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landing-page

Explicit landing-page build and deploy operator. Loads marketing and frontend judgment, scaffolds the smallest suitable site, verifies it rendered, deploys to the configured target.

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Files included (2)

  • SKILL.md3.5 KB
  • agents/openai.yaml220 B

SKILL.md (original)

Review the instructions the agent will receive before you install.

<skill id="landing-page"> <purpose> Build, verify, and optionally deploy a focused landing page. This is the explicit operator; strategy and aesthetics come from the methodology skills it composes. </purpose>

<skill_load> Load skills/marketing-site/SKILL.md and skills/frontend/SKILL.md before writing. </skill_load>

<inputs> Use answers already present in the request/repository. Resolve only what materially changes the build: audience, desired action, offer/proof, brand/assets, required content/legal pages, real CTA destination, domain, and deploy target. Never invent brand facts or proof.

For the unresolved inputs, run a structured interview with the AskUserQuestion tool (batched, up to 4 questions per round, recommended option first where evidence supports one) instead of guessing or asking loose prose questions. Bounded choices only; positioning and voice discussions stay prose. The interview method: skills/build/SKILL.md "The interview". </inputs>

<scaffold> - Follow the existing repository and stack first. For a new simple page, prefer static HTML/CSS with JavaScript only for real behavior; add a framework only when requirements earn it. - Build the content argument with `marketing-site`; build the visual system with `frontend`. - Add only the pages and integrations the brief needs. If forms, analytics, cookies, payments, embeds, or accounts touch data, create/update a privacy page that matches the real behavior. - Keep secrets and deploy credentials out of source. </scaffold> <verify-local> - Render and do visual QA at 375 / 768 / 1440 widths unless the product defines better targets. - Check hierarchy, realistic content, overflow, keyboard/focus, reduced motion, contrast, images, console errors, links, metadata, and CTA/form success plus error paths. - Confirm the privacy policy matches actual collection and third parties. - Run the repository's tests/build/lint and fix failures before deployment. </verify-local> <deploy> - Use the project's configured deploy command and provider. If none exists, choose the smallest provider-appropriate static deployment; Cloudflare Workers Static Assets is one option, not a universal default. - If the user already named the deploy target and asked to deploy, that counts as confirmation. Otherwise surface the resolved account/project/domain before the side effect. - After deploy, verify the live URL: status 200, headline/content marker, nested assets, legal page, and conversion path. Static assets can propagate briefly, so retry a short bounded check before diagnosing a successful deploy as broken. </deploy> <hard-stops> - No fabricated proof, shippable placeholders, fake form success, or dead CTA. - No secrets in committed source. - No “done” claim based only on source, build, commit, or deploy output; inspect the rendered page locally and the served page after deployment. </hard-stops>

<on_end> Report the live URL if deployed, target widths and paths checked, claims/proof source, privacy behavior, and any verification bar not observed. </on_end>

</skill>

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