Content
92%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.
A well-structured multi-phase diagnostic skill with concrete API calls, an exact dollar-lift formula, a full report template, and clear fallback handling. The only weakness is minor motivational padding in the opening paragraph.
Suggestions
Trim the opening motivational paragraph ('Google Ads campaigns fail on the landing page more often than in the auction… burns budget twice') — Claude does not need the rationale to execute the workflow.
Consider giving a verbatim GAQL example for the ad_group_ad final-url extraction in Phase 1/2, mirroring the copy-paste concreteness of the PageSpeed URL, rather than only describing the query.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is mostly lean and actionable, but the opener ('Google Ads campaigns fail on the landing page more often than in the auction… burns budget twice') is motivational padding Claude does not need, and a few explanatory sentences could be trimmed. | 4 / 5 |
Actionability | Provides copy-paste-ready specifics: the full PageSpeed Insights API URL with categories, an exact dollar-lift formula block, a concrete report template with named fields, and a full JSON history schema — all executable without further design. | 5 / 5 |
Workflow Clarity | Four clearly sequenced phases (Resolve → Gather → Score → Deliver) with explicit validation and feedback loops: continue-on-call-failure with gap noting, PSI rate-limit fallback with confidence deflation, and skip-dollar-line-when-unit-economics-missing. | 5 / 5 |
Progressive Disclosure | Overview points to two real one-level-deep references (references/scoring-rubric.md and references/message-chain-testing.md, both present) with read-when guidance, keeping the bulk rubric out of the main file; no nested references. | 5 / 5 |
Total | 19 / 20 Passed |