skill. This minimizes risk (nothing is written to disk or executed beyond the agent following textual instructions).
Credentials
The skill requests no environment variables, credentials, or config paths. All declared capabilities are achievable without additional secrets; therefore requested environment access is proportionate.
Persistence & Privilege
always is false and the skill does not request elevated/system-wide persistence. It does instruct saving evaluations to memory/evaluations/, which is a reasonable local persistence need for an evaluator. Operators should confirm the agent's memory/storage policy (what is stored, who can read it) before allowing persistent saves.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install xiaobai-skill-quality-eval - After installation, invoke the skill by name or use
/xiaobai-skill-quality-eval - Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
Initial release: 6-dimension skill evaluation framework
Metadata
Frequently Asked Questions
What is Skill Quality Evaluator?
Skill Quality Evaluator - Score any skill on 6 dimensions. Catch 30% of skills that look good but fail silently. Based on Tessl Research 2026 findings. It is an AI Agent Skill for Claude Code / OpenClaw, with 108 downloads so far.
How do I install Skill Quality Evaluator?
Run "/install xiaobai-skill-quality-eval" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is Skill Quality Evaluator free?
Yes, Skill Quality Evaluator is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does Skill Quality Evaluator support?
Skill Quality Evaluator is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created Skill Quality Evaluator?
It is built and maintained by Erwin (@aptratcn); the current version is v1.0.0.
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