Pricing

$4.00 / 1,000 store analyzeds

Shopify Store Analyzer | $4/1K | Revenue, Traffic, Tech Stack

Most complete Shopify intelligence tool, lowest price. Analyze any store: revenue estimate, real traffic, brand age, 60+ apps, tracking IDs (GTM/GA4/FB Pixel), promo codes, dropshipper risk score, international expansion. StoreLeads ($29/mo) alternative - pay-per-use $4/1K, no API key.

Pricing

$4.00 / 1,000 store analyzeds

Rating

0.0

(0)

Developer

Apivault Labs

Actor stats

Bookmarked

Total users

Monthly active users

4 days ago

Last modified

[2.20] — 2026-06-20 — Recent launches & top product types

Added

🆕 Recent products (recent_products) — the store's most recently launched products (title, launch date, URL, price). "What did this competitor just drop?" — a high-value spy signal.
🗂️ Top product types (top_product_types) — the most common product types in the catalog with counts, for quick category profiling.

[2.19] — 2026-06-20 — Lead-list market snapshot (discovery summary)

Added

📊 Discovery summary — discover / reverse-app-lookup / find-similar runs now also return a single lead-list snapshot record: how many stores were found, % with a public email / phone, country distribution, and app-category & top-app adoption across the set. Also saved to the key-value store under DISCOVERY_SUMMARY. Gives the lead-gen audience an instant market read.

[2.18] — 2026-06-20 — Qualification filters (filtered prospecting)

Added

🎯 Qualification filters — minMonthlyVisits, minStoreHealth and minOpportunityScore keep only analyzed stores that clear your thresholds. Combine with discovery + requiredApps / excludeApps / country to build a precisely-filtered lead list, e.g. "coffee stores with >50k visits using Klaviyo but not Yotpo". Filtered-out stores are skipped and never charged.

[2.16] — 2026-06-20 — Robust at volume (catalog rate-limit handling)

Fixed

Genuine Shopify stores are no longer dropped at volume. When many stores are analyzed at once, Shopify rate-limits /products.json per IP; previously a throttled catalog made the Actor skip the store as "not Shopify". Now: the homepage is fetched first to confirm the store, /products.json is retried with backoff on rate-limit / 5xx, and a confirmed Shopify store with an unreachable catalog still returns its full homepage-derived intelligence (catalog_accessible: false) instead of being skipped.

[2.15] — 2026-06-20 — Dropshipper-risk legitimacy dampener

Fixed

The dropshipper risk score no longer falsely flags large, established brands as "high" risk. A legitimacy dampener (high traffic + revenue + brand age + large catalog) caps the score so genuine brands that happen to reuse template descriptions or launch frequently are correctly rated low risk.

[2.14] — 2026-06-20 — Cleaner email extraction

Fixed

Public email extraction now filters out telemetry / asset noise (Sentry DSN addresses, ingest.*, .css / .js / font artifacts, placeholder example.com), so best_email and the contact list contain only real, usable addresses for lead generation.

[2.13] — 2026-06-20 — Store summary & target markets

Added

🧾 Store summary (store_summary) — a single human/LLM-readable line per store (segment, niche, est. revenue, maturity, key apps, ads) — ideal for AI agents and quick scanning of a results table.
🌐 Target markets (markets) — the distinct country markets a store localizes for, parsed from its hreflang tags.

[2.12] — 2026-06-20 — Cohort intelligence + email-capture signal

Added

📈 Cohort intelligence in the comparison report — when comparing 2+ stores, the report now also shows the niche distribution, cohort-average store-health / opportunity / lead scores, an opportunity-score ranking, the most attractive sales target and the healthiest store.
✉️ Email-capture signal (content_marketing.has_email_capture) — whether the store runs a newsletter / email-capture popup (Privy, Justuno, Klaviyo form, OptinMonster…).

[2.11] — 2026-06-20 — Opportunity score, pitch angles, exclude-apps filter

Added

🎯 Opportunity score (0–100) + tier — how attractive a store is as a sales target (established + has app gaps to fill + growing + reachable + has budget), with a transparent opportunity_breakdown.
💬 Pitch angles (pitch_angles) — concrete, ready-to-use sales angles derived from the store's gaps and weaknesses (no reviews app, missing meta description, no blog, heavy discounting, single-market high-traffic…).
🚫 Exclude-apps filter (excludeApps) — in Discover modes, skip stores that use a given app, e.g. find stores that do NOT already run your tool. Combine with requiredApps for precise targeting (uses Y but not Z).

[2.10] — 2026-06-20 — Quick Shopify check + policy details

Added

⚡ Quick check mode (quick_check) — bulk-triage a list of URLs: is each one a Shopify store? Returns is_shopify, detected platform (Shopify / WooCommerce / BigCommerce / Wix / Squarespace / Magento / custom) and the myshopify handle. One fast fetch per URL — a low-friction way to filter a big domain list before a full analysis.
📦 Policy details (extractPolicyDetails, opt-in) — reads the store's refund & shipping policy pages for the returns window (days), free-returns and free-shipping signals.

[2.9] — 2026-06-20 — Richer best-sellers, price bands, SEO & content signals

Added

🏆 Richer best-sellers — each best-seller now includes compare-at price, discount %, on-sale flag, product type, option/variant counts and image URL (not just title + price).
📊 Price distribution (price_distribution) — how the catalog splits across price bands (under $25 / $25–50 / $50–100 / $100–250 / $250+).
🔎 SEO snapshot — homepage page_title, meta_description_present, has_structured_data (JSON-LD).
✍️ Content-marketing signal (content_marketing) — whether the store runs a blog and how many posts it has (content maturity).

[2.8] — 2026-06-20 — Find similar / competitor stores

Added

🧭 Find similar / competitor stores — new find_similar mode. Give one store (seedStoreUrl) and the Actor learns its niche from its products, then returns other Shopify stores selling similar things — each tagged with similar_to. Perfect for "find competitors of this store" research. Results are enriched (contacts, tech stack) and respect the country and reverse app-lookup filters.

[2.7] — 2026-06-20 — Reverse app lookup (find stores using an app)

Added

🔎 Reverse app lookup (requiredApps + appMatchMode) — in Discover modes, return only stores whose tech stack uses a specific app or technology, e.g. ["Klaviyo"], ["Yotpo"], ["ReCharge"]. Combine with search terms to find, for example, coffee stores using Klaviyo. Non-matching stores are skipped and never charged. Matched apps are returned in matched_apps. Built for app vendors targeting stores that run a competitor's app.
Discovered stores now also include their detected tech stack (tech_stack + tech_stack_categorized) during contact enrichment.

[2.6] — 2026-06-20 — Categorized tech stack, express checkout, tiered pricing

Added

🗂️ Categorized tech stack (tech_stack_categorized) — the detected apps grouped into readable categories (reviews, email & SMS, loyalty & subscriptions, support, page builder & CRO, logistics, dropshipping, analytics & pixels, payments, search) instead of one flat list.
⚡ Express checkout (express_checkout + express_checkout_methods) — whether an accelerated checkout is enabled (Shop Pay / Apple Pay / Google Pay / PayPal).

Changed

Volume-based tiered pricing — higher plans pay less per store. Lower price the more you scale.

[2.5] — 2026-06-20 — Comparison report now included for everyone

Changed

The cross-store comparison report is no longer a premium add-on. It's now generated automatically for every run that analyzes 2+ stores, at no separate charge — rankings by traffic, revenue, AOV, discounting, international expansion and tech stack, shared-tech analysis and the cohort leader in each category. Set generateComparison: false to skip the extra record.

[2.4] — 2026-06-20 — Lead score, growth signals, payments & policies

Added

🎯 Lead score (0–100) + temperature bucket (cold / warm / hot) with a lead_score_breakdown — how actionable a store is as a sales lead (best-email role, phone, socials, store quality, upsell gaps). Built for the lead-generation audience.
🚀 Growth signals (growth_signals + is_scaling) — momentum flags (product velocity, young brand, running paid ads, aggressive discounting, international expansion, traffic growth) so you spot a competitor that's actively scaling.
💳 Payment & BNPL stack (payment_methods, bnpl_offered, bnpl_methods) — surfaced as first-class fields (Shop Pay, Apple/Google Pay, PayPal, Klarna, Afterpay, Affirm, Sezzle).
📜 Store policies (policies_detected) — which policy pages the store links (refund, shipping, privacy, terms) as a trust / maturity signal.
Lead score & temperature added to the Contacts & Ads dataset view.

[2.3] — 2026-06-20 — Store health score, upsell targeting, niche, deeper contacts

Added

💯 Store health score (0–100) + maturity tier (emerging / growing / established / enterprise) with a transparent store_health_breakdown — combines traffic, revenue, product velocity, tech sophistication, international reach and social proof so you can rank and prioritize stores at a glance.
🎯 Upsell opportunities (upsell_opportunities + app_categories_present) — the high-value app categories a store has no solution for (reviews, email & SMS, loyalty, subscriptions, helpdesk, page builder, CRO/upsell, analytics & attribution). A ready-made pitch list for Shopify app vendors and agencies, and the categories already covered.
🏷️ Primary niche (primary_niche) — best-effort product-niche classification from tags and store copy (beauty, apparel, food & beverage, fitness, pet, and more).
📧 Deeper contact discovery (deepContactCrawl, on by default) — when the homepage exposes no email, the Actor checks the store's contact / about pages too, so best_email is found for many more stores. Only fires when the homepage has none, so stores that already show contact info cost no extra time.
New dataset view: Upsell Targets; health score & niche added to the Store Overview view.

[2.2] — 2026-06-20 — Change tracking (competitor monitoring)

Added

🔔 Change tracking (trackChanges, on by default) — the Actor now remembers each store between runs and reports exactly what changed since you last analyzed it, in a new changes field:
- new and removed products (with examples of the new ones)
- monthly traffic and estimated-revenue moves (absolute + %)
- AOV and product-count shifts
- apps installed or removed from the tech stack
- new advertising / analytics pixels
- promo codes launched or ended Run it on a schedule over a list of competitors to get a running monitor of who's launching products, ramping ad spend, or discounting. The first run for a store just records a baseline. New Changes Since Last Run dataset view.

[2.1] — 2026-06-20 — Best-seller detection, ad intelligence, contact roles

Added

🏆 Best-seller detection — every analyzed store now returns a ranked best_sellers list of its likely top products. When the store keeps a curated best-seller / trending / most-popular collection, the products are taken straight from it in the merchant's own order (
```
best_sellers_basis: "store-curated collection"
```
); otherwise a catalog heuristic is used. Each entry includes title, direct product URL, price and stock status — ideal for spotting a competitor's winning products at a glance.
📣 Ad intelligence (ad_intelligence) — see a store's paid-acquisition footprint: which platforms it's set up to advertise on (Meta, TikTok, Google Ads, Pinterest, Snapchat) and a one-click Meta Ad Library link straight to the brand's live ads. Derived from the public advertising pixels already on the page.
📧 Contact roles + best email — public emails are now tagged by role (owner / sales / marketing / support / info / personal / noreply) and the single most outreach-useful address is surfaced as best_email, in both Analyze and Discover modes. Turns a raw email dump into a ready-to-action lead contact.
New dataset views: Best Sellers and Contacts & Ads.

Changed

The old image-count likely_best_sellers proxy is replaced by the stronger collection-based best_sellers signal above.

[2.0] — 2026-06-18 — Universal revenue, lead enrichment, flat output

Added

Review-based revenue estimate — revenue/sales are now estimated even for small or low-traffic stores where public traffic data is unavailable, using the store's review volume (sales_estimate block + a basis flag on revenue_estimate). Configurable reviewsToSalesMultiplier.
Contact enrichment in Discover mode (enrichContacts, on by default) — each discovered store now also returns public emails, phones and social handles, turning a store list into a ready-to-use lead list.
Flat output (flatOutput) — flatten nested fields into underscore-joined columns (e.g. traffic_monthly_visits) for easy mapping in spreadsheets, n8n, Zapier and Make.

[1.9] — 2026-06-18 — Store discovery (find stores by keyword)

Added — find Shopify stores, no URL needed

New Discover modes via the mode input:
- Discover stores by keyword / niche — give search terms like ["organic coffee", "yoga mats"] and get back a list of real Shopify stores selling those products (name, URL, myshopify domain, country). Perfect for lead generation and market mapping.
- Discover, then analyze — discover stores and immediately run the full intelligence analysis on each.
New inputs: searchTerms, discoverCountry (optional best-effort ISO-2 filter), maxStores. storeUrls is now only required in Analyze mode.
Discovery uses public marketplace data, rotates proxies and backs off on rate limits for reliable results. You're billed per store returned, the same flat per-store rate as analysis.

[1.8] — 2026-06-18 — Lower price + clearer listing

Changed

New lower price: $4 per 1,000 stores (down from $10/1K) — now the most affordable full Shopify store-intelligence tool on Apify, with platform usage included and a single flat per-store fee.
Rewritten README and store description: unique capabilities up front (advertising tracking IDs for brand-network mapping, dropshipper risk score, real traffic intelligence, 60+ app detectors), a side-by-side comparison, and an AI-assistant / MCP quick-start block.

[1.7] — 2026-06-05 — Billing safety

Fixed

The premium comparison report is now charged before it is written to the dataset, so a per-run cost-cap abort can never deliver an uncharged report. (Per-store analysis billing is unchanged — it uses the implicit dataset-item event.)

[1.6] — 2026-05-31 — Competitor comparison report (premium add-on)

Added — cross-store benchmarking

New optional generateComparison flag. When analyzing 2 or more stores in one run, the Actor produces a single comparison report that ranks the stores against each other:
- rankings by monthly visits, estimated revenue, AOV, discount aggressiveness, international expansion and tech-stack richness
- the cohort leader in each category (traffic leader, revenue leader, highest AOV, most aggressive discounting, most international, richest tech stack)
- shared-tech analysis (which apps are common across the cohort vs rare)
- cohort averages and a customer-segment / dropshipper-risk breakdown
The report is added as a record in your dataset and also saved to the key-value store under COMPARISON_REPORT for easy one-key retrieval.
This is a premium add-on, billed once per run as a separate event, and only when a report is actually produced (needs at least 2 successfully analyzed stores). Leave generateComparison off to skip it entirely.

[1.5] — 2026-05-31 — Reliability & accuracy improvements

This release makes runs faster and more reliable, and ensures you only get clean, successful results in your dataset.

Improved — only successful analyses are saved

Stores that can't be analyzed (not a Shopify store, unreachable homepage) are no longer mixed into your results. Successful analyses go to your dataset; anything skipped is listed separately in the key-value store under FAILED_STORES so you can review it without it cluttering your data.

Improved — faster, more stable runs on large catalogs

Full-catalog mode (productSampleSize: 0) now samples up to 2000 products, which is more than enough for every metric and keeps runs fast and stable on very large stores.
Per-request response handling was streamlined so unusually large pages or sitemaps no longer slow a run down.

Changed — brand-age lookup is now opt-in

The brand-age lookup (earliest Wayback snapshot + SSL certificate) is the slowest part of an analysis and is a secondary signal, so it's now off by default (extractBrandAge: false). The store's CDN ID still gives an approximate age signal for free. Enable extractBrandAge when you specifically need founding year / brand age.

Added — per-run limits for predictable runs

Up to 100 stores per run (split larger lists across runs).
Each page/sitemap fetch reads only what's needed for the metrics.

[1.4] — 2026-05-21

Added — 5 new intelligence layers (no new HTTP requests)

New extractors (all parsed from existing homepage HTML / /products.json):

🎯 tracking_ids — extracts public advertising / analytics IDs:
- Google Tag Manager (GTM-XXXXXX)
- GA4 Measurement ID (G-XXXXXXXX)
- Universal Analytics (UA-XXXX-X)
- Facebook Pixel ID
- TikTok Pixel ID
- Pinterest Tag ID
- Snapchat Pixel ID
- Klaviyo public key
- Hotjar Site ID
- Intercom App ID
- Microsoft Clarity ID
Use case: brand-network mapping — multiple domains sharing the same FB Pixel = same operator. Unique feature, not offered by StoreLeads/Commerce Inspector.
🔢 cdn_store_id / cdn_store_id_numeric — Shopify-internal sequential ID parsed from cdn.shopify.com/s/files/1/{group}/{store}/. Lower numbers = older stores. Free backup signal for brand age, independent of Wayback / SSL. Stores on Online Store 2.0 get cdn_store_id_format: "online-store-2.0" instead.
📢 announcement block — pulls active marketing copy from announcement bars / hero sections:
- free_shipping_threshold_usd (e.g. 35, 50, 100, or 0 for universal free shipping)
- active_promo_codes — up to 3 currently-active codes (SUMMER25, SAVE10)
- announcement_discount_pct — current % off on banner
- announcement_bar_text — clean excerpt (Liquid placeholders filtered out)
🏷️ Top product tags (top_tags, unique_tags_count) — aggregated from /products.json tags field. Reveals niche orientation (vegan, eco, gift-for-her, men, women, organic, ...) at a glance.
🪞 duplicate_description_pct — percentage of sampled products sharing a body description. High duplicate ratio = generic AliExpress catalog. Adds a strong dropshipper signal.

Dropshipper risk score upgrades:

New signal: >30% duplicate descriptions → +15 points
New signal: very high CDN store ID (very recent store) + low brand age → +5 points

Input schema:

New flag extractPromo (default true) for announcement / promo extraction
Updated descriptions for extractTechStack, extractShopifyMeta, extractProducts to reflect new fields

Tested

colourpop.com → GTM WQKQL2VQ, GA4 WSYJCRME4P, "Free U.S. shipping on orders over $35", 207 unique tags, 44% duplicate descriptions
allbirds.com → GTM TH8KRSBJ, CDN store ID 1104/4168 (legacy), "30% off your order when you spend $150+", 89% duplicate descriptions

[1.3] — 2026-05-21

Added — Major intelligence expansion (5 new data sources, 14 new derived signals)

New data sources:

🌐 Sitemap analysis (/sitemap.xml) — real product/page/collection/blog totals (not sample-based)
⏱️ Brand age estimation — combines Wayback Machine first snapshot + crt.sh first SSL cert
🌍 International expansion scan — hreflang languages, currency switcher, country selector detection
⭐ Reviews aggregate — schema.org aggregateRating JSON-LD parsing
🛒 Cart endpoint confirmation

New derived signals:

customer_segment — mass-market / mid-market / premium / luxury (auto-classified by AOV)
marketing_channel_mix — search-driven, social-driven, paid-driven, brand-driven, email-driven, mixed (with %)
dropshipper_risk_score (0-100) + signals — heuristic detection: brand age, velocity, traffic, discounting, dropshipping apps
dropshipper_risk_bucket — low / medium / high
annualized_revenue_usd_est — yearly projection
oldest_product_date — when store first started selling
products_on_sale_pct + avg_discount_pct — discount aggressiveness
vendors_count + top_vendors[] — vendor concentration
product_types_count
total_variants_sampled + variant_in_stock_pct — inventory health
avg_images_per_product — premium brand signal
international_expansion_score (0-100)
estimated_brand_age_years + estimated_founded_year

Tech stack — expanded from 50 to 60+ detectors:

Reviews: added Junip, Reviews.io
Loyalty: added LoyaltyLion, Yotpo Loyalty, Growave
Email/SMS: added SMSBump, Sendlane
Support: added Re:amaze
CRO: added Crazy Egg, Mouseflow, Triple Whale, Northbeam
Logistics: added ShipStation, ShipBob
Dropshipping: added CJ Dropshipping, Spocket
Search: added Algolia, Searchanise

Fixed

classify_marketing_mix no longer crashes on stores with sparse SimilarWeb data (None values in traffic_sources)
Phone number extraction now uses tel: links primarily, avoiding timestamp false positives
SimilarWeb traffic source schema change handled (SearchOrganic/SearchPaid split)

Improved

Better email filtering (drops CDN, Sentry, escaped characters)
Theme name now properly trimmed in output
9-second average per store with default concurrency

[1.2] — 2026-05-20

Added

Initial pricing structure: $10 per 1000 stores
Tech stack detection (50+ Shopify apps)

[1.1] — 2026-05-12

Added

Multi-store batch processing
Parallel HTTP via ThreadPoolExecutor

[1.0] — 2026-05-11

Added

Initial release
4 data sources: /products.json, /collections.json, homepage HTML, SimilarWeb public API
Revenue estimation via visits × CR × AOV formula
Basic tech stack detection
Social links + emails extraction
Shopify meta detection (currency, locale, theme)

Shopify Store Discovery - Apps, Revenue Estimate, Tech Stack

seibs.co/shopify-store-discovery

Find Shopify stores by domain list with full intel: 30+ app detection (Klaviyo/Recharge/Yotpo/Gorgias/etc), product count, revenue estimate range, theme, social links. Server-side filter by required/excluded apps + revenue range. For D2C SaaS sales teams.

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Pay-per-result Store Leads scraper. Look up Shopify, WooCommerce, BigCommerce stores by domain or search with filters. Extract traffic, sales, employees, technologies, social profiles (Instagram, Facebook, TikTok), contact emails, and 80+ fields per store.

SilentFlow

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Shopify AppStore Scraper

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A powerful Apify Actor designed to extract comprehensive data from the Shopify App Store. This scraper can discover all available apps, collect detailed application information, and extract user reviews from any Shopify app, making it perfect for market research, and competitor analysis.

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Shopify App Reviews Scraper

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Scrape customer reviews from Shopify App Store by providing a review page URL, with automatic pagination and comprehensive review information extraction.

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Shopify Product Scraper

webdatalabs/shopify-product-scraper

Extract complete product data from any Shopify store including prices, discounts, variants (up to 250 per product), customer reviews, ratings, and sales estimates. Bonus: discover 321K+ Shopify stores by category.

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Judge Me Review Scraper for Shopify stores

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Scrape Judge.me reviews from any Shopify store. Get ratings, text, images & videos. Unlimited usage for a $7/month.

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Semantic Scholar Scraper

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Extract detailed academic paper data from Semantic Scholar, including abstracts, citations, authors, and publication details. Ideal for researchers, academics, and analysts who need structured scholarly data for literature reviews, research workflows, and large-scale academic analysis.

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Monitor any Shopify store for competitor catalog, price, availability, variants, collections, and review data. Extract DTC storefront intelligence with no API key.

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Storeleads Scraper

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Scrape Store Leads ecommerce data. Look up Shopify, WooCommerce, BigCommerce stores by domain or search with filters. Extract traffic, sales, employees, technologies, social profiles, contact emails, and 80+ fields per store. Free preview mode available.

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Shopify Store Analyzer | $4/1K | Revenue, Traffic, Tech Stack

Changelog

[2.20] — 2026-06-20 — Recent launches & top product types

Added

[2.19] — 2026-06-20 — Lead-list market snapshot (discovery summary)

Added

[2.18] — 2026-06-20 — Qualification filters (filtered prospecting)

Added

[2.16] — 2026-06-20 — Robust at volume (catalog rate-limit handling)

Fixed

[2.15] — 2026-06-20 — Dropshipper-risk legitimacy dampener

Fixed

[2.14] — 2026-06-20 — Cleaner email extraction

Fixed

[2.13] — 2026-06-20 — Store summary & target markets

Added

[2.12] — 2026-06-20 — Cohort intelligence + email-capture signal

Added

[2.11] — 2026-06-20 — Opportunity score, pitch angles, exclude-apps filter

Added

[2.10] — 2026-06-20 — Quick Shopify check + policy details

Added

[2.9] — 2026-06-20 — Richer best-sellers, price bands, SEO & content signals

Added

[2.8] — 2026-06-20 — Find similar / competitor stores

Added

[2.7] — 2026-06-20 — Reverse app lookup (find stores using an app)

Added

[2.6] — 2026-06-20 — Categorized tech stack, express checkout, tiered pricing

Added

Changed

[2.5] — 2026-06-20 — Comparison report now included for everyone

Changed

[2.4] — 2026-06-20 — Lead score, growth signals, payments & policies

Added

[2.3] — 2026-06-20 — Store health score, upsell targeting, niche, deeper contacts

Added

[2.2] — 2026-06-20 — Change tracking (competitor monitoring)

Added

[2.1] — 2026-06-20 — Best-seller detection, ad intelligence, contact roles

Added

Changed

[2.0] — 2026-06-18 — Universal revenue, lead enrichment, flat output

Added

[1.9] — 2026-06-18 — Store discovery (find stores by keyword)

Added — find Shopify stores, no URL needed

[1.8] — 2026-06-18 — Lower price + clearer listing

Changed

[1.7] — 2026-06-05 — Billing safety

Fixed

[1.6] — 2026-05-31 — Competitor comparison report (premium add-on)

Added — cross-store benchmarking

[1.5] — 2026-05-31 — Reliability & accuracy improvements

Improved — only successful analyses are saved

Improved — faster, more stable runs on large catalogs

Changed — brand-age lookup is now opt-in

Added — per-run limits for predictable runs

[1.4] — 2026-05-21

Added — 5 new intelligence layers (no new HTTP requests)

Tested

[1.3] — 2026-05-21

Added — Major intelligence expansion (5 new data sources, 14 new derived signals)

Fixed

Improved

[1.2] — 2026-05-20

Added

[1.1] — 2026-05-12

Added

[1.0] — 2026-05-11

Added

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