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

1. 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").
2. 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.
3. 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)
4. 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
5. 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:

1. Publish CRO-anchored guide (prd-v09-alternatives-pages handles competitor variants)
2. Rewrite product schema (JSON-LD) with the Dunford category claim
3. 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:

• At least 5 queries tested (quick) / 10–15 (standard) / 20+ (deep)
• At least 3 AI surfaces sampled (standard+)
• Every gap has a typed classification (Absence / Category / Citation / Comparison)
• Every gap has a proposed fix with a handoff target
• Coverage Matrix exists and is dated
• Fix backlog is ranked

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)