| name | cf-aeo-check |
| description | Post-publication AI-visibility check — re-probes target queries via web search, records whether the published piece is cited in Google AI Overviews, audits on-page extractability (definition block, dates, schema, structures) via web fetch, and appends every check to per-brand history so deltas are tracked over time. Triggers on "/contentforge:cf-aeo-check", "is our article cited in AI Overviews", "did we earn AI citations", "check AEO for this URL", "why is a competitor cited instead of us". Measures Google-observable signals only (no ChatGPT/Perplexity probing unless an AEO-tracking connector is present, and then labeled); closes the loop /contentforge:cf-brief opens and routes absent verdicts to /contentforge:content-refresh with evidence. Reports and records — it does not edit or republish the page. |
| argument-hint | [published URL or REQ-ID] |
| effort | medium |
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
Optional:
- Brand — brand profile (auto-detected from the tracking record when using REQ-ID)
- Queries — comma-separated override of the queries to probe. Default: primary keyword + top 3 question keywords, recovered from the run's
phase-6-seo.md (preferred) or the brief; if neither exists, derive 3-5 natural queries from the page's H1/H2s and say so. Also fold in any FAQ-disposition questions from the Phase 7 review report — the questions the reviewer found readers silently asking are the closest thing to real query data the pipeline produces, and they are exactly what answer engines get asked
--compare — show deltas vs the previous check (default when history exists)
How to Use
/contentforge:cf-aeo-check https://acme.com/blog/ai-in-healthcare-2026
/contentforge:cf-aeo-check REQ-001 --brand=AcmeMed
/contentforge:cf-aeo-check REQ-001 --queries="ai diagnostics accuracy,is AI better than radiologists"
What Happens
Step 1: Resolve target + queries (10-20 seconds)
- Resolve REQ-ID → published URL via the tracking backend (
local / google_sheets / airtable)
- Assemble the query set (see Required Inputs); record which source the queries came from — scorecard honesty rule: derived queries are labeled
derived, never passed off as the brief's targets
Step 2: SERP + AI Overview probe (per query, 1-3 minutes total)
For each query, via web search:
- AI Overview present? yes / no / unclear (record verbatim which sources are visibly cited when the search surface exposes them)
- Own-domain citation: is the published piece (or its domain) among the cited/visible sources?
cited / visible-not-cited / absent
- Competitor presence: which Phase-1/Phase-2-era competitors (or new domains) hold the citations
- Organic position band for the published URL where observable: top-3 / top-10 / beyond / not-found — a band, not a fake precise rank
Step 3: On-page extractability audit (30-60 seconds)
Web-fetch the published URL and verify the machine-liftable elements survived the CMS:
- Definition sentence within the first 150 words — intact?
- Publication + last-updated dates visible?
- Structured elements (tables, numbered steps, Q&A headers) from the phase-6 structure manifest — still present in the rendered page?
- Article/Person schema in the page source — present? (CMSes routinely strip JSON-LD; this is the #1 silent AEO regression)
- Author byline with credentials — rendered?
Step 4: Record + delta (10 seconds)
Append the check to ~/.claude-marketing/{brand-slug}/aeo/checks.json (same storage-resolution rules as every other artifact — $CLAUDE_MARKETING_HOME → $CLAUDE_PLUGIN_DATA → ~/.claude-marketing):
{
"url": "...", "requirement_id": "REQ-001", "checked_at": "YYYY-MM-DD",
"queries": [{"q": "...", "source": "phase-6-seo|brief|derived|user",
"ai_overview": "yes|no|unclear", "own_citation": "cited|visible-not-cited|absent",
"cited_domains": ["..."], "position_band": "top-3|top-10|beyond|not-found"}],
"extractability": {"definition_intact": true, "dates_visible": true,
If history exists, compute deltas per query (gained / lost / unchanged citation status) and flag any extractability regression since the last check.
Step 5: Report + routing
Render the AEO Check Report: per-query table, extractability checklist, deltas, and one recommended action:
cited and holding → re-check in 6-12 weeks, no actionvisible-not-cited → extractability fixes first (they're free): restore stripped schema, tighten the definition block — then re-check in 2-4 weeksabsent while competitors are cited → route to /contentforge:content-refresh with the specific gap evidence (which domains are cited and what they have that the piece lacks)- Extractability regression (schema stripped, structures flattened by the CMS) → fix at the CMS level; note that
/contentforge:cf-publish post-publish verification would have caught this at publish time
Cadence recommendation: check at ~2, ~6 and ~12 weeks post-publication, then quarterly. Record every check — the trend is the product.
Output Example
SYNTHETIC EXAMPLE — fabricated for illustration; never reuse these domains or results.
AEO CITATION CHECK — acme.com/blog/ai-in-healthcare-2026
Checked: 2026-07-30 | Previous: 2026-07-02 | Engine coverage: google-only
| Query | AIO | Own citation | Δ vs last | Cited domains |
|--------------------------------------|-----|---------------------|------------|----------------------|
| ai diagnostics precision medicine | yes | cited | ▲ gained | acme.com, nih.gov |
| how accurate is AI diagnosis | yes | visible-not-cited | = unchanged| examplehealth.com |
| ai diagnostic tools for hospitals | no | — (top-10 organic) | = unchanged| — |
Extractability: definition ✓ | dates ✓ | structures 5/5 ✓ | schema ✗ (JSON-LD stripped by CMS) | byline ✓
Action: schema was present at publish and is now missing — restore Article+Person
JSON-LD in the CMS template, then re-check query 2 in ~3 weeks.
Limitations
- Google-observable signals only, unless an AEO-tracking connector is present (then per-connector coverage, labeled)
- AI Overview composition varies by location/session — single probes are evidence, not ground truth; the multi-check trend is the reliable signal
- A citation today is not a citation tomorrow; that is why checks append to history instead of overwriting
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