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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.

58

Quality

68%

Does it follow best practices?

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SecuritybySnyk

Low

Low-risk findings worth noting

Fix and improve this skill with Tessl

tessl review fix ./skills/keyword-stuffing/SKILL.md
SKILL.md
Quality
Evals
Security

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.

A well-structured overview with genuinely concrete detection criteria and fix examples, backed by a real one-level reference file for implementation details. The main deficits are triply-repeated rationale/background padding, an ambiguous section ordering, and the absence of a re-validation loop after fixes.

Suggestions

Collapse the intro, Quick Reference, and Explain rationale into one brief statement and move the Panda/SpamBrain background to references/rule.md — the penalty rationale is currently stated three times.

Add a validation loop at the end of Fix: re-run the density/frequency check from the Code Review section to confirm flagged terms fall below thresholds before finishing.

Reorder sections so the programmatic Code Review analysis precedes Fix (detect → analyze → remediate → re-check), and make the reference pointer a markdown link within the relevant sections.

DimensionReasoningScore

Conciseness

The Check and Fix sections are dense and useful, but the rationale that Google penalizes keyword stuffing is stated three times — in the intro ("penalise pages... demoted in search results"), Quick Reference ("Google's algorithms (Panda, SpamBrain) penalise pages"), and the Explain section ("demoted or removed from results") — and the Explain section restates background (Panda, SpamBrain, quality guidelines) Claude already knows. This is more than the 4 anchor's 'minor instances of over-explanation' but the core sections are efficient enough to stay above the 2 anchor's 'several padded sections'.

3 / 5

Actionability

The Check section gives executable criteria with concrete thresholds ("more than 3× in the title tag", "density above 3% of total word count", specific keyword-list examples, DevTools computed-styles check), and Fix gives concrete before/after rewrites ("cheap flights london paris..." → "Passenger cabin view on London to Paris flight"). It sits at 4 rather than 5 because the Code Review section is procedural description ("Tokenise into words. Compute frequency...") with no command or script, and implementation details are deferred to the reference rather than made copy-paste ready here.

4 / 5

Workflow Clarity

A rough Check → Fix sequence exists, but the Code Review (programmatic analysis) section appears after Fix, making the intended order of detect → analyze → remediate ambiguous. More importantly, there is no validation loop: Fix step 6 tests readability, but nothing instructs re-running the density/frequency check to confirm the fixes actually resolved the flagged issues, which for a content-rewriting workflow is a missing checkpoint rather than a minor gap. This matches the 3 anchor ('steps listed but validation gaps') and sits below the 4 anchor's 'most checkpoints present'.

3 / 5

Progressive Disclosure

The body is a ~40-line overview organized into labeled sections (Quick Reference, Check, Fix, Explain, Code Review) and correctly offloads full implementation and code examples to a real, one-level-deep bundle file — "see `references/rule.md`", which exists and contains the code examples as claimed. It falls short of the 5 anchor because the pointer is plain text (not a link) placed below a trailing horizontal rule where it is easy to miss, and background material (Explain) that could live in the reference is inlined in the main file.

4 / 5

Total

14

/

20

Passed

Description

75%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.

A solid description with explicit, well-phrased 'Use when' triggers and concrete third-person audit actions tied to specific page elements. Its main weaknesses are the merged what/when structure that never states remediation capabilities, and omission of the canonical trigger terms 'keyword stuffing' and 'SEO'.

Suggestions

Add the canonical terms 'keyword stuffing' and 'SEO' to the description so users who say those exact phrases trigger the skill naturally.

State what the skill does with findings (e.g., 'flags stuffed elements and rewrites them with natural variation') in addition to when to use it, separating the 'what' from the 'Use when...' clause.

DimensionReasoningScore

Specificity

The description lists three concrete audit actions with specific targets — "auditing content pages for over-optimisation", "reviewing AI-generated content that may repeat target phrases excessively", "checking meta tags and alt text for unnatural keyword accumulation" — all in third-person gerund form. It falls short of the 5 anchor because coverage has gaps: it never states what the skill does about findings (e.g., flagging, rewriting, fixing, or computing keyword density), only that it audits/checks. It is clearly above the 3 anchor, which expects only 1-2 concrete actions.

4 / 5

Completeness

The explicit "Use when..." clause answers 'when' with three concrete trigger scenarios, satisfying the trigger-clause requirement. The 'what' is present but embedded in the same gerund phrases (auditing/reviewing/checking) rather than stated as distinct capabilities or outcomes, so it does not match the 5 anchor's clearly separated and explicit what-and-when. It is above the 3 anchor because the 'when' is explicit, not merely implied.

4 / 5

Trigger Term Quality

Good natural-term coverage: "content pages", "AI-generated content", "meta tags", "alt text", "target phrases", and "keyword accumulation" are phrases users would plausibly say. It misses the most canonical natural terms — "keyword stuffing" (the practice's name, which appears only in the skill name field) and "SEO" — plus "keyword density", so it fits the 4 anchor ("good keyword coverage; a few natural terms missing") rather than the comprehensive 5 anchor, and is well above the 3 anchor's 'missing common variations'.

4 / 5

Distinctiveness Conflict Risk

The keyword-repetition/accumulation niche is mostly distinct from sibling SEO-audit rules, with triggers unlikely to fire for unrelated skills. Minor overlap risk remains: "auditing content pages for over-optimisation" is broad enough to collide with general content-quality or meta-tag-specific SEO skills, matching the 4 anchor ('mostly distinct; minor overlap risk with closely related skills') rather than the minimal-conflict 5 anchor.

4 / 5

Total

16

/

20

Passed

Validation

93%

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

CriteriaDescriptionResult

metadata_version

'metadata.version' is missing

Warning

Total

15

/

16

Passed

Repository
thedaviddias/Front-End-Checklist
Reviewed

Table of Contents

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