Name: bencium-aeo
Rating: 64 (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

75%

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 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 has an explicit 'Use when' clause. It follows third-person voice correctly 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, which is clearly different from general SEO, content writing, or other web optimization skills. The AEO-specific terminology and AI platform names create a clear, unique trigger profile.	3 / 3
	Total	12 / 12 Passed

Implementation

50%

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

This skill provides a solid conceptual framework for AEO optimization with useful principles (18-token rule, authority levels, freshness) and good structural guidance. However, it falls short on actionability by lacking executable code examples for JSON-LD generation or complete output templates, and the workflow lacks explicit validation/feedback loops. The content is moderately concise but includes some sections that explain context Claude could infer.

Suggestions

Add a complete, copy-paste-ready JSON-LD FAQPage schema example with placeholder content that Claude can adapt, rather than just naming the schema types.

Include a concrete before/after example showing a full FAQ entry transformation (original content → AEO-optimized output with schema markup).

Add explicit validation steps to the workflow: e.g., after generating JSON-LD, validate with a specific tool/command; if extraction test fails, specify remediation steps.

Trim the 'When to Use This Skill' trigger list—Claude can infer these from the skill description—and use that space for actionable templates instead.

Dimension	Reasoning	Score
Conciseness	The skill is mostly efficient but includes some unnecessary framing (e.g., the 'When to Use This Skill' section tells Claude things it can infer, and some explanatory text like 'NOT for traditional SEO' is somewhat redundant). The anti-patterns section and core principles are reasonably tight but could be tightened further.	2 / 3
Actionability	The skill provides concrete structural guidance (word counts, token counts, checklist items) and good/bad examples for extraction-ready sentences, but lacks executable code examples for JSON-LD schema generation, HTML templates, or any copy-paste-ready output templates. The 'What to Generate' section describes what to produce but doesn't show complete examples of the output.	2 / 3
Workflow Clarity	The implementation checklist and testing protocol provide a reasonable sequence, but there are no explicit validation checkpoints or feedback loops. The testing protocol is listed as a post-implementation step but lacks guidance on what to do if tests fail. The assessment framework scoring (0-10) lacks clear thresholds for pass/fail.	2 / 3
Progressive Disclosure	References to `prd.md` and `story-structured.md` are present and clearly signaled, but no bundle files were provided to verify these exist. The SKILL.md itself contains a substantial amount of inline content that could potentially be split better, and the core reference to prd.md is mentioned twice (top and bottom) without clear differentiation of what's in each referenced file.	2 / 3
	Total	8 / 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: 2e2fa33

Reviewed: 5 days ago

Table of Contents

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