ai-content

Use when auditing metadata, crawlability, structured data, or indexability related to Audit and refine AI-generated content. Verify the rendered HTML and HTTP response rather than relying only on source files.

Quality

58%

Does it follow best practices?

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

Quality

Content

57%Weight 40%Scale 1-5

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

The body is compact and correctly pushes implementation detail to a real, well-signaled reference file, but the in-body guidance itself is vague — it tells Claude to review and rewrite without concrete signals to check, examples, or validation steps.

Suggestions

Make the "Check" section concrete: list specific signals to look for (missing bylines or fact-check dates, no original data or first-hand experience, generic phrasing indistinguishable from top-ranking rewrites) instead of one abstract criterion.

Add a validation step after "Fix", e.g. re-check the rewritten sections against the checklist and verify the rendered page (per the description's rendered-HTML emphasis) before considering the rule passed.

Drop or tighten the generic "Explain" section and the background opening sentence to free tokens for the concrete checklist items.

Dimension	Reasoning	Score
Conciseness	The 44-line body is lean and well-sectioned, but the opening sentence about search engines prioritizing people-first content and the generic "Explain" section are minor explanations Claude does not need and could be trimmed.	4 / 5
Actionability	Guidance is high-level throughout — "Review the content to see if it provides unique value beyond what AI models can generate by default" and "Rewrite AI-generated sections to include original research, personal experiences, and a unique brand voice" give direction without concrete checklist items, signals, commands, or examples.	2 / 5
Workflow Clarity	A rough Check → Fix → Explain sequence is present, but steps are thin and no validation checkpoints exist for confirming the rewrite actually improved quality or that the rendered output is correct.	3 / 5
Progressive Disclosure	The short overview body keeps detail appropriately split into references/rule.md, which exists, is clearly signaled ("For full implementation details, code examples, and framework-specific guidance, see references/rule.md"), and is only one level deep with no nested references.	5 / 5
	Total	14 / 20 Passed

Description

58%Weight 40%Scale 1-5

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

The description includes an explicit "Use when..." trigger and some concrete actions, but its central sentence is grammatically garbled and its trigger terms (crawlability, structured data, indexability) misalign with the skill's actual AI-content-quality focus, weakening both clarity and distinctiveness.

Suggestions

Rewrite as a clean two-part sentence: a third-person statement of what the skill does ("Audits and refines AI-generated content for accuracy, unique value, and human voice") followed by an explicit 'Use when' clause ("Use when the user mentions AI-generated content, unedited AI output, or content originality/quality checks").

Replace or prune the misaligned trigger terms (metadata, crawlability, structured data, indexability) so the description triggers on AI-content tasks rather than generic technical-SEO audits, reducing conflict with other SEO skills.

Add natural synonyms users would say, such as "AI content quality", "SEO content review", or "humanize AI text", to improve trigger-term coverage.

Dimension	Reasoning	Score
Specificity	Names several audit areas ("metadata, crawlability, structured data, or indexability") plus one concrete action ("Verify the rendered HTML and HTTP response"), but the core capability clause "related to Audit and refine AI-generated content" is grammatically broken, so action coverage is present yet muddled rather than comprehensive.	3 / 5
Completeness	Both what ("Audit and refine AI-generated content", "Verify the rendered HTML and HTTP response") and when ("Use when auditing metadata, crawlability...") are present, but the what is awkwardly embedded in a broken clause, so it could be more clearly and explicitly stated.	4 / 5
Trigger Term Quality	Some relevant keywords appear ("AI-generated content", "structured data", "rendered HTML"), but common natural phrases users would actually say (e.g. "SEO audit", "AI content quality", "human review of AI text") are missing, and the trigger list leans toward crawlability jargon.	3 / 5
Distinctiveness Conflict Risk	"AI-generated content" is a distinctive niche, but the trigger terms "metadata, crawlability, structured data, indexability" overlap heavily with generic SEO-audit skills, creating genuine mis-trigger risk.	3 / 5
	Total	13 / 20 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
metadata_version	'metadata.version' is missing	Warning

	Total	15 / 16 Passed

Repository: thedaviddias/Front-End-Checklist
Path: skills/ai-content/SKILL.md
Commit: 7bfd868

Reviewed: 1 day ago

Table of Contents

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