Improve Search Visibility Question Set skill

question-set

Reads: ../improve-search-visibility/references/question-list.md, ../improve-search-visibility/references/battlegrounds.md; brand summary, products, audience, competitors (gooseworks:brand_read, gooseworks:competitor_read); research-audience's research/audience/voc-bank.md and research-market's research/market/demand.md if present; customer language via gooseworks:knowledge_search with source_types: ["document", "evidence"] (query "Voice-of-customer bank — customer questions, objections, words customers use"); Search Console export if shared; the previous search/questions.md and search/page-map.md on re-runs.

Does: 0. Cover every audience the site sells to. If the site sells to more than one buyer or carries more than one positioning, include questions for each, so the decisions message can ask which buyer to win.

1. Re-run: reuse the saved set, then top it up to the mix — at least 3 brand-accuracy questions and every audience the site sells to — before anything runs; propose at most 3 other additions or swaps with reasons; keep ids stable — the same id always means the same words: a reworded question gets a new id and the old one is marked retired (reworded → Q<n>, v<N>), so the next run never compares different wordings.
2. First run: draft 18–20 candidates across the stage mix in both forms, never with the brand name in non-brand questions; 3–6 brand-accuracy questions always; local variants per city for physical businesses.
3. Score value (buying intent 1–5, ../improve-search-visibility/references/question-list.md) × winnability (1–3) provisionally with a one-line reason each; drop to the best 12–15. A brand name that is a common word always carries the category in brand questions. Pre-launch: category questions plus one name-collision question only.
4. Cluster and weight. Group the questions into clusters (one cluster = one page that should answer them); with a Search Console export, sum each cluster's impressions as its demand weight and add any high-impression query the list missed. These clusters are the page map's rows.
5. Pick the key questions yourself (the 3–5 highest value × winnability) and run the set — no approval before the free pass. The first message shows the set grouped by cluster for edits; edits apply to the paid top-up and the next runs.

Writes: search/questions.md in the saved-set format (version, date, country, language, engines, runs·route line, the table with a cluster column). Never: invents search volumes or "how many people ask this". Demand comes from Search Console, Google Trends or autocomplete (free), Keyword Planner when the brand shares it, or a vendor prompt-volume estimate the brand already has — always labelled with its source, estimates as estimates; otherwise "no demand data, ranked by judgment".