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 Registryarrow-up-right, skill reviews show multiple scores.

Example: React development skill reviewarrow-up-right

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/specificationarrow-up-right

  • 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

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