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.
git clone --depth 1 https://github.com/thatrebeccarae/claude-marketingWrote 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/rules/thatrebeccarae/claude-marketing/landing-page-optimizer)<a href="https://agentmods.dev/rules/thatrebeccarae/claude-marketing/landing-page-optimizer"><img src="https://agentmods.dev/badge/rules/thatrebeccarae/claude-marketing/landing-page-optimizer/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/rules/thatrebeccarae/claude-marketing/landing-page-optimizer"><img src="https://agentmods.dev/badge/rules/thatrebeccarae/claude-marketing/landing-page-optimizer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00055 | $0.00992 |
| Opus 5 | $0.00028 | $0.00496 |
| Sonnet 5 | $0.00011 | $0.00198 |
| Haiku 4.5 | $0.00006 | $0.00099 |
Grade A, and why
landing-page-optimizer 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 10d 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 — 111 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Landing Page Optimizer
Audit and optimize landing pages for maximum conversion.
Audit Framework
Above the Fold (First 5 Seconds)
The visitor must answer 3 questions instantly:
- What is this? (Clear headline)
- Why should I care? (Benefit-focused subheadline)
- What do I do next? (Visible CTA)
Hero Layout Patterns
| Pattern | Best For | Structure |
|---|---|---|
| Left copy / right visual | SaaS, B2B | Headline + CTA left, product screenshot right |
| Centered hero | Simple offers | Centered headline, subheadline, CTA |
| Video hero | Complex products | Autoplay background or embedded explainer |
| Social proof hero | High-trust needed | Headline with customer logos or metrics |
| Split test | Dual audiences | Two distinct paths with separate CTAs |
Value Proposition Hierarchy
H1: Primary benefit (what outcome they get)
Subheadline: How you deliver it (mechanism or differentiator)
Supporting points: 3 proof points or features (bullets)
CTA: Specific action + anxiety reducer
CTA Optimization
Text: Action verb + specific outcome ("Start Free Trial" not "Submit") Design: High contrast to background, generous padding, whitespace around it Placement: Above fold, after each content section, sticky on scroll Microcopy: Reduce anxiety below CTA ("No credit card required", "Cancel anytime")
Social Proof Patterns
| Type | Placement | Impact |
|---|---|---|
| Customer logos | Below hero | Trust (B2B) |
| Metric ("50,000+ users") | Near headline | Scale proof |
| Star rating | Near CTA | Purchase confidence |
| Testimonial quote | Mid-page | Emotional proof |
| Case study result | Deep in page | Detailed proof |
| Trust badges | Near form/checkout | Security |
Form Optimization
- Every field removed increases completion 5-10%
- Labels above fields (never placeholder-only)
- Inline validation (real-time, not on submit)
- Smart defaults and autofill (autocomplete attributes)
- Multi-step forms outperform single long forms
- Progress indicator for multi-step
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.
- 10d ago First seen · 111 lines · 55 tokens per session scan A 153b4b2c2fb7
landing-page-optimizer is a cursor rule published in the GitHub repository thatrebeccarae/claude-marketing (134 stars, last pushed 3mo ago), licensed MIT. It adds 55 tokens to every session and 992 once invoked, about $0.0003 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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