seo-content

Content quality and E-E-A-T analysis with AI citation readiness assessment. Use when user says "content quality", "E-E-A-T", "content analysis", "readability check", "thin content", or "content audit".

Quality

66%

Does it follow best practices?

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Securityby

Low

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tessl review fix ./skills/seo-content/SKILL.md

Quality

Content

50%

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

A substantive, reasonably organized audit reference with concrete thresholds and good error handling, but it is verbose in places, lacks an explicit sequenced audit workflow with validation checkpoints, and presents a near-monolithic body with external-only references and a skeletal output template.

Suggestions

Add an explicit ordered audit procedure (e.g., 1. fetch URL, 2. confirm retrievable content / handle error table, 3. run Who/How/Why, 4. score E-E-A-T, 5. metrics, 6. AI-citation readiness, 7. produce report) with a validation checkpoint before scoring.

Flesh out the Output section — replace 'XX/100' placeholders and empty 'Issues Found'/'Recommendations' headers with the expected fields/format so reports are reproducible.

Move the detailed E-E-A-T sub-factor signal lists and Google-update-history blockquotes into a references/ file within this skill's bundle (with a signaled one-level link) to tighten the main body, since the referenced eeat-framework.md path currently lives outside the skill.

Dimension	Reasoning	Score
Conciseness	The body is mostly efficient structured guidance, but several blockquotes recount Google update history and caveats (Helpful Content System merger, Gen-AI optimization, 'honest scoping') and restate E-E-A-T sub-factor lists that pad the token budget beyond what Claude needs; not the level below because the tables and thresholds do earn their place.	2 / 3
Actionability	Concrete thresholds and tool names are present (word-count minimums by page type, Flesch 60-70, density 1-3%, 3-5 internal links/1000 words, named DataForSEO MCP functions, error-handling table), but the Output section is skeletal — 'XX/100' placeholders and empty 'Issues Found'/'Recommendations' headers with no guidance — leaving key details missing.	2 / 3
Workflow Clarity	The sections imply an audit order (Who/How/Why → E-E-A-T → metrics → AI → freshness → output) and the error-handling table gives recovery actions, but there is no explicit step-by-step audit sequence or validation checkpoint (e.g., confirm retrievable content before scoring), so checkpoints are implicit.	2 / 3
Progressive Disclosure	Sections are clearly headed and a couple of one-level references are signaled ('Read skills/seo/references/eeat-framework.md for full criteria'), but no bundle files exist in this skill's references/scripts/assets directories, the referenced paths point into sibling skills, and most detail (metric tables, AI-citation strategies) is inline in a ~200-line monolith rather than split out.	2 / 3
	Total	8 / 12 Passed

Description

82%

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

A well-constructed description with an explicit 'Use when' trigger clause and natural, well-chosen trigger terms. It loses points only on action specificity (abstract analysis verbs) and a moderate overlap risk with sibling SEO skills.

Dimension	Reasoning	Score
Specificity	Names the domain and several named analysis actions ('Content quality and E-E-A-T analysis with AI citation readiness assessment'), but the actions are abstract analysis/assessment verbs rather than concrete distinct operations like the score-3 anchor (extract, fill, merge), so it sits at the 'names domain and some actions' level.	2 / 3
Completeness	It explicitly answers both what ('Content quality and E-E-A-T analysis with AI citation readiness assessment') and when ('Use when user says...') with an explicit trigger clause, matching the score-3 anchor; it is not the level below because the 'when' is explicit, not implied.	3 / 3
Trigger Term Quality	The 'Use when user says' clause gives good coverage of natural terms a user would actually say — 'content quality', 'E-E-A-T', 'content analysis', 'readability check', 'thin content', 'content audit' — matching the score-3 anchor for natural keyword coverage.	3 / 3
Distinctiveness Conflict Risk	The E-E-A-T / AI-citation framing is a recognizable niche, but triggers like 'content analysis' and 'readability check' are broad and the body cross-references a sibling seo-geo skill covering the same AI-citation territory, so it could still overlap with similar skills rather than being unambiguously distinct.	2 / 3
	Total	10 / 12 Passed

Validation

93%

Warnings & errors only

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 15 / 16 Passed

Validation for skill structure

Criteria	Description	Result
frontmatter_unknown_keys	Unknown frontmatter key(s) found; consider removing or moving to metadata	Warning

	Total	15 / 16 Passed

Repository: AgriciDaniel/claude-seo
Path: skills/seo-content/SKILL.md
Commit: 09d37c7

Reviewed: 4 days ago

Table of Contents

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