aeo

Answer Engine Optimization (AEO) skill — optimize content to be cited by AI language models (ChatGPT, Perplexity, Claude, Gemini, Mistral) as authoritative sources. Distinct from SEO — AEO optimizes for citation in LLM-generated responses, not search rankings. Use when planning content for AI-first search audiences, auditing existing content for E-E-A-T signals, tracking which pages get cited by which LLMs, or building a citation-friendly content strategy. Triggers — 'AEO audit', 'optimize for ChatGPT', 'get cited by Perplexity', 'LLM citation strategy', 'answer engine optimization', 'content for AI search', 'E-E-A-T audit'. Output is a markdown audit report (default) or JSON for pipeline integration. Stdlib-only Python tools.

Quality

85%

Does it follow best practices?

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Quality

Content

75%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 highly actionable, with copy-paste CLI commands and a clear workflow supported by real bundle files. Its main weakness is conciseness: several tables and templates that belong in the reference files are inlined in SKILL.md.

Suggestions

Move the full 'Industry-Specific E-E-A-T Thresholds' table into references/aeo_eeat_canon.md and replace it in SKILL.md with a one-line pointer plus a couple of representative examples.

Trim the Output Format section to a compact example and defer the full markdown template to a reference file, since the '[...]' and '[3-count of analysis steps]' placeholders add length without actionable detail.

Add an explicit post-optimization validation step to the Workflow (e.g., 're-run aeo_audit.py on the optimized variant to confirm the composite score improved') to close the feedback loop.

Dimension	Reasoning	Score
Conciseness	Mostly efficient, but it inlines reference-grade material — the full Industry-Specific E-E-A-T Thresholds table, a complete output-format template with placeholder sections, and an SEO comparison table that duplicate content belonging in the provided reference files.	3 / 5
Actionability	Fully executable, copy-paste-ready CLI commands with real flags cover the common cases — audit ('--url'), optimize ('--input post.md --mode balanced --output'), and citation tracking ('--action add'/'report').	5 / 5
Workflow Clarity	A clear numbered sequence (pre-flight bot access → audit → optimize → publish/monitor → report) with an explicit pre-flight gate, but it lacks an explicit post-optimization re-audit feedback loop to confirm improvement.	4 / 5
Progressive Disclosure	Good structure with five real, well-signaled one-level-deep references and three scripts, all described in the References section; the minor gap is inlining some reference-grade tables rather than pointing to the reference files.	4 / 5
	Total	16 / 20 Passed

Description

95%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, third-person description that clearly states what the skill does, when to use it, and how it differs from SEO, with a rich set of natural trigger phrases. The only mild weakness is that the listed actions are somewhat high-level rather than fully granular.

Dimension	Reasoning	Score
Specificity	Lists several concrete actions — 'auditing existing content for E-E-A-T signals', 'tracking which pages get cited by which LLMs', 'building a citation-friendly content strategy' — but they remain moderately high-level rather than maximally granular.	4 / 5
Completeness	Explicitly answers both what ('optimize content to be cited by AI language models as authoritative sources') and when ('Use when planning content for AI-first search audiences...') with concrete trigger phrases.	5 / 5
Trigger Term Quality	Comprehensive natural trigger coverage with synonyms — 'AEO audit', 'optimize for ChatGPT', 'get cited by Perplexity', 'LLM citation strategy', 'answer engine optimization', 'content for AI search', 'E-E-A-T audit' — phrases a user would naturally say.	5 / 5
Distinctiveness Conflict Risk	Clear niche with an explicit carve-out — 'Distinct from SEO — AEO optimizes for citation in LLM-generated responses, not search rankings' — and distinct triggers, minimizing overlap with the adjacent SEO skill.	5 / 5
	Total	19 / 20 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 — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository: alirezarezvani/claude-skills
Path: marketing-skill/skills/aeo/SKILL.md
Commit: 19392f7

Reviewed: ~2 hours ago

Table of Contents

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