Individual skill
semantic-core
Build a measured semantic core for a brand through official keyword APIs (Yandex Wordstat for RU, Google Ads Keyword Planner / Bing Webmaster worldwide, autocomplete everywhere), commit it as core.json plus a questions.csv, and hand that straight to an open-geo visibility run. Use when the user wants demand research, a semantic core, keyword volume, or "collect the questions and then measure visibility" — no browser and no manual keyword tool.
.grok/skills/semantic-core/SKILL.md
Source commit 97bd17024393df10804ae90f719d81af1d306d9f
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- Last checked
- Nov 11, 2026
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- Repository last updated
- Oct 24, 2026
- License
- MIT
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- aeo-optimization Repository topic
- answer-engine-optimization Repository topic
- claude Repository topic
- generative-engine-optimization Repository topic
- geo Repository topic
- ai-visibility Repository topic
- brand-monitoring Repository topic
- chatgpt Repository topic
- deepseek Repository topic
- gemini Repository topic
- marketing Derived category
- research Derived category
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# semantic-core — measured demand core, then the run
You are the orchestrator for one **core build**: find what people actually search around a product,
**measure it through the platforms' own APIs**, cluster it by intent, write the assistant-style
questions each cluster justifies, commit the whole thing as a `core.json` + `questions.csv`, and hand
that to an **open-geo** visibility run.
Two halves, deliberately separated:
- **Deterministic** — the numbers. `demand/` asks Wordstat / Google Ads / Bing / autocomplete and
returns each figure *with its scope* (region, period, pull date). No browser, no logged-in session,
no hand-typed volume. Contract: `pipeline/INTERFACES.md §8`, guide: `demand/README.md`.
- **Agentic** — the judgement. Which angles the product has, how a person phrases the need to an
assistant, which lines survive a skeptic. Authority: `harvest/METHODOLOGY.md` (§3 demand gate,