keyword-stuffing

Use when auditing content pages for over-optimisation, reviewing AI-generated content that may repeat target phrases excessively, or checking meta tags and alt text for unnatural keyword accumulation.

Quality

61%

Does it follow best practices?

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Securityby

Low

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tessl review fix ./skills/keyword-stuffing/SKILL.md

Quality

Content

61%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 well-structured and actionable with a genuine one-level reference, but it is held back by redundant density-threshold restatements, a conceptual Explain section, and a missing post-fix validation checkpoint in the audit workflow.

Suggestions

Collapse the repeated 2–3% density threshold into a single statement and remove the Explain section's general Panda/SpamBrain background that Claude already knows.

Add an explicit validation step after Fix (e.g., 'Re-run the Code Review density check to confirm flagged terms now fall below 3%') to close the audit feedback loop.

Move the references/rule.md pointer earlier (e.g., directly under the intro) and slim the inline Check/Fix detail that the reference already covers, so the body reads as a true overview.

Dimension	Reasoning	Score
Conciseness	The Check and Fix sections are lean and actionable, but the Explain section restates Panda/SpamBrain background Claude already knows and the 2–3% density threshold is repeated across Quick Reference, Check, and Explain, adding padding that could be trimmed.	3 / 5
Actionability	Concrete flagging criteria (density >3%, >3× in title, comma-separated alt-text lists, hidden-text patterns) and specific remediation steps (Flesch Reading Ease, DevTools computed styles) give mostly executable guidance, though the Code Review section describes the procedure in prose rather than runnable code.	4 / 5
Workflow Clarity	A rough Check → Fix → Code Review sequence exists, but there is no explicit validation/feedback loop (e.g., re-run the density check after fixing to confirm it dropped below threshold), and the audit/batch nature of the task makes that checkpoint gap material.	3 / 5
Progressive Disclosure	The body is organized into clear sections and points to a real one-level-deep reference (references/rule.md, which exists and holds the code examples), but the body still duplicates some detail found in the reference and the pointer is placed at the very end rather than clearly signposted up front.	4 / 5
	Total	14 / 20 Passed

Description

61%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 is specific to a distinct SEO niche and carries strong, natural trigger phrases, but it is framed entirely as a 'Use when' clause with no explicit statement of what the skill does, capping completeness and specificity.

Suggestions

Lead with an explicit capability statement (e.g., 'Detects and flags keyword stuffing in page content, titles, meta tags, and alt text.') before the 'Use when' clause so 'what' is answered explicitly.

Add 'keyword stuffing' and 'keyword density' as natural trigger terms inside the description, not only in the skill name.

Tighten the three trigger scenarios so each maps to a distinct concrete capability (detect, review, check) rather than overlapping phrasings.

Dimension	Reasoning	Score
Specificity	Names the SEO/keyword-stuffing domain and several concrete actions ('auditing content pages for over-optimisation', 'reviewing AI-generated content', 'checking meta tags and alt text'), but these are embedded in a when-clause rather than stated as explicit capabilities, leaving coverage implicit.	3 / 5
Completeness	It has an explicit, strong 'when' ('Use when auditing... reviewing... or checking...') but no standalone 'what' statement — the capability is only implicit inside the trigger clause, so it falls short of the anchor that requires both an explicit what and when.	3 / 5
Trigger Term Quality	Good coverage of natural terms a user would say — 'auditing content pages for over-optimisation', 'AI-generated content', 'meta tags and alt text', 'unnatural keyword accumulation' — with synonyms (over-optimisation, keyword accumulation), though a few common phrasings like 'keyword stuffing' appear only in the name.	4 / 5
Distinctiveness Conflict Risk	Targets a clear niche (keyword stuffing / over-optimisation detection) with specific triggers (AI-generated repetition, meta/alt-text accumulation); only minor overlap risk with broader content-quality or SEO skills.	4 / 5
	Total	14 / 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/keyword-stuffing/SKILL.md
Commit: 30756a7

Reviewed: 26 days ago

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