MR
Mayur Rathi
@github
⭐ 34.1k GitHub stars

Landing-Page-Conversion-Audit

Landing-Page-Conversion-Audit is an code AI skill with a core value of Audit a landing page, sales page or checkout page for conversion leaks and return a fix list ordered by expected revenue impact. It helps developers solve real-world problems in the code domain, boosting efficiency, automating repetitive tasks, and optimizing workflows.

Audit a landing page, sales page or checkout page for conversion leaks and return a fix list ordered by expected revenue impact. Use when asked to review, critique or improve a landing page, sales pag

Last verified on: 2026-10-06

Quick Facts

Category code
Works With GitHub Copilot, Claude
Source github/awesome-copilot
Stars ⭐ 34.1k
Last Verified 2026-10-06
Risk Level Low
mkdir -p ./skills/landing-page-conversion-audit && curl -sfL https://raw.githubusercontent.com/github/awesome-copilot/main/skills/landing-page-conversion-audit/SKILL.md -o ./skills/landing-page-conversion-audit/SKILL.md

Run in terminal / PowerShell. Requires curl (Unix) or PowerShell 5+ (Windows).

Skill Content

# Landing Page Conversion Audit


Audit a live page (or a mockup) for the things that actually move conversion rate on paid traffic, and return a ranked fix list. Do not return a generic "add more social proof" list - every finding must name the element, the failure mode, and what to change it to.


When to use


- "Review my landing page" / "why is my conversion rate so low"

- Paid traffic is running and CPA is above target

- Before scaling ad spend on a page that has never been audited

- A checkout page with a high add-to-cart-to-purchase drop-off


When not to use


- The page has no traffic yet - there is nothing to diagnose. Design the funnel and get traffic on it first; an audit needs behaviour to read.

- The problem is upstream (wrong audience, wrong offer). A page audit cannot fix a broken offer; say so and stop.


Procedure


1. Gather what you are allowed to conclude from


Ask for, or fetch, in this order. Note explicitly which you did not get, because it caps what you can claim:


| Input | What it unlocks |

|---|---|

| Page URL | Everything below (fetch and read the rendered DOM, not just the HTML source) |

| Traffic source + a sample ad / keyword | Message-match check, the single highest-impact finding |

| Sessions and conversions over the last 14-30 days | Whether the problem is statistically real or noise |

| Funnel step drop-off numbers | Which step to audit at all |

| Device split | Whether to audit mobile-first (usually yes: paid social is 70-90% mobile) |


If you only have the URL, say so in the output and mark every quantitative claim as an estimate.


2. Run the checks


Work in this order. It is ordered by how much revenue each typically moves, not by how easy it is to check.


**A. Message match (ad → page)**

- Does the page headline repeat the ad's promise in the ad's own words? A mismatch here caps everything downstream and is the most common single leak on paid traffic.

- Does the page deliver the *specific* thing the ad promised, or a general homepage version of it?

- Is the offer visible without scrolling on a 390x844 viewport?


**B. Above the fold, mobile**

- One clear promise, one clear CTA. Count the competing CTAs - more than one primary action is a leak.

- Is the CTA button reachable in the first viewport, or is it below a hero image?

- Load: is anything meaningful painted before ~2.5s LCP? Slow hero video/images on paid social is a silent 10-30% loss.


**C. Offer clarity**

- Can a stranger answer, in 5 seconds: what is it, who is it for, what does it cost, what happens when I click?

- Price presented, or hidden? Hiding price is only correct for high-ticket / call-booking funnels.

- Risk reversal present (guarantee, trial, "cancel anytime", shipping/returns)?


**D. Friction in the form**

- Count the fields. Every field past the minimum costs conversions. Ask for each: is this needed *now*, or can it be collected after payment?

- Is the checkout on the same page as the offer, or is there an extra click/redirect?

- Are payment methods visible before the user commits? Mobile wallets (Apple Pay / PayPal) present?

- Does the form validate inline, or dump errors on submit?


**E. Trust at the moment of payment**

- Trust elements next to the button, not stranded in the footer: guarantee, secure-payment mark, real reviews with names, return policy.

- Are testimonials specific and attributable, or anonymous filler? Anonymous filler reads as fake and costs more than it earns.


**F. The path after the button**

- Is there a next step (upsell / order bump / thank-you with instructions), or does the funnel dead-end at "thanks"? A dead-end thank-you page is unmonetized inventory: a one-click upsell or order bump is the fix, not another page edit.

- Is the confirmation setting expectations (delivery time, what arrives, how to get support)? Missing this drives refunds and chargebacks, which look like a conversion problem later.


**G. Measurement (check this even though it is not a conversion leak)**

- Is a

🎯 Best For

  • Engineering teams doing code reviews
  • Open source maintainers
  • GitHub Copilot users
  • Claude users
  • Software engineers

💡 Use Cases

  • Reviewing pull requests for security vulnerabilities
  • Checking code style consistency
  • Code quality improvement
  • Best practice enforcement

📖 How to Use This Skill

  1. 1

    Install the Skill

    Copy the install command from the Terminal tab and run it. The SKILL.md file downloads to your local skills directory.

  2. 2

    Load into Your AI Assistant

    Open GitHub Copilot or Claude and reference the skill. Paste the SKILL.md content or use the system prompt tab.

  3. 3

    Apply Landing-Page-Conversion-Audit to Your Work

    Open your project in the AI assistant and ask it to apply the skill. Start with a small module to verify the output quality.

  4. 4

    Review and Refine

    Review AI suggestions before committing. Run tests, check for regressions, and iterate on the skill output.

❓ Frequently Asked Questions

Does this skill check for OWASP Top 10?

Security-focused review skills often include OWASP checks. Check the skill content for specific vulnerability categories covered.

Is Landing-Page-Conversion-Audit compatible with Cursor and VS Code?

Yes — this skill works with any AI coding assistant including Cursor, VS Code with Copilot, and JetBrains IDEs.

Do I need specific dependencies for Landing-Page-Conversion-Audit?

Check the install command and Works With section. Most code skills only require the AI assistant and your codebase.

How do I install Landing-Page-Conversion-Audit?

Copy the install command from the Terminal tab and run it. The skill downloads to ./skills/landing-page-conversion-audit/SKILL.md, ready to use.

Can I customize this skill for my team?

Absolutely. Edit the SKILL.md file to add team-specific instructions, examples, or workflows.

⚠️ Common Mistakes to Avoid

Blindly accepting AI suggestions

Always verify AI-generated review comments. Some suggestions may not apply to your specific codebase conventions.

Skipping validation

Always test AI-generated code changes, even for simple refactors.

Missing dependency updates

Check if the skill requires updated dependencies or new packages.

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