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.
npx skills add kensaurus/cursor-kenji --skill plan-aeo-readinessgit clone --depth 1 https://github.com/kensaurus/cursor-kenjiWrote 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.
[](https://agentmods.dev/skills/kensaurus/cursor-kenji/plan-aeo-readiness)<a href="https://agentmods.dev/skills/kensaurus/cursor-kenji/plan-aeo-readiness"><img src="https://agentmods.dev/badge/skills/kensaurus/cursor-kenji/plan-aeo-readiness/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.
<a href="https://agentmods.dev/skills/kensaurus/cursor-kenji/plan-aeo-readiness"><img src="https://agentmods.dev/badge/skills/kensaurus/cursor-kenji/plan-aeo-readiness.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00084 | $0.01694 |
| Opus 5 | $0.00042 | $0.00847 |
| Sonnet 5 | $0.00017 | $0.00339 |
| Haiku 4.5 | $0.00008 | $0.00169 |
Grade A, and why
plan-aeo-readiness 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 5d 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.
How it starts
The opening of the file, as written. The whole thing — 166 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Answer-Engine Readiness Audit + Citation Plan
Degree of freedom: HIGH — crawl access, extractability, authority levers, plan. Stay plan-only. No robots.txt, schema, or copy edits until approved.
This skill vs neighbors
| Skill | Owns |
|---|---|
| plan-aeo-readiness (this) | Answer-engine / GEO citation plan |
enhance-web-seo |
Classic search meta / sitemap / OG |
plan-antislop |
Voice / slop in the copy itself |
Role: Senior growth engineer + content strategist (AEO/GEO lens).
Task: Confirm AI crawler access first, audit content extractability and authority
levers per key page, phase remediations, emit plan-aeo-readiness.md. Audit & plan
only — no robots.txt, schema, or copy edits until approved.
Find why AI engines don't cite you. Plan the fix. Change nothing until approved.
How to reason (every plan item)
- Propose — unblock a bot, SSR/expose, schema, or authority lever
- Risk — engines never see the page, or they see it and have nothing to cite
- Keep-working — pages already answer-first with valid schema
- Phase — Unblock → Structure → Authority → Entity-measure (do not execute)
Worked example
Propose: allow GPTBot/PerplexityBot in robots.txt; add an FAQ JSON-LD block on
/pricing. Risk: Cloudflare default blocks AI bots — citation frequency is zero until access exists. Keep-working:/docsis SSR and already direct-answer-first. Phase: Phase 1 — Unblock & expose. Lever: access before schema; do not promise a rank.
Ranking #1 on Google no longer buys an AI citation. Overlap between top Google links and AI-cited sources has dropped from ~70% to below 20%. LLM-referred visitors convert markedly better than classic search traffic (~4.4x in one 2026 analysis).
This skill targets LLM citation — distinct from SERP rank (enhance-web-seo).
When this fires
Trigger phrases: "do AI engines cite me", "AEO", "GEO", "answer engine optimization", "show up in ChatGPT/Perplexity", "AI search visibility", "llms.txt", "am I blocking AI crawlers".
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.
- 5d ago First seen · 166 lines · 84 tokens per session scan A 5bdd99a67ec9
plan-aeo-readiness is a skill published in the GitHub repository kensaurus/cursor-kenji (9 stars, last pushed 11d ago), licensed MIT. It adds 84 tokens to every session and 1,694 once invoked, about $0.0004 per session on Opus 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 2026-09-03.
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