Review a skill against best practices
How to review and optimize skills to ensure they follow best practices
Skills provide procedural knowledge and specific workflows that agents load when relevant. This guide explains how to run skill reviews against best practices and on the next page we'll talk about how to use the automated optimize option to address issues before deploying the skill to your team.
TL;DR
Compare your skill against best practices. For example:
Examine the description in the skill, determine if the wording is effective, and how that affects activation.
Why review skills?
Skills encode team knowledge and workflows. Skill reviews help you:
Assess if skills conform to the skills standard
Validate skill content quality (how likely skill is to help) before deploying to your team
Validate skill description quality (how likely skill is to activate) before deploying to your team
Viewing skill reviews
In the Tessl Registry, skill reviews show multiple scores.
Example: React development skill review
Review Score: Overall quality assessment (0-100%)
Weighted average of the three sub components below
Validation Checks: Validates that skill follows the criteria at https://agentskills.io/specification
Checks covering line count, frontmatter, schema, license and metadata
Pass/warning/fail deterministic grading
Implementation Score: LLM-as-a-judge review of the SKILL.md body, graded on:
Conciseness
Actionability
Workflow clarity
Progressive disclosure
Activation Score: LLM-as-a-judge review of the description, assessing how likely agents are to use the skill, graded on:
Specificity
Completeness
Trigger Term Quality
Distinctiveness Conflict Risk
Each skill review includes detailed validation results showing what passed, what needs improvement, and specific recommendations.
What scores mean:
90%+ Review Score: Skill conforms well to best practices
70-89% Review Score: Good skill, may have minor improvements needed
Below 70%: Likely needs work before deployment
Use these scores to choose quality skills and identify what to fix in your own skills before publishing.
Automatic review on publish
When you publish a skill to the registry using tessl skill publish, skill reviews run automatically:
What happens automatically:
Skill is linted for format and structure
Skill review is performed
Review scores are calculated and displayed in the registry
Reviewing skills locally
Before publishing skills, validate them locally:
Fix any issues locally, then publish. The registry will show updated review scores. For fixing issues with skill reviews, use the optimise flag.
Here's a sample output of tessl skill review in the CLI:
Next steps
Optimize a skill using best practices - Automate fixing issues in your skill
Evaluate skill quality using scenarios - Evaluate skill effect on agent performance
Evaluating documentation - Measure documentation effectiveness
Distributing via registry for publishing skills.
Creating skills - Write better skills
Publishing skills - Share reviewed skills
Related resources
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