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feature-optimiser

スター2
フォーク0
更新日2026年7月18日 09:30

Deterministically audit and optimise a published feature page on the register ladder: struggling-moment heroes with zero implementation jargon, mechanism evidence relocated to section bodies and dropdowns in the HashiCorp / Stripe / Tailscale register. Runs an 11-section quality audit plus register-ladder checks (hero jargon count, homepage narrative echo, struggling-moment opener, identifier-enumeration, established-not-indie voice) and applies 6 rewrite rules: claim verification, conversion clarity, brand discipline, and Technical-Marketing Synthesis (ten sub-checks: outcome headlines, jargon payoff scoped to sections/dropdowns, numbers with context, feature-to-outcome binding, narrative-vs-reference separation, skeptic test, named surfaces over coined metaphors, dropdown alignment, no Rust internals in narrative, dense sentences no filler). Penalises metaphor-stacking and marketing adjectives. Reads website analytics and GSC data per feature URL, produces a 90-point score delta (115 with analytics), commit

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