pitch-landing

pitch-landing is a skill for Claude Code from tonone-ai/tonone. It costs 49 tokens per session (617 once invoked), scanned A, a copy of pitch-landing, MIT.

A landing-page planning skill that lays out the sections of a page around a product's position and audience. A landing page is a focused web page designed to explain an offer and prompt an action such as signing up.

In plain words
What is it for?
Use it to plan launch pages, product pages, and pages intended to turn visitors into customers or sign-ups. It produces an ordered page layout rather than the finished text.
Why use it?
It removes guesswork about what information the page should contain and where to place calls to action, proof, and answers to objections. It also connects the page structure to the product's message.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter.

Part of the marketing-team plugin — 12 skills shipped together

Good fit Use it to plan launch pages, product pages, and pages intended to turn visitors into customers or sign-ups. It produces an ordered page layout rather than the finished text.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/tonone-ai/tonone/pitch-landing
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 tonone-ai/tonone --skill pitch-landing
Clone the repo
git clone --depth 1 https://github.com/tonone-ai/tonone

Made for: Claude Code.

Or install marketing-team, the plugin that ships this one along with the rest of its 12 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 pitch-landing

README.md
[![agentmods](https://agentmods.dev/badge/skills/tonone-ai/tonone/pitch-landing/github.svg)](https://agentmods.dev/skills/tonone-ai/tonone/pitch-landing)
Your own site
<a href="https://agentmods.dev/skills/tonone-ai/tonone/pitch-landing"><img src="https://agentmods.dev/badge/skills/tonone-ai/tonone/pitch-landing/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 pitch-landing

Your own site · 80×15
<a href="https://agentmods.dev/skills/tonone-ai/tonone/pitch-landing"><img src="https://agentmods.dev/badge/skills/tonone-ai/tonone/pitch-landing.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 49 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 617 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.
Origin 100% copy Near-identical to another mod 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 $0.00049 $0.00617
Opus 5.5 $0.00020 $0.00247
Sonnet 5.5 $0.00010 $0.00123
Haiku 4.5 $0.00005 $0.00062

Measured 1mo ago against content hash 1a005eaac8d7, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

pitch-landing 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 1mo 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.

Origin

This is a copy

100% identical to pitch-landing — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

bundle/marketing-team/skills/pitch-landing/SKILL.md · 63 lines

How it starts

The opening of the file, as written. The whole thing — 63 lines — stays where its author put it; the contents beside it link to each section on GitHub.

pitch-landing — Launch & Positioning Landing Page

Follow the output format defined in docs/output-kit.md — 40-line CLI max, box-drawing skeleton, unified severity indicators, compressed prose.

When to use

User needs a landing page structured around product positioning, launch messaging, or conversion for a specific audience.

Workflow

  1. Identify product type and positioning anchor from user request or brief
  2. Search landing page patterns:
    python3 -m pitch_agent.uiux search --domain landing --query "{product_type}" --limit 3
    
  3. Search product reasoning for audience + messaging context:
    python3 -m pitch_agent.uiux search --domain product --query "{product_type}" --limit 3
    
  4. Layer in positioning: CTA strategy, social proof placement, objection handling
  5. Output section order with conversion and messaging optimization

Output format

┌─ Launch Landing Page — {product_type} ──────────────────────────────┐
│ #  │ Section            │ Purpose                    │ CTA?          │
├────┼────────────────────┼────────────────────────────┼───────────────┤
│  1 │ {section_name}     │ {purpose}                  │ Primary CTA   │
│  2 │ {section_name}     │ {purpose}                  │ —             │
│  3 │ {section_name}     │ {purpose}                  │ Secondary CTA │
│  … │ …                  │ …                          │ …             │
└────┴────────────────────┴────────────────────────────┴───────────────┘

CTA strategy:          {cta_strategy}
Social proof:          {social_proof_placement}
Objection handling:    {objection_section}
Positioning anchor:    {positioning_anchor}

Anti-patterns

  • Never structure copy without a clear positioning anchor (who it's for + what makes it different)
  • Never add sections that don't serve conversion or objection handling
  • Never place social proof after the primary CTA — it should reinforce before the ask
  • Never launch without a single, unambiguous primary CTA per viewport

Read the full file on GitHub · 63 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. 1mo ago First seen · 63 lines · 49 tokens per session scan A 1a005eaac8d7

Subscribe to this mod's changes

pitch-landing is a skill published in the GitHub repository tonone-ai/tonone (76 stars, last pushed 13d ago), licensed MIT. It adds 49 tokens to every session and 617 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to pitch-landing, differing in 0 lines, and is treated as a copy.

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