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 matteotitta/genesys-skills --skill aeo-strategygit clone --depth 1 https://github.com/matteotitta/genesys-skillsWrote 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/matteotitta/genesys-skills/aeo-strategy)<a href="https://agentmods.dev/skills/matteotitta/genesys-skills/aeo-strategy"><img src="https://agentmods.dev/badge/skills/matteotitta/genesys-skills/aeo-strategy/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/matteotitta/genesys-skills/aeo-strategy"><img src="https://agentmods.dev/badge/skills/matteotitta/genesys-skills/aeo-strategy.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00024 | $0.01917 |
| Opus 5 | $0.00012 | $0.00958 |
| Sonnet 5 | $0.00005 | $0.00383 |
| Haiku 4.5 | $0.00002 | $0.00192 |
Grade A, and why
aeo-strategy 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 9d 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 — 103 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AEO Strategy
Produce a research-backed content strategy for search + AI visibility. Output: cluster taxonomy, keyword gap analysis, competitor content audit, prioritised article queue with target keywords, and a 90-day publishing timeline. Level 1 strategy skill — produces what to write; the Level 2 aeo-content skill produces the actual content from this queue.
When to run
User says "AEO strategy", "content roadmap", "keyword gap analysis", "what should [company] publish", "90-day content plan for search", "article queue for [company]", or "what content will get us cited by AI?". Skip if they want a single article (/aeo-content), channel-agnostic plan (/content-strategy), or pure SEO audit (web search). Full trigger list: the premium reference.
Inputs
Required: company context (product, features) · 3-5 competitors with URLs · GSC exports (Queries CSV, Pages CSV, Coverage) · GA4 exports (Traffic acquisition, Landing pages). Without GSC/GA4, all keyword data must be marked [ESTIMATED] and strategy confidence flagged in the executive summary.
Recommended: ICP research · existing content audit · positioning/messaging · competitor-research · content-strategy · win-loss-analysis · transcript-analysis (last two enable Phase 2.5 query seeding).
Optional: prior keyword research · monthly content target (override default 20) · AirOps brand kit.
Full export instructions (exact GSC/GA4 click paths, columns, used-in-phase mapping) + validation checklist: the premium reference.
Steps
Eight phases. Each phase has sub-steps, output templates, and checkpoints in the premium reference — read it before producing the output.
- Phase 1 — Input validation. Load company context · confirm 3-5 competitors with geography tags · set parameters (default: 20/month, 90 days, 50/20/30 BOFU/MOFU/TOFU split; adjust by maturity).
- Phase 2 — Cluster taxonomy. Build 5-8 product-mapped pillars (not generic categories), each with 5-10 sub-clusters from product docs + ICP pains + competitor content.
- Phase 2.5 — Transcript query seeding (only if win-loss/transcript outputs exist). Mine buyer questions, convert to natural-language queries, tag by cluster + source, merge into
aeo/query-index.md(or seed it). - Phase 3 — SEO keyword gap analysis. Pull client baseline (GSC) + competitor keywords (DataForSEO → Apify → Exa fallback) · identify gaps · group by cluster · separate by geography · pull AirOps AI-citation baseline · write 1-paragraph competitor keyword strategy summaries.
- Phase 4 — Competitor content analysis. Enumerate each competitor's pages free with
mcp__spider__spider_links(per.claude/rules/crawl-cost-discipline.md), triage to in-scope pages, then Firecrawl only the kept set · LLM-classify pages by funnel stage (TOFU/MOFU/BOFU) AND cluster · build funnel-stage and cluster comparison tables · identify zero-coverage clusters and underweight stages. - Phase 5 — Competitor best performing content. Exa + Firecrawl + DataForSEO traffic estimates → pick top 5 per competitor · tag each with funnel stage + cluster · write 1-paragraph strategy analysis per competitor.
- Phase 6 — Content type strategy. Define types per stage (BOFU: comparisons, branded, integrations, pricing, demo · MOFU: how-to, "Best X for Y", deep-dives, use cases, compliance · TOFU: definitions, industry guides, regulatory, thought leadership) · set % allocation grounded in Phase 4 gaps · write rationale per type.
- Phase 7 — Article queue. Generate specific titles per type with target keywords. BOFU: 1 comparison per competitor + branded pages. MOFU: how-tos mapped to features + "Best for [year]" listicles, flag UPDATE vs CREATE. TOFU: definitions targeting highest-volume gap keywords + industry/regulatory guides.
- Phase 8 — 90-day timeline. Assign articles to months (M1: comparisons + high-volume TOFU + initial MOFU · M2: BOFU deep-dives + continue MOFU/TOFU · M3: remaining BOFU + integrations + TOFU depth) · build period × stage summary table.
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.
- 9d ago First seen · 103 lines · 119 tokens per session scan A 9e6125925846
aeo-strategy is a skill published in the GitHub repository matteotitta/genesys-skills (36 stars, last pushed 1mo ago), licensed MIT. It adds 24 tokens to every session and 1,917 once invoked, about $0.0001 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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