seo-aeo

seo-aeo is a skill for Claude Code, Codex from oegeyilmaz9/seo-aeo-geo-ultimate. It costs 104 tokens per session (1,182 once invoked), scanned A, original, Apache-2.0.

A guide for checking whether supplied pages or documents give clear, complete answers to users’ questions. AEO, or answer-engine optimization, is the practice of making content easy for search systems and AI tools to understand and extract accurately.

In plain words
What is it for?
Use it to audit answers, search intents, audiences, journey stages, clarity, extractability, claim support, and consistency against a prepared research pack.
Why use it?
It helps reveal missing answers, unclear wording, unsupported claims, and differences between what a page visibly says and what its data represents. The review uses captured, dated, source-linked material so missing evidence is not filled in by assumption.

Skill for Claude CodeCodex

Written for Claude Code and Codex: shipped in a Claude Code plugin, but also agents/openai.yaml present.

Part of the seo-aeo-geo-ultimate plugin — 27 skills shipped together

Good fit Use it to audit answers, search intents, audiences, journey stages, clarity, extractability, claim support, and consistency against a prepared research pack.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/oegeyilmaz9/seo-aeo-geo-ultimate/seo-aeo
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add oegeyilmaz9/seo-aeo-geo-ultimate --skill seo-aeo
Clone the repo
git clone --depth 1 https://github.com/oegeyilmaz9/seo-aeo-geo-ultimate

Made for: Claude Code, Codex.

Or install seo-aeo-geo-ultimate, the plugin that ships this one along with the rest of its 27 skills.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for seo-aeo

README.md
[![agentmods](https://agentmods.dev/badge/skills/oegeyilmaz9/seo-aeo-geo-ultimate/seo-aeo/github.svg)](https://agentmods.dev/skills/oegeyilmaz9/seo-aeo-geo-ultimate/seo-aeo)
Your own site
<a href="https://agentmods.dev/skills/oegeyilmaz9/seo-aeo-geo-ultimate/seo-aeo"><img src="https://agentmods.dev/badge/skills/oegeyilmaz9/seo-aeo-geo-ultimate/seo-aeo/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for seo-aeo

Your own site · 80×15
<a href="https://agentmods.dev/skills/oegeyilmaz9/seo-aeo-geo-ultimate/seo-aeo"><img src="https://agentmods.dev/badge/skills/oegeyilmaz9/seo-aeo-geo-ultimate/seo-aeo.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 104 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,182 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00104 $0.01182
Opus 5.5 $0.00042 $0.00473
Sonnet 5.5 $0.00021 $0.00236
Haiku 4.5 $0.00010 $0.00118

Measured 22d ago against content hash a81666c7e971, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

seo-aeo scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 22d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/seo-aeo/SKILL.md · 64 lines

How it starts

The opening of the file, as written. The whole thing — 64 lines — stays where its author put it; the contents beside it link to each section on GitHub.

SEO AEO

Markdown delivery contract

Read markdown-delivery-contract.md for every task. Write a substantive .md document for every material work step and register its direct destination in the work index.md. For public-site work, apply the owner-required Markdown discovery profile across the full eligible inventory; preserve native standards and immutable evidence formats.

Lane outputs: aeo-findings.md; answer-map.md (combine small related steps with stable section links). Audit substantive Markdown answers alongside their pinned HTML/source captures: self-contained meaning, question-to-section access, completeness, dates, limitations and HTML parity. Keep formal Research Pack requirements for engine-scoped claims. Route publisher navigation/parity defects to technical/content owners without inventing engine evidence.

Produce an evidence-linked AEO Optimization Brief from immutable inputs. Audit answer readiness; do not implement the remedies.

Required inputs

  • Require a contract-valid research-pack.json from ai-search-research.
  • Require a dated, bundle-relative capture plus a hash-pinned target-metadata file containing target ID, type, locale, supplied source URL, capture reference, capture SHA-256, and capture time. Never trust Brief fields without matching metadata, invent a canonical URL, or audit an uncaptured, unpinned, or silently refreshed page.
  • Record inaccessible, incomplete, stale, or locale-mismatched inputs as limitations. Do not infer missing content.
  • Read audit-protocol.md before scoring findings or recommending a handoff.

Procedure

  1. Verify the Research Pack identity, schema version, hash, declared locales, queries, evidence, ground truth, and gaps.
  2. Verify every target capture, capture time, target type, and locale. Stop with an explicit gap if a required capture is missing.
  3. Audit only these AEO dimensions:
    • direct-answer completeness;
    • question, intent, audience, and journey-stage coverage;
    • answer clarity and self-contained meaning;
    • claim-to-evidence support and freshness;
    • entity and terminology consistency within the answer;
    • visible-content consistency with any supplied structured-data representation.
  4. Verify every Brief target field against the hash-pinned metadata file. Record target observations as intra-brief direct_observation evidence pinned to the target capture and metadata-supplied source URL. Do not invent a URL or republish Research Pack source records as audit evidence. A target finding must cite that observation; research-dependent conclusions must also cite scope-matched Research Pack evidence.
  5. Bind each finding to resolved Research Pack query IDs. Keep the finding locale equal to its target locale and keep engine/surface scope within those queries' applicability.
  6. Classify each observation as confirmed, vendor-recommended, experimental, or speculative. A finding or confidence level cannot exceed its weakest necessary premise. Speculative evidence never supports an implementation recommendation. Experimental-only support belongs in experiments; route unsupported premises to limitations, declined claims, or research backlog.
  7. Reject unsupported formulas, word-count thresholds, guaranteed placements, universal crawler claims, and universal engine-mandatory llms.txt claims into declined_claims.
  8. Create an optimization-brief.json with optimization_domain: "aeo" and producer_skill: "seo-aeo". Pin every external evidence reference to the immutable Research Pack hash. Use SELF only for an intra-brief audit_evidence reference. Keep stable IDs unique and never copy Research Pack evidence into audit_evidence.
  9. Give every recommendation its own evidence references, desired outcome, confidence, verification method, and exactly one candidate implementation owner. Its evidence must overlap every linked finding and remain scope-compatible. A Brief does not approve a change.
  10. Set created_at after all target captures and audit observations. Validate Research Pack uniqueness, chronology, capture hashes, query applicability, evidence resolution and scope, and the Optimization Brief contract before delivery.

Read the full file on GitHub · 64 lines

Files

What ships with it

7 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 22d ago Changed · +7 lines a81666c7e971
  2. 1mo ago First seen · 57 lines · 104 tokens per session scan A ae1fa3b5f620

Subscribe to this mod's changes

seo-aeo is a skill published in the GitHub repository oegeyilmaz9/seo-aeo-geo-ultimate (5 stars, last pushed 22d ago), licensed Apache-2.0. It adds 104 tokens to every session and 1,182 once invoked, about $0.0004 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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