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ai-seo

Optimize content for AI search and LLM citations across AI Overviews, ChatGPT, Perplexity, Claude, Gemini, and similar systems. Use when improving AI visibility, answer engine optimization, or citation readiness.

Quality

77%

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tessl review fix ./plugins/AI-Agents-Safe-Coding-Skills-claude/skills/ai-seo/SKILL.md

The canonical home for this skill is ai-seo in administrakt0r/AI-Agents-Safe-Coding-Skills

SKILL.md
Quality
Evals
Security

Quality

Content

67%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, information-dense skill with concrete heuristics, named tools/bots, and real reference files properly linked one level deep. Its weaknesses are redundancy (duplicated question sections and repeated statistics) and topic-organized rather than explicitly-sequenced workflow guidance that keeps the audit-to-monitoring loop implicit.

Suggestions

Remove the 'Task-Specific Questions' section — it duplicates the 'Before Starting' context-gathering questions almost verbatim — and delete the repeated Princeton GEO statistics that appear in both the Pillar 2 table and its sub-bullets.

State the end-to-end workflow explicitly at the top (audit current visibility → fix extractability/robots.txt → apply pillar optimizations → re-check monthly) so the audit's pass/fail results clearly gate which optimization steps to prioritize.

Move the monitoring-tools and content-type citation-share tables into a references file (e.g., references/monitoring-tools.md), keeping only the tracking metrics inline, so the main body mirrors the lean split already used for content patterns and platform ranking factors.

DimensionReasoningScore

Conciseness

The tables carry genuinely useful domain data, but there is notable redundancy: "Task-Specific Questions" duplicates the "Before Starting" context gathering, the Princeton GEO stats and 45% AI Overview figure each appear in multiple sections, and Pillar 2's sub-bullets restate the methods table. This is more than minor over-explanation (below anchor 4) though the payload still dominates over padding (above anchor 2).

3 / 5

Actionability

Guidance is largely concrete and executable: the 40-60-word passage rule, named bot user-agents (GPTBot, PerplexityBot, ClaudeBot), exact query patterns, a pass/fail extractability checklist, and per-content-type optimization lists. Some Pillar 3 items are generic marketing advice ("Participate authentically in Reddit communities") without how-to specifics, keeping it below anchor 5.

4 / 5

Workflow Clarity

A clear sequence exists — gather context, run the 4-step visibility audit, apply the three pillars, then monitor monthly — with the audit's pass/fail checks and DIY monthly monitoring acting as validation checkpoints. However, the end-to-end flow is implied by section order rather than stated as one explicit workflow with checkpoints, and per-page optimization lacks a validate-after-change step.

4 / 5

Progressive Disclosure

Both referenced bundle files exist (references/content-patterns.md, references/platform-ranking-factors.md) and are clearly signaled at one level deep with purpose statements. The 400-line body still inlines substantial detail that mirrors those reference topics (platform landscape table, monitoring tool tables), which is a minor organization gap versus anchor 5's clean split.

4 / 5

Total

15

/

20

Passed

Description

78%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 strong description that clearly states both capability and explicit trigger conditions in third person, with good natural-language trigger coverage. Its main weakness is reliance on a single generic verb ("optimize") rather than enumerating concrete actions like auditing visibility, restructuring content, or checking robots.txt access.

DimensionReasoningScore

Specificity

The single generic action "Optimize content for AI search and LLM citations" names the domain and enumerates platforms, but offers no breakdown into concrete capabilities (audit, restructuring, schema, monitoring). It exceeds anchor 2's bare domain-naming thanks to the platform list and citation framing, but falls short of anchor 4's several specific actions.

3 / 5

Completeness

Explicitly answers what ("Optimize content for AI search and LLM citations across AI Overviews, ChatGPT, Perplexity, Claude, Gemini, and similar systems") and when ("Use when improving AI visibility, answer engine optimization, or citation readiness") with concrete trigger phrases — a direct match for anchor 5.

5 / 5

Trigger Term Quality

Natural phrases like "AI visibility", "answer engine optimization", and "citation readiness" plus platform names (ChatGPT, Perplexity, AI Overviews) match what users would say. Missing common variations such as "AI SEO", "GEO", or "generative engine optimization", so it does not reach comprehensive anchor 5.

4 / 5

Distinctiveness Conflict Risk

The AI-citation niche is clearly distinct from traditional SEO, but the body's own related-skills list (seo-audit, schema-markup, copywriting) shows closely adjacent siblings, and bare "optimize content" phrasing could overlap with general copywriting/SEO skills. Mostly distinct with minor overlap risk — anchor 4.

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

frontmatter_unknown_keys

Unknown frontmatter key(s) found; consider removing or moving to metadata

Warning

Total

15

/

16

Passed

Repository

administrakt0r/AI-Agents-Safe-Coding-Skills

Path

plugins/AI-Agents-Safe-Coding-Skills-claude/skills/ai-seo/SKILL.md

Reviewed

Table of Contents

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