| name | prd-v09-aeo-audit |
| description | Audit how AI search engines (ChatGPT, Perplexity, Google AI Overviews, Claude) describe and recommend your product, then propose fixes. Triggers on requests to audit AI search visibility, improve AEO/GEO, check ChatGPT/Perplexity coverage, or when user asks "do we show up in AI search?", "AEO audit", "generative engine optimization", "AI discoverability", "how does ChatGPT describe us?", "Perplexity ranking". Outputs GTM-AEO-* entries and a Coverage Matrix.
|
| context | fork |
| allowed-tools | ["Read","Write","Edit","Glob","Grep","WebSearch","WebFetch"] |
| execution_modes | {"default":"standard","supports":["quick","standard","deep"]} |
AEO Audit (AI Search Discoverability)
Position in workflow: v0.9 Launch Channels (ORB) → v0.9 AEO Audit → v0.9 Alternatives Pages, Launch Metrics
Execution Mode
Default is standard. See .claude/rules/08-skill-execution-modes.md for selection logic.
| Mode | What this skill produces |
|---|
| quick | 5 target queries × 2 AI surfaces (ChatGPT + Perplexity); top 3 gaps with fixes |
| standard | 10–15 queries × 3–4 AI surfaces; full Coverage Matrix; ranked fix backlog |
| deep | 20–30 queries × all major surfaces; per-surface citation analysis; structured-data audit; before/after re-test plan |
What This Does
Tests whether AI search engines surface, recommend, and accurately describe the product when a target customer asks a relevant question. AEO (answer-engine optimization) and GEO (generative-engine optimization) are the post-SEO distribution layer — when ChatGPT/Perplexity/AI Overviews answer a buyer's question, the product either is in the answer or isn't.
This is a diagnostic skill. It produces a gap map and a ranked fix backlog. The fixes are executed by prd-v09-alternatives-pages, content updates, and structured-data work — not by this skill.
How It Works
- Build a query set — From the Positioning best-fit characteristics (jobs to be done, triggers, search intent), generate target queries an actual best-fit buyer would type. Mix high-intent ("best X for Y"), comparison ("X vs Y"), and category ("what is X").
- Run each query against AI surfaces — At minimum: ChatGPT (free tier — what the median buyer sees), Perplexity, Google AI Overviews. Deep mode adds Claude, Brave Search, Kagi. Save raw responses with timestamps.
- Score each result on five dimensions:
- Mentioned? (yes / no)
- Position in recommendation list (1st, 2nd, not listed)
- Description accuracy (matches positioning vs. miscategorized vs. wrong)
- Competitive frame (which alternatives are listed alongside)
- Citation sources (which URLs/domains the AI cited to build the answer)
- Identify the gap pattern:
- Absence gaps — product not mentioned at all
- Category gaps — mentioned in the wrong category (positioning failure)
- Citation gaps — answer is built from sources the product doesn't appear in (need to be on those sources)
- Comparison gaps — competitor wins the comparison query because comparison content doesn't exist on your side
- Propose ranked fixes — Each fix maps to a specific gap type:
- Absence → content on best-fit query intent, JSON-LD structured data, citation-source targets
- Category → positioning content (handoff to Positioning skill)
- Citation → outreach/contribution to high-citation sources (G2, Reddit, blog posts on cited domains)
- Comparison → handoff to prd-v09-alternatives-pages
Example
A best-fit buyer types "best CRO tool for early-stage SaaS founders" into ChatGPT. Result:
| Surface | Mentioned? | Position | Accuracy | Citations |
|---|
| ChatGPT | No | n/a | n/a | 5 sources, none ours |
| Perplexity | Yes | 4th of 5 | "an analytics tool" (wrong category) | Sources include our pricing page only |
| AI Overviews | No | n/a | n/a | G2, Reddit r/SaaS, two competitor blog posts |
Gaps identified:
- Absence in ChatGPT — no high-intent landing for this query
- Category miscoding in Perplexity — we're being summarized as "analytics", not "CRO"
- Citation gap — we don't appear in G2 or r/SaaS threads about CRO
Ranked fixes:
- Publish CRO-anchored guide (prd-v09-alternatives-pages handles competitor variants)
- Rewrite product schema (JSON-LD) with the Dunford category claim
- Outreach to G2 (claim profile, request reviews) and post a substantive thread in r/SaaS
What You Get Back
- GTM-AEO-* entries — one per query × surface gap, with the proposed fix and ranking
- Coverage Matrix (single GTM-* with Type=Audit) — full query × surface × status table
- Fix backlog — ranked list with handoff target skills
When to Use It
| Trigger | Mode |
|---|
| Pre-launch sanity check (before paid channels activate) | quick |
| Standard launch wave audit | standard |
| Quarterly retention/competitive intelligence review | deep |
| After major positioning change (re-test) | standard |
| When organic signups stall and paid CAC rises | deep |
Do not run before Positioning is complete — without a sharpened category claim, every "miscategorized" result is unfixable.
Consumes
- GTM-* positioning statement + category claim (from v0.9 Positioning) — Defines what "accurate description" looks like; without this, scoring is opinion
- CFD-* competitive alternatives (from v0.2) — Source for comparison-intent queries
- PER-* best-fit characteristics (sharpened by Positioning) — Source for query intent
- GTM-* channel mix (from v0.9 Launch Channels) — AEO is a channel; surfaces tested should match best-fit channel use
Produces
- GTM-AEO-* entries with
Type=AEO-Recommendation, one per gap-fix pair
- GTM-* with
Type=Audit — the Coverage Matrix
- Fix backlog — handoff list referencing prd-v09-alternatives-pages, Positioning re-run, content production tickets
Confidence guidance (P4): AEO scoring is 3/5 minimum because it's based on observed AI responses, not opinion. Quick mode may produce 2/5 outputs (limited sampling) and must tag them.
Output Template
GTM-AEO-XXX: [Gap Title]
Type: AEO-Recommendation
Status: Open
Priority: [High | Medium | Low]
Owner: [Person / role]
Query: "[the exact query]"
Surface: [ChatGPT | Perplexity | AI Overviews | Claude | Brave | Kagi]
Date observed: [YYYY-MM-DD]
Result summary:
Mentioned? [yes | no]
Position: [#]
Accuracy: [matches positioning | miscategorized | wrong]
Competitive frame: [list of alternatives shown]
Citation sources: [URLs/domains used]
Gap type: [Absence | Category | Citation | Comparison]
Proposed fix:
- [Specific action 1]
- [Specific action 2]
Handoff: [Target skill or owner — e.g., prd-v09-alternatives-pages, content team]
Re-test: [Date to verify fix]
Linked IDs: GTM-YYY (positioning), CFD-ZZZ (competitor), PER-AAA (best-fit)
GTM-XXX: AEO Coverage Matrix
Type: Audit
Status: Snapshot — [YYYY-MM-DD]
| Query | ChatGPT | Perplexity | AI Overviews | Gap Type |
|-------|---------|------------|--------------|----------|
| ... | ✓ #2 | ✗ | ✗ | Absence (2 surfaces) |
| ... | ✗ | ✓ #4 (miscat) | ✗ | Category + Absence |
Total queries: X
Coverage rate: Y% (mentioned in any surface)
Accurate-description rate: Z% (mentioned AND correctly described)
Linked IDs: All GTM-AEO-* entries above
Anti-Patterns
| Pattern | Signal | Fix |
|---|
| Vanity queries | Auditing "best [exact product name]" — you'll always win that one | Use buyer-intent queries the buyer would actually type |
| No timestamp / no re-test | Results saved but never re-tested | AI surfaces change; re-test every fix within 2 weeks |
| Surface monoculture | Only testing ChatGPT | Each surface has different model/data; minimum 3 surfaces |
| Fix all gaps equally | 20 gaps, parallel work, no ranking | Rank by query buyer-intent strength × surface adoption |
| Treating absence as failure | "We're not in any results — game over" | Absence is often the easiest fix (publish high-intent content); category miscoding is the harder one |
| Skipping citation analysis | Knowing you're absent but not why | Citation sources reveal where you need to appear |
Quality Gates
Before proceeding to fix execution:
Downstream Connections
| Consumer | What it uses | Example |
|---|
| Alternatives Pages | Comparison-gap fixes become alternatives-page targets | "X vs us" comparison gap → SCR-ALT- page |
| Positioning (re-run) | Category-coding gaps signal positioning weakness | Recurring miscategorization → re-run prd-v09-positioning-dunford |
| Launch Metrics | Coverage Matrix becomes a KPI baseline | KPI-AEO-coverage% |
| v1.0 Continuous Discovery | Recurring gap patterns inform discovery questions | "Users keep finding competitor X — why?" |
Detailed References
- Sanity team's
seo-aeo-best-practices skill (VoltAgent index)
- Princeton AI Search benchmark studies
- (No bundled
references/ — AI surfaces change too quickly to canonize)
