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.
npx skills add autonnel/autonnel-skills --skill landing-page-conversion-auditgit clone --depth 1 https://github.com/autonnel/autonnel-skillsWrote 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.
[](https://agentmods.dev/skills/autonnel/autonnel-skills/landing-page-conversion-audit)<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.
<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>- Socket pass
- Snyk fail
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.
| Model | Per session | Once 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 |
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.
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-blueprintto 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?
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.
- 13d ago First seen · 123 lines · 90 tokens per session scan A 90d4d54d0372
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.
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