One CLI command that tells you exactly why ChatGPT, Gemini, and Perplexity aren't recommending your store — and how to fix it.
Score Trend dashboard — a new admin page under Angeo AEO → Score Trend shows your AEO score over time as a line chart. Includes store selector, period selector (7 / 30 / 90 / 365 days), reference lines at 65% and 85%, and per-store score cards with the latest pass/warn/fail breakdown. Useful for agencies tracking progress across multiple stores.
Dynamic fix commands in CLI output — when a signal fails, the audit output now shows the exact composer require command to fix it. Each checker knows its own fix module, so only relevant commands are shown. No more generic suggestions that don't match your actual failures.
llms.jsonl as Signal #2b — a new checker validates the machine-readable catalog file at /llms.jsonl. Checks JSON Lines format validity, required fields (name, url), eCommerce fields (price, sku, gtin), record count, file freshness via Last-Modified, and dead links. Weight 0.75 — contributes to score but weighted below critical signals.
Deeper llms.txt validation — the existing checker now runs 12 checks instead of 5: description paragraph after H1, eCommerce section detection, currency/language metadata, duplicate URL detection, file freshness, dead link HEAD-checks, and llms-full.txt presence.
getFixCommand() on CheckerInterface — checkers now expose the fix command as part of the interface. Third-party checkers can implement this to surface fix suggestions in CLI output and Admin UI.
- Deep checks — robots.txt fully parsed; Product schema validates
offers.availability; sitemap checks XML validity and lastmod freshness - Weighted scoring — critical checks weight 1.0; informational checks lower weights
- Hyvä theme detection — Product schema check auto-detects Hyvä and gives a specific fix recommendation
- Admin UI — full results grid under Marketing → Angeo AEO → AEO Audit Results
- Cron scheduling — automatic weekly audit every Monday at 03:00
- Extensible via di.xml — third-party modules can inject custom
CheckerInterfaceimplementations
| # | Signal | Weight | What it validates |
|---|---|---|---|
| 1 | robots.txt — AI bot access | 1.0 | OAI-SearchBot, GPTBot, ClaudeBot, PerplexityBot, Google-Extended + 4 more; full parser with first-match semantics |
| 2 | llms.txt — AI content map | 1.0 | H1 title, description, H2 sections, markdown links, eCommerce sections, metadata, freshness, dead links |
| 2b | llms.jsonl — machine-readable catalog | 0.75 | JSON Lines validity, required fields, eCommerce fields, record count, freshness |
| 3 | sitemap.xml | 0.8 | XML validity, URL count, lastmod freshness, robots.txt reference |
| 4 | Product schema — JSON-LD | 1.0 | Real product page, offers.availability, Hyvä detection |
| 5 | FAQPage schema | 0.5 | Homepage and CMS pages |
| 6 | AI product feed | 1.0 | Feed file, /.well-known/ai-plugin.json, REST API endpoint |
| 7 | Open Graph tags | 0.7 | All 5 required tags, description length |
| 8 | Canonical tags | 0.6 | Presence and domain mismatch detection |
composer require angeo/module-aeo-audit
bin/magento setup:upgrade
bin/magento cache:flush# Audit all stores
bin/magento angeo:aeo:audit
# Specific store
bin/magento angeo:aeo:audit --store=en_us
# JSON output (for dashboards / CI)
bin/magento angeo:aeo:audit --format=json
# Markdown report to file
bin/magento angeo:aeo:audit --format=markdown --output=/var/www/html/aeo-report.md
# Fail build if score below threshold
bin/magento angeo:aeo:audit --fail-on=80
# Run without saving to DB (CI / read-only environments)
bin/magento angeo:aeo:audit --no-saveSample output:
AEO Score: [████████████████░░░░] 79% — Good
✓ Pass: 6 ⚠ Warn: 2 ✗ Fail: 1
Critical fixes needed:
→ Install angeo/module-openai-product-feed and register at chatgpt.com/merchants
💡 Fix with angeo modules:
composer require angeo/module-openai-product-feed angeo/module-openai-product-feed-api
Marketing → Angeo AEO → AEO Audit Results — full history grid with score, pass/warn/fail counts, triggered-by, and date. Click View for a detailed breakdown of all checks with messages and fix recommendations.
Marketing → Angeo AEO → Score Trend — line chart of AEO score over time per store. Filter by store and period. Reference lines at 65% (Good) and 85% (Excellent).
Marketing → Angeo AEO → Run Audit Now — trigger an on-demand audit for all stores from the browser.
| Score | Label |
|---|---|
| 0–25% | Needs Improvement — AI crawlers likely blocked, no structured data |
| 26–50% | Needs Improvement — some signals fixed, critical gaps remain |
| 51–75% | Moderate — core signals present, feed or schema incomplete |
| 76–90% | Good — strong foundation, minor gaps |
| 91–100% | Excellent — full AEO compliance |
Weekly audit every Monday at 03:00 server time. Results saved to DB, last 50 per store retained.
bin/magento cron:run --group=defaultImplement Angeo\AeoAudit\Api\CheckerInterface and register via di.xml:
<type name="Angeo\AeoAudit\Model\AuditRunner">
<arguments>
<argument name="checkers" xsi:type="array">
<item name="my_check" xsi:type="object">Vendor\Module\Model\Checker\MyChecker</item>
</argument>
</arguments>
</type>Interface:
public function getName(): string; // "My Custom Check"
public function getCode(): string; // "my_check"
public function getWeight(): float; // 0.0–1.0
public function getFixCommand(): string; // "composer require vendor/fix-module" or ""
public function check(string $baseUrl): CheckResult;vendor/bin/phpunit -c app/code/Angeo/AeoAudit/phpunit.xml| Module | Signal | Purpose |
|---|---|---|
angeo/module-aeo-audit |
— | This module — audit all 9 signals |
angeo/module-robots-txt-aeo |
#1 | Inject AI bot rules into robots.txt |
angeo/module-llms-txt |
#2, #2b | Generate llms.txt and llms.jsonl |
angeo/module-rich-data |
#4, #5 | Product and FAQPage JSON-LD schema |
angeo/module-openai-product-feed |
#6 | ACP product feed for ChatGPT Shopping |
angeo/module-openai-product-feed-api |
#6 | REST API — 6 ACP endpoints |
MIT — see LICENSE