Name: bencium-aeo
Rating: 83 (1 reviews)
Author: bencium

bencium-aeo

Generate AEO-optimized content (Answer Engine Optimization) for AI search visibility - ChatGPT, Claude, Gemini, AI Overviews. Use when optimizing websites for AI citations, creating FAQ schemas, evidence panels, or analyzing content for LLM extraction readiness.

Quality

78%

Does it follow best practices?

Impact

—

No eval scenarios have been run

Securityby

Advisory

Suggest reviewing before use

Optimize this skill with Tessl

npx tessl skill review --optimize ./bencium-aeo/skills/bencium-aeo/SKILL.md

Quality

Discovery

100%

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

This is a strong, well-crafted skill description that clearly defines a specific niche (AEO/AI search optimization), lists concrete actions, includes rich trigger terms spanning both technical and natural language, and provides explicit 'Use when' guidance. It uses proper third-person voice throughout and would be easily distinguishable from other skills in a large skill library.

Dimension	Reasoning	Score
Specificity	Lists multiple specific concrete actions: 'Generate AEO-optimized content', 'optimizing websites for AI citations', 'creating FAQ schemas', 'evidence panels', 'analyzing content for LLM extraction readiness'. These are distinct, actionable capabilities.	3 / 3
Completeness	Clearly answers both 'what' (generate AEO-optimized content for AI search visibility) and 'when' with an explicit 'Use when...' clause listing specific trigger scenarios: optimizing for AI citations, creating FAQ schemas, evidence panels, or analyzing LLM extraction readiness.	3 / 3
Trigger Term Quality	Excellent coverage of natural terms users would say: 'AEO', 'Answer Engine Optimization', 'AI search visibility', 'ChatGPT', 'Claude', 'Gemini', 'AI Overviews', 'AI citations', 'FAQ schemas', 'evidence panels', 'LLM extraction'. These cover both technical and conversational terms a user might use.	3 / 3
Distinctiveness Conflict Risk	Highly distinctive niche focused specifically on AI search engine optimization (AEO), which is clearly different from traditional SEO skills or general content creation skills. The specific mention of AI platforms and AEO-specific concepts like 'evidence panels' and 'LLM extraction readiness' make it unlikely to conflict with other skills.	3 / 3
	Total	12 / 12 Passed

Implementation

57%

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

This is a well-organized AEO skill with good progressive disclosure and useful domain-specific knowledge (18-token rule, authority levels, Princeton findings). Its main weaknesses are the lack of executable/copy-paste-ready output examples (especially JSON-LD templates) and some verbosity in framing sections. The workflow could benefit from explicit validation checkpoints and feedback loops.

Suggestions

Add a complete, copy-paste-ready JSON-LD FAQPage schema example with datePublished/dateModified fields so Claude can directly adapt it rather than generating from scratch.

Include a concrete before/after example showing a full FAQ entry transformation (original content → AEO-optimized output with schema) to make the 'What to Generate' section truly actionable.

Add an explicit feedback loop to the assessment framework: e.g., 'If score < 6 on any dimension, apply these specific fixes and re-score.'

Dimension	Reasoning	Score
Conciseness	The skill is mostly efficient but includes some unnecessary framing (e.g., the 'When to Use This Skill' section lists triggers Claude could infer, and some explanatory text like 'NOT for traditional SEO' is somewhat redundant). The core content is reasonably dense but could be tightened in places.	2 / 3
Actionability	Provides concrete structural guidance (word counts, token counts, checklist items) and good/bad examples for extraction, but lacks executable code examples for JSON-LD schema generation, HTML templates, or any copy-paste-ready output templates. The skill tells Claude what to generate but doesn't show complete examples of the output.	2 / 3
Workflow Clarity	The 'What to Generate' section provides a clear sequence of deliverables, and the testing protocol adds a validation step. However, there's no explicit feedback loop for the assessment framework (e.g., score below X → do Y), and the implementation checklist lacks sequencing or validation checkpoints between steps.	2 / 3
Progressive Disclosure	Well-structured with a clear overview in the SKILL.md, appropriate use of sections, and one-level-deep references to prd.md and story-structured.md for full templates and details. Navigation is clear and content is appropriately split between overview and detailed documentation.	3 / 3
	Total	9 / 12 Passed

Validation

100%

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 — 11 / 11 Passed

Validation for skill structure

No warnings or errors.

Repository: bencium/bencium-marketplace
Commit: 20077d3

Reviewed: 15 days ago

Table of Contents

Discovery Implementation Validation

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