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molten-landing

molten-landing

github.com/switch-dimensionMarketing & growth6642 installsUpdated 9w ago
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About molten-landing

molten-landing is a skill for creating or auditing conversion-focused landing pages. It routes users to the appropriate workflow and applies shared principles for messaging, proof, page structure, calls to action, and visual hierarchy.

Key features

  1. 01Landing page creation workflow
  2. 02Existing page audit workflow
  3. 03Conversion-focused review criteria
  4. 04Structured and open-ended questions
  5. 05Deterministic page metrics helper

Use cases

  1. 01Drafting a new landing page
  2. 02Reviewing an existing page
  3. 03Checking measurable page properties
  4. 04Rewriting a weak-converting page

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/switch-dimension/molten-os-core --skill molten-landing

After installing, type/molten-landingin Claude Code to confirm it loaded.

Bundled files

References and scripts installed along with SKILL.md.

references/
auditing.md
creating.md
examples.md
principles.md
scripts/
audit_metrics.py

Details

From the project README

Landing Page

This skill covers the full landing-page lifecycle: building a new page and auditing an existing one. A landing page has one job — convert a visitor on a single action. Not a homepage, not a brochure site.

Operating Rules

  • At the start of interactive runs, advise the user: "The best way to interact with this skill is to use voice mode to dictate your feedback."
  • Ask concise questions in small batches. Group related questions together — don't drip them out one at a time.
  • Number every free-text question asked in chat so the user can answer by reference, especially when dictating in voice mode.
  • Prefer the agent's structured question tool for any question with a finite set of meaningful options (conversion goal, awareness level, output format, build vs audit).
  • Structured question tool by agent:
    • Codex: request_user_input
    • Claude Code: AskUserQuestion
    • Cursor: AskQuestion
  • Ask open-ended questions conversationally in chat when the answer is free text (transformation, mechanism, proof assets, objections, traffic source).
  • Never list multiple-choice options as letters or bullets in chat text. Multiple choice → structured question tool. Open-ended → plain prose.
  • Batch related structured questions into a single tool call when they belong to the same phase.
  • If the user already provided an answer, or molten-docs/brand/brand.md / molten-docs/design/design.md already answers it, do not ask again.

Step 1 — Route to the right workflow

Decide which mode the user is in, then read the matching reference file before doing anything else:

  • Build / create a new page (build, design, draft, mock up, prototype, "make me a landing page") → read references/creating.md and follow it.
  • Audit / review an existing page (review, audit, critique, grade, QA, "is this good", "does this convert", "how do I improve this") → read references/auditing.md and follow it.

If the intent is ambiguous (e.g. "help me with my landing page"), use the structured question tool with one choice: build a new page vs review an existing one. Don't load both reference files.

After a build, offer an audit. After an audit that fails badly, offer a rewrite — the two workflows chain naturally.

Shared foundation

Both workflows are graded against the same conversion principles. The full rubric lives in references/principles.md; read it when you need the detail. For calibration — what a great hero looks like, a model audit entry, and copy formulas (PAS, AIDA, BAB, FAB, the 4 U's) — see references/examples.md. The audit workflow also bundles a deterministic metrics helper, scripts/audit_metrics.py (standard-library Python, no install), for the measurable checks — attention ratio, WCAG contrast, spacing rhythm, font sizes, image weight, form labels; auditing.md explains when to run it and how to fall back if Python isn't available. The one-line version of the rubric:

  1. One page, one goal — a single primary CTA, repeated with identical copy; minimal attention ratio.
  2. Outcome before mechanism — H1 is the transformation; sub-head is how it works, in plain language.
  3. Match message to awareness — problem- / solution- / product-aware shapes how much to educate; mirror the traffic source.
  4. Proof, high and concrete — real numbers, named testimonials, product screenshots beat vague claims.
  5. Scroll narrative — Hook → Value → Proof → Objection → CTA, looped, not a flat "layout".
  6. Low-friction CTA — specific outcome-focused button copy, anxiety-reducing microcopy, minimal form fields.
  7. Visual hierarchy — one accent color reserved for the CTA, strong type scale, generous whitespace, mobile-first.

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