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 shawnpang/startup-founder-skills --skill landing-pagegit clone --depth 1 https://github.com/shawnpang/startup-founder-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/shawnpang/startup-founder-skills/landing-page)<a href="https://agentmods.dev/skills/shawnpang/startup-founder-skills/landing-page"><img src="https://agentmods.dev/badge/skills/shawnpang/startup-founder-skills/landing-page/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/shawnpang/startup-founder-skills/landing-page"><img src="https://agentmods.dev/badge/skills/shawnpang/startup-founder-skills/landing-page.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 | $0.00037 | $0.01675 |
| Opus 5 | $0.00018 | $0.00838 |
| Sonnet 5 | $0.00007 | $0.00335 |
| Haiku 4.5 | $0.00004 | $0.00168 |
Grade A, and why
landing-page 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- landing-page — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 84 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Landing Page
When to Use
- Creating a new landing page from scratch (product launch, feature page, waitlist).
- Auditing an existing page for conversion rate optimization (CRO).
- Rewriting headlines, CTAs, or hero sections.
- Structuring page sections for a specific audience and traffic source.
- Generating A/B test variants for copy or layout changes.
Context Required
- From startup-context: product description, ICP (ideal customer profile), value proposition, competitive positioning, stage, tone of voice.
- From the user: page URL or current copy (if auditing), page type (homepage, landing page, pricing, feature, blog), primary conversion goal (signup, demo, purchase, subscribe, download), traffic source (organic, paid, email, social), any existing conversion data or user research.
Workflow
- Identify page type and conversion goal -- Every page gets one primary conversion action. Determine whether this is a homepage, landing page, pricing page, feature page, or blog post -- each has a different CRO framework.
- Assess value proposition clarity -- Can a visitor understand what this is and why they should care within 5 seconds? Check whether copy is benefit-focused (good) or feature-focused (common problem). Ensure it is written in the customer's language, not company jargon.
- Evaluate headline effectiveness -- Does the headline communicate the core value proposition? Is it specific enough to be meaningful? Does it match the traffic source's messaging? Apply headline patterns:
- Outcome-focused: "Get [desired outcome] without [pain point]"
- Specificity: Include numbers, timeframes, or concrete results
- Social proof: "Join [N] teams who [achieve outcome]"
- Direct address: "You [do painful thing]. There's a better way."
- Audit CTA placement, copy, and hierarchy -- Is there one clear primary action visible without scrolling? Does button copy communicate value, not just action? ("Start my free trial" beats "Submit"). Check CTA hierarchy: primary vs. secondary, repeated at key decision points.
- Check visual hierarchy and scannability -- Can someone scanning the page get the main message? Are the most important elements visually prominent? Is there sufficient whitespace? Do images support or distract from the message?
- Evaluate trust signals and social proof -- Look for: customer logos (especially recognizable ones), testimonials with specifics and attribution, case study snippets with real numbers, review scores, security badges. Place trust signals near CTAs and after benefit claims.
- Identify objection handling -- Are common objections addressed? Price/value concerns, "will this work for me?", implementation difficulty, "what if it doesn't work?" Address through FAQ sections, guarantees, comparison content, process transparency.
- Find friction points -- Too many form fields, unclear next steps, confusing navigation, required fields that should not be required, poor mobile experience, slow load times.
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 · 84 lines · 37 tokens per session scan A 364768188b81
landing-page is a skill published in the GitHub repository shawnpang/startup-founder-skills (321 stars, last pushed 6mo ago), licensed MIT. It adds 37 tokens to every session and 1,675 once invoked, about $0.0002 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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