Content
75%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 highly actionable, well-sourced reference with executable commands, explicit scoring weights, and honest scoping caveats. Its weaknesses are verbosity — duplicated E-E-A-T checklists and scattered dated Google-update notes that belong in a consolidated changelog section — and an audit workflow that is implied by checkpoints rather than laid out as an explicit sequence.
Suggestions
Consolidate time-sensitive version/date notes (QRG versions, core-update dates, AI Mode model versions) into a single 'Google update ledger' or 'Old patterns' section so stale details don't pad the mainline guidance.
Trim the inline E-E-A-T sub-bullets that duplicate eeat-framework.md, keeping only the trust-weighted summary and the pointer to the reference file.
Add a short numbered audit workflow (fetch page -> Who/How/Why test -> E-E-A-T scoring -> content metrics -> AI citation readiness -> output report) so the sequence is explicit rather than implied by section order.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is mostly efficient reference material, but it includes unnecessary content: the inline E-E-A-T sub-bullets ("Contact information, physical address", "Privacy policy, terms of service") duplicate criteria already delegated to eeat-framework.md, and time-sensitive dates (March 2024, Sept 2025 QRG, 2026-05-15, Gemini 3.5 Flash 2026-05-19, changelog 2025-12-09) are scattered throughout rather than confined to an old-patterns/deprecated section, which the guidelines penalize. It is above 2 because there is no concept-teaching padding and most sections earn their tokens. | 3 / 5 |
Actionability | Guidance is fully executable: copy-paste-ready commands ("${CLAUDE_PLUGIN_ROOT}/scripts/claude-seo" run content_humanize.py draft.md -o cleaned.md; seo_updates.py --since <yyyy-mm> --json), named output fields (invisible_removed, changes, freshness.stale), numeric thresholds (word-count floors, Flesch 60-70, keyword density 1-3%), explicit E-E-A-T weights (20/25/25/30), named DataForSEO MCP tools, and a concrete error-handling table. It matches the 5 anchor because the common cases are covered with specific commands and numbers. | 5 / 5 |
Workflow Clarity | There is no single numbered end-to-end procedure, but sequencing and checkpoints are present: "Before scoring E-E-A-T sub-factors, every page audit should pass Google's own three-question heuristic", "Before attributing a traffic or ranking change... list the confirmed Google updates" (a validate-before-concluding loop), freshness staleness flagging, an error-handling table, and a defined output format. This is not a destructive/batch skill, so the workflow cap-3 rule does not apply; it falls short of 5 because the overall audit sequence is implied by section order rather than explicit. | 4 / 5 |
Progressive Disclosure | References are one level deep and clearly signaled ("Read ${CLAUDE_PLUGIN_ROOT}/skills/seo/references/eeat-framework.md for full criteria and ... eeat-scoring-guide.md for score bands"), with inline script usage and a cross-reference to the seo-geo skill; no bundle directories were provided alongside SKILL.md to verify further. Minor gaps keep it at 4: the inline E-E-A-T bullet lists duplicate the referenced framework file, and the google-ai-optimization-guide.md reference is buried mid-paragraph rather than clearly signaled. | 4 / 5 |
Total | 16 / 20 Passed |