Content
92%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
A highly actionable, well-sequenced skill body with strong validation checkpoints. Its main weaknesses are mild redundancy in restating source-preference ordering and on-demand references that point to files absent from the bundle.
Suggestions
Consolidate the source-preference ordering into one place (e.g. the Fallback cascade) and have each section reference it, rather than repeating the DataForSEO > Moz > Bing > Common Crawl ordering inline.
Either bundle the referenced `backlink-quality.md` and `free-backlink-sources.md` under ./references/ or correct the paths so the on-demand links resolve within the skill bundle.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is mostly efficient and free of concept-explanation fluff, but the per-section source-preference ordering is restated a third time in the "Fallback cascade" section, so it could be tightened. | 2 / 3 |
Actionability | Provides copy-paste-ready commands (e.g. `claude-seo run moz_api.py metrics <url> --json`), named DataForSEO tools, and concrete scoring thresholds in tables — fully executable guidance. | 3 / 3 |
Workflow Clarity | The 7-section sequence is clearly ordered with explicit validation checkpoints: the data-sufficiency gate and the MANDATORY pre-delivery review checklist ("If ANY check fails, fix the finding before presenting") provide real feedback loops. | 3 / 3 |
Progressive Disclosure | References are well-signaled and one-level deep ("Load on demand (do NOT load at startup)"), but the referenced files (`skills/seo/references/backlink-quality.md`, `free-backlink-sources.md`) are not present in this skill's bundle, weakening navigation. | 2 / 3 |
Total | 10 / 12 Passed |