Content
80%Weight 40%Scale 1-5Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
The body is a concise, well-structured instruction set with strong progressive disclosure for a simple skill, but its workflow lacks explicit validation checkpoints and its actionability has minor gaps where generic source guidance could name specific tools.
Suggestions
Add an explicit verification step (e.g., before returning results, confirm every observation has a source URL and that estimates are labeled as inferred, re-checking if not) to introduce a validation feedback loop.
Replace "Use official transparency libraries" with named sources such as Google Ads Transparency and Meta Ad Library, ideally with their access URLs, to match the specificity of the description.
Optionally include a short output schema or example evidence record so the "Return evidence-backed opportunities, risks, experiments, and source records" step is copy-paste ready.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is a lean six-step checklist plus a short guardrail paragraph; it assumes Claude's competence and avoids explaining concepts Claude already knows. | 5 / 5 |
Actionability | Each step specifies concrete data fields to capture (e.g., "capture date, platform, placement, observable creative/message, landing destination, and source URL"), but "Use official transparency libraries" is generic compared to the named platforms in the description and lacks concrete tool/URL examples. | 4 / 5 |
Workflow Clarity | A clear six-step sequence is present, but there are no explicit validation or verification checkpoints and no fix-and-retry feedback loop for this batch data-collection operation. | 3 / 5 |
Progressive Disclosure | The skill is under 50 lines, self-contained with no external references needed, and well-organized via a numbered list plus a guardrail section. | 5 / 5 |
Total | 17 / 20 Passed |