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 teachskillofskills-ai/ContentForge-techshu --skill cf-aeo-checkgit clone --depth 1 https://github.com/teachskillofskills-ai/ContentForge-techshuWrote 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/teachskillofskills-ai/contentforge-techshu/cf-aeo-check)<a href="https://agentmods.dev/skills/teachskillofskills-ai/contentforge-techshu/cf-aeo-check"><img src="https://agentmods.dev/badge/skills/teachskillofskills-ai/contentforge-techshu/cf-aeo-check/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/teachskillofskills-ai/contentforge-techshu/cf-aeo-check"><img src="https://agentmods.dev/badge/skills/teachskillofskills-ai/contentforge-techshu/cf-aeo-check.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 | $0.00187 | $0.02253 |
| Opus 5 | $0.00093 | $0.01126 |
| Sonnet 5 | $0.00037 | $0.00451 |
| Haiku 4.5 | $0.00019 | $0.00225 |
Grade A, and why
cf-aeo-check 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 12d 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.
This is a copy
100% identical to cf-aeo-check — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 125 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AEO Citation Check — Post-Publication
Close the loop that /contentforge:cf-brief opens. The brief checks AI Overview presence and citation patterns before production; this skill verifies — after publication — whether the piece actually earned citations, tracks the trend across re-checks, and routes losses to /contentforge:content-refresh with specific evidence.
Honest scope — read before promising anything
- What this skill measures directly: Google SERP state for the target queries via web search (AI Overview present? which domains are cited/visible? does the piece rank?), and on-page extractability of the published URL via web fetch (definition block intact, dates visible, schema present, metrics tables surviving the CMS).
- What it cannot measure directly: citations inside ChatGPT, Perplexity, Gemini or Copilot answers — there is no public API for "was I cited," and probing chat UIs is not reproducible. Cross-engine measurement needs a third-party tracker (Profound, Otterly, Conductor AgentStack, HubSpot AEO — same list the Phase 6 optimizer names). If such a connector is available in the tool list, use it and label the data's source; if not, say plainly that engine coverage is Google-observable-only. Never present an estimate as a measurement.
When to Use
Use /contentforge:cf-aeo-check when:
- A piece published 2+ weeks ago and you want to know if AI engines are citing it (earlier checks mostly measure indexing lag, not merit)
- You're deciding which content to refresh and want citation evidence, not hunches
- A competitor appears in AI Overviews for your target query and you want the delta documented
- You want a standing citation scoreboard per brand across re-checks
Not for: pre-production research (that's /contentforge:cf-brief), rank tracking as a discipline (this is a citation check, not a rank tracker), or measuring engines it cannot observe (see Honest scope).
Required Inputs
Minimum required (one of):
- Published URL — the live page to check
- Requirement ID (e.g.,
REQ-001) — resolved via the brand's tracking backend to the published URL recorded at completion; fails with a clear message if no URL was recorded
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.
- 12d ago First seen · 125 lines · 187 tokens per session scan A ae2540caf58d
cf-aeo-check is a skill published in the GitHub repository teachskillofskills-ai/ContentForge-techshu (1 stars, last pushed 22d ago), licensed MIT. It adds 187 tokens to every session and 2,253 once invoked, about $0.0009 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to cf-aeo-check, differing in 0 lines, and is treated as a copy.
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