Using skills
How to evaluate an AI skill before relying on it
Use a realistic test, inspect the evidence, and distinguish a strong workflow from strong marketing.
Quick answer
Check the stated output and prerequisites, then test the skill on a small task whose quality you can judge. Look for explicit decision rules, useful questions, and clear limits. A review badge, large catalog, or convincing demo should not replace inspection of the workflow and its result.
Match the skill to your actual task
Read the listing for the intended user, required inputs, external tools, and concrete deliverable. If you need a draft email, a broad marketing strategy workflow may be the wrong fit. Make a short list of the constraints that matter to your situation before comparing options.
Use a test with a known difficulty
Give the AI an ordinary case plus one issue you expect it to notice. For example, ask a reply-writing workflow to handle a request where an important policy detail is missing. A useful result should identify the omission instead of inventing a policy that makes the reply easy.
Score the output against a simple rubric
Use the same rubric for each candidate. Save the input and result so you can compare the method fairly. This is your evaluation of a particular task; do not present the score as a general success rate for all users.
| Check | Evidence to look for |
|---|---|
| Grounding | Important claims point to supplied facts |
| Method | The response reflects the selected workflow |
| Completeness | The promised deliverable is present |
| Uncertainty | Missing or conflicting facts are explicit |
| Permission | Consequential actions wait for approval |
Decide what would justify wider use
Begin with drafts or read-only work. If the workflow consistently helps with your representative cases, consider a broader test with the relevant human reviewer. If it requires tools, confirm the tool access separately. Loading instructions does not prove that every dependency is connected.
When something fails, record the exact skill title and the problem with the input or output. Specific feedback helps a creator improve a version. Avoid blaming an unavailable external tool on the instruction text, or treating a good instruction load as evidence that an outside action happened.
Common questions
Should I trust an impressive demo?
Use it to understand the intended output, then test your own representative case. A demonstration is not a measured success rate.
Can I compare two skills fairly?
Use the same inputs and review rubric, and note differences in required tools. Compare the resulting work and the questions each workflow asks.
Does verification replace evaluation?
No. Creator identity, security review, and usefulness for your specific task are different questions.
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