landing-page-conversion-audit

landing-page-conversion-audit is a skill for Claude Code from autonnel/autonnel-skills. It costs 90 tokens per session (1,693 once invoked), scanned A, original, Apache-2.0.

An instruction set for reviewing a landing page, sales page, or checkout page for problems that reduce purchases or sign-ups. It returns a ranked list of fixes based on expected revenue impact.

In plain words
What is it for?
Use it to review a live page or mockup, investigate low conversion rates, assess paid-traffic message matching, or diagnose drop-offs between adding a product to the cart and buying.
Why use it?
It connects each finding to a specific page element, the way it may lose customers, and a proposed change. It also limits its conclusions when there is no traffic or when the underlying offer is the real problem.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the autonnel plugin — 6 skills shipped together

Good fit Use it to review a live page or mockup, investigate low conversion rates, assess paid-traffic message matching, or diagnose drop-offs between adding a product to the cart and buying.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/autonnel/autonnel-skills/landing-page-conversion-audit
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add autonnel/autonnel-skills --skill landing-page-conversion-audit
Clone the repo
git clone --depth 1 https://github.com/autonnel/autonnel-skills

Made for: Claude Code.

Or install autonnel, the plugin that ships this one along with the rest of its 6 skills.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for landing-page-conversion-audit

README.md
[![agentmods](https://agentmods.dev/badge/skills/autonnel/autonnel-skills/landing-page-conversion-audit/github.svg)](https://agentmods.dev/skills/autonnel/autonnel-skills/landing-page-conversion-audit)
Your own site
<a href="https://agentmods.dev/skills/autonnel/autonnel-skills/landing-page-conversion-audit"><img src="https://agentmods.dev/badge/skills/autonnel/autonnel-skills/landing-page-conversion-audit/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for landing-page-conversion-audit

Your own site · 80×15
<a href="https://agentmods.dev/skills/autonnel/autonnel-skills/landing-page-conversion-audit"><img src="https://agentmods.dev/badge/skills/autonnel/autonnel-skills/landing-page-conversion-audit.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 90 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,693 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • Socket pass 6 Aug 2026
  • Snyk fail 6 Aug 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00090 $0.01693
Opus 5 $0.00045 $0.00847
Sonnet 5 $0.00018 $0.00339
Haiku 4.5 $0.00009 $0.00169

Measured 13d ago against content hash 90d4d54d0372, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

landing-page-conversion-audit scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 13d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

landing-page-conversion-audit/SKILL.md · 123 lines

How it starts

The opening of the file, as written. The whole thing — 123 lines — stays where its author put it; the contents beside it link to each section on GitHub.

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. Use sales-funnel-blueprint to design it instead.
  • 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?

Read the full file on GitHub · 123 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 13d ago First seen · 123 lines · 90 tokens per session scan A 90d4d54d0372

Subscribe to this mod's changes

landing-page-conversion-audit is a skill published in the GitHub repository autonnel/autonnel-skills (2 stars, last pushed 24d ago), licensed Apache-2.0. It adds 90 tokens to every session and 1,693 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.