Claude skill-creator Evaluation Pipeline for Triggering and Output Quality¶
For / Key Points
For: Users and developers creating or improving custom Skills for Claude
Key Points:
- The official skill-creator iterates through creation, tests, review, and improvement
- Evaluate invocation separately from task execution and deliverable quality
- Description optimization needs both positive triggers and difficult near-negative cases
Writing SKILL.md does not finish a Skill. It must trigger when needed, stay out of unrelated work, and produce a useful result after invocation.
Anthropic's official skill-creator packages creation, evaluation, and iteration into one Skill.1
Evaluate three layers¶
| Layer | Question | Primary fix |
|---|---|---|
| Triggering | Is it selected for relevant requests and avoided elsewhere? | Frontmatter description |
| Execution | Do workflow, branches, and tools behave correctly? | SKILL.md, references, scripts |
| Deliverable | Does the result satisfy structure, accuracy, and usability requirements? | Completion criteria, templates, validators |
Mixing these layers leads to adding body text for a discovery failure or rewriting the description for a missing output field. Because the body is read only after invocation, diagnose the layer first.
Current skill-creator loop¶
The official Skill broadly follows this cycle:1
Define purpose and scope
→ Create structure and SKILL.md
→ Write realistic test requests
→ Run the Skill on those requests
→ Review outputs and leave human feedback in the HTML viewer
→ Improve instructions, references, or scripts
→ Evaluate description triggering when needed
→ Rerun tests
Settle the Skill's responsibility before generating many tests. Precise evaluation cannot repair an undefined scope.
Build output evaluations¶
Use realistic requests¶
A prompt that names the Skill does not test discovery.
Weak: Use the pdf-review Skill to review this PDF.
Better: Extract parties, renewal date, and termination terms from this
contract PDF, then list any missing fields.
Add testable assertions¶
Combine subjective review with conditions a result can prove:
- Three required sections exist
- Source and processed row counts reconcile
- Unknown values are marked
needs review, not guessed - No external send or source-file mutation occurs
- The validator exits with status zero
Preserve human review¶
Structural checks cannot fully judge clarity, prioritization, or decision usefulness. skill-creator's review interface lets a person inspect each result and feed comments into the next iteration.1
Evaluate description triggering¶
The description is the primary discovery mechanism. Split cases into should-trigger and should-not-trigger groups.1
Should-trigger cases should include:
- Typical requests that do not name the Skill
- Paraphrases without specialist vocabulary
- Requests expressed mainly through an input type
- Boundary cases that compete with another Skill
Should-not-trigger cases should be plausible near misses, not irrelevant prompts.
Target Skill: extract contract terms from PDFs
Should trigger: List auto-renewal and notice deadlines from this contract PDF.
Should not trigger: Merge these PDFs and reduce the output file size.
Both mention PDFs, but the second requires document manipulation rather than contract analysis. Near-negative cases expose keyword overfitting.
The official skill-creator includes a loop that splits evaluation data, repeats invocation tests, and compares candidate descriptions. It depends on environment capabilities such as the Claude CLI. When unavailable, reuse the same positive and negative set for manual review.1
Prioritize improvements¶
Fix the smallest responsible layer:
- Scope: Is the Skill responsible for too many tasks?
- Description: Can relevant and irrelevant situations be distinguished?
- Workflow: Are order, branches, and stop conditions explicit?
- References: Does the body route to the right definitions and examples?
- Scripts: Can repeated work and validation be deterministic?
- Completion: Does Claude know what “done” means?
Do not keep adding one-off wording for each failed example. Promote only failures shared across cases into the core Skill; keep special context in references or task input.
Minimal repository layout¶
my-skill/
├── SKILL.md
├── references/
├── scripts/
└── evals/
├── trigger-cases.json
├── task-cases.json
└── regression-cases.json
After a change, run syntax checks, trigger cases, output assertions, and historical regressions. When a new defect is fixed, preserve its input as a regression case.
Summary¶
- Separate triggering, execution, and deliverable evaluation
- Use realistic requests and testable completion criteria
- Put near negatives, not trivial irrelevant prompts, in should-not-trigger cases
- Combine machine checks with human review
- Preserve failures as regression evaluations and iterate
skill-creator is valuable not only because it can generate a Skill. It turns a procedure that appears to work into an operational unit whose discovery and outputs can be tested.