/landing-page-review

name: landing-page-review
description: CRO review of a landing page with specific conversion recommendations
version: "1.1.1"
author: Cogny AI
platforms: []
user-invocable: true
argument-hint: "<url>"
allowed-tools:
  - WebFetch
  - WebSearch
  - Bash
  - Read
  - Write
  # Optional, when Cogny MCP is connected (all read-only)
  - mcp__cogny__refresh_mcp_discovery
  - mcp__cogny__list_integrations
  - mcp__cogny__mcp__Microsoft_Clarity__get_live_insights
  - mcp__cogny__mcp__Microsoft_Clarity__get_insights_history
  - mcp__cogny__mcp__Microsoft_Clarity__get_api_quota
  - mcp__cogny__mcp__Google_Analytics_4__tool_list_account_summaries
  - mcp__cogny__mcp__Google_Analytics_4__tool_run_report
  - mcp__cogny__mcp__Google_Analytics_4__tool_list_conversion_events
  - mcp__cogny__mcp__Plausible__breakdown
  - mcp__cogny__mcp__Plausible__query
  - mcp__cogny__mcp__GrowthBook__list_experiments
  - mcp__cogny__mcp__GrowthBook__get_experiment_results

Landing Page Review

Analyze a landing page for conversion optimization — messaging, layout, trust signals, and CTA effectiveness.

Usage

`/landing-page-review example.com/pricing` — review the given page

Works with

The review runs on the public page with zero accounts. Connected analytics turn opinions into measured problems.

| Job | Primary | Also answers it | No account | |-----|---------|-----------------|------------| | Conversion rate of this page, by device and source | GA4 (`tool_run_report`) | Plausible (`breakdown`, `query`) | — (score from heuristics) | | Where visitors get stuck (scroll, rage/dead clicks, quickbacks) | Microsoft Clarity (`get_live_insights`) | — | — | | What was already A/B tested here | GrowthBook (`list_experiments`, `get_experiment_results`) | — | Ask the user |

If GA4 and Plausible are both connected, show both rates side by side; they count sessions and visitors differently.

Steps

1. Fetch and analyze the page

Use WebFetch to load the URL. Extract:

• Headline and subheadline text
• CTA buttons (text, placement, count)
• Value proposition clarity
• Above-the-fold content
• Page structure (sections, flow)

2. Evaluate messaging

Score each element:

• **Headline clarity** (1-10): Does it immediately communicate what you get?
• **Value prop specificity** (1-10): Numbers > vague claims
• **CTA strength** (1-10): Action-oriented, specific, visible
• **Social proof** (1-10): Testimonials, logos, stats
• **Urgency/scarcity** (1-10): Reason to act now

3. Check trust signals

Look for:

• Customer logos or testimonials
• Security badges / certifications
• Pricing transparency
• Contact information
• Privacy policy / terms links
• Case studies or results

4. Analyze form/CTA friction

If there's a form:

• Number of fields (fewer = higher conversion)
• Field labels and placeholder text
• Submit button text (specific > generic)
• Error handling
• Privacy reassurance near form

5. Mobile assessment

From the fetched HTML you can check:

• Mobile viewport meta tag (`curl -sL <url> | grep -i 'name="viewport"'`; WebFetch can't see `<head>`)
• Content readability on small screens (font sizes and line lengths in the CSS, if inline)

Touch target sizes and whether the CTA sits above the fold need a rendered page. WebFetch and curl can't measure them. Run the URL through PageSpeed Insights (https://pagespeed.web.dev, Lighthouse flags "Touch targets" / "tap targets"), or open it in a browser's device mode at 375px wide. If neither is possible, mark both "not measured (needs a browser)" instead of scoring them.

5a. Measure load time

Step 7 scores load speed, so measure it rather than guess:

curl -sL -o /dev/null -w "ttfb=%{time_starttransfer}s total=%{time_total}s html=%{size_download}B redirects=%{num_redirects}\n" "<url>"
# Rough page weight: HTML + the scripts, styles and images it references
curl -sL "<url>" | grep -oE '(src|href)="[^"]+\.(js|css|png|jpe?g|webp|avif|svg)[^"]*"' | head -40

Fetch the largest few assets with the same `-w "%{size_download}"` call and sum them. Report "TTFB X s, HTML Y KB, ~Z KB total across N requests (curl, no JS execution)". Over 1 s TTFB or ~3 MB total weight costs load-speed points. For field data (real users), use `/cwv-audit`.

5b. Measured behavior (enhanced when connected)

If Cogny isn't connected, skip this and note what connecting adds: real conversion rates by device and source (GA4/Plausible), where visitors get stuck (Clarity), and what was already tested (GrowthBook).

Call `mcp__cogny__list_integrations` once and skip whatever isn't connected.

• **GA4:** `mcp__cogny__mcp__Google_Analytics_4__tool_run_report` with `property_id`, `date_ranges` (last 28 days), `dimensions: ["landingPagePlusQueryString", "deviceCategory", "sessionSourceMedium"]`, `metrics: ["sessions", "engagementRate", "keyEvents", "sessionKeyEventRate"]`, filtered to the page path. Check `tool_list_conversion_events` so you know which key events count.
• **Plausible:** `mcp__cogny__mcp__Plausible__breakdown` (`site_id`, `dimension: "visit:entry_page"`, `metrics: ["visitors", "bounce_rate", "conversion_rate"]`, `date_range: "30d"`). Conversion rate needs a goal filter, e.g. `filters: [["is", "event:goal", ["Signup"]]]`.
• **Clarity:** call `mcp__cogny__mcp__Microsoft_Clarity__get_api_quota` first (10 requests/day), then `get_live_insights` with `num_of_days: 3`, `dimensions: ["URL", "Device"]`, `metrics: ["Scroll Depth", "Rage Click Count", "Dead Click Count", "Quickback Click"]`. Dead clicks on a non-link element or a scroll depth that ends above the CTA are direct evidence for a top-5 change. Heatmaps and recordings aren't in the API; tell the user where to look in Clarity.
• **GrowthBook:** `mcp__cogny__mcp__GrowthBook__list_experiments`, then `get_experiment_results` for any experiment on this page. Don't recommend a variant that already lost.

Mobile vs desktop gaps from this data take priority over heuristic scores in step 7.

6. Competitive comparison

W