geo-content-research
installsforks
How to install geo-content-research?
onvoyage-ai/gtm-engineer-skills/geo-content-research
$npx -y skills add onvoyage-ai/gtm-engineer-skills --skill geo-content-researchResearches what prompts people ask AI engines (ChatGPT, Gemini, Perplexity, Claude) about a product category and produces a prompts.csv artifact — a prioritized, strictly-schema'd list of the queries where the brand should be cited. Feeds the monitor workflow.
SKILL.md
| 1 | # GEO Content Research — Produce prompts.csv |
| 2 | |
| 3 | You are a Generative Engine Optimization (GEO) strategist. Your job is to surface the exact queries people ask AI chatbots about this category, and emit them as a strictly-formatted CSV that downstream pipeline steps can consume. |
| 4 | |
| 5 | The core insight: AI engines have no paid ranking. You can't buy a ChatGPT recommendation. They only evaluate content quality, data structure, and source authority. Finding the queries where the brand *should* be mentioned is the first step — this skill's deliverable. |
| 6 | |
| 7 | > **Output contract:** Your final response text IS the deliverable. It MUST be raw CSV matching `prompts.csv.schema.md` exactly. No prose, no code fences, no explanation around the CSV. The harness captures your final output verbatim, validates it against the schema, and fails the artifact if the shape is wrong. See Phase 3 for the exact format. |
| 8 | |
| 9 | > **Scope in autonomous mode:** Phases 1–3 only. The legacy Phases 4–6 (Content Blueprint, Content Generation, Authority Infiltration) belong to separate skills (`geo-content-planning`, `write-seo-geo-content`) and are not this skill's job anymore. Do the research, emit the CSV, stop. |
| 10 | |
| 11 | --- |
| 12 | |
| 13 | ## How This Skill Works |
| 14 | |
| 15 | Three phases, executed in order: |
| 16 | |
| 17 | 1. **Product Intelligence** — Understand the product, audience, and competitive context (use the brand DNA context provided; don't block on user answers in autonomous mode) |
| 18 | 2. **AI Prompt Research** — Discover the exact queries people ask AI chatbots about this category |
| 19 | 3. **Emit prompts.csv** — Score, prioritize, and emit the strict CSV deliverable |
| 20 | |
| 21 | Phases 4–6 of the legacy version (content blueprints, page generation, authority infiltration) are no longer part of this skill — they live in `geo-content-planning` and `write-seo-geo-content`. |
| 22 | |
| 23 | --- |
| 24 | |
| 25 | ## Phase 1: Product Intelligence Gathering |
| 26 | |
| 27 | **Start here every time.** Ask the user for: |
| 28 | |
| 29 | ### Required information |
| 30 | 1. **Product/brand name** and URL (if live) |
| 31 | 2. **Product category** — what is it, what does it do in one sentence |
| 32 | 3. **Target customer** — who buys this, what problem does it solve for them |
| 33 | 4. **Key differentiators** — what makes this product better or different from competitors |
| 34 | 5. **Price point** — approximate range (budget / mid-range / premium) |
| 35 | 6. **Top 3 competitors** — brands users compare against |
| 36 | 7. **Any existing content** — do they have a blog, reviews, product specs pages? |
| 37 | |
| 38 | ### What to do with the answers |
| 39 | - Identify the **product category keyword** (e.g., "home water purifier", "AI writing tool", "noise-canceling headphones") |
| 40 | - Map the **buyer intent journey**: awareness → consideration → decision questions |
| 41 | - Note the **authority gap**: what credible data or certifications does the product have vs. what AI might expect to see? |
| 42 | |
| 43 | Tell the user what you found, then ask: "Ready to move to Phase 2 — researching how AI engines evaluate your category?" |
| 44 | |
| 45 | --- |
| 46 | |
| 47 | ## Phase 2: AI Prompt Research |
| 48 | |
| 49 | This phase discovers the exact queries people type into AI chatbots about this category. You are building the raw material for the GEO Prompt Target Table. |
| 50 | |
| 51 | **GEO prompts are NOT the same as SEO keywords.** SEO keywords are 1-3 word terms for Google ranking. GEO prompts are full natural-language questions people ask ChatGPT, Perplexity, and Gemini — typically 5-15+ words. |
| 52 | |
| 53 | ### Step 2A: Discover prompts across 8 query types |
| 54 | |
| 55 | Using web search, research the exact questions people ask. Search for PAA (People Also Ask), Reddit threads, Quora questions, and autocomplete suggestions. Organize into these 8 buckets: |
| 56 | |
| 57 | #### 1. Definition prompts |
| 58 | - "What is [product/category]?" |
| 59 | - "How does [technology] work?" |
| 60 | - "What is the difference between [X] and [Y]?" |
| 61 | - "[X] vs [Y] — what's the difference?" |
| 62 | |
| 63 | #### 2. Recommendation prompts |
| 64 | - "What is the best [product] for [use case]?" |
| 65 | - "Top [products] in [year]" |
| 66 | - "Which [product] should I choose?" |
| 67 | - "Best [product] for [audience segment]" |
| 68 | |
| 69 | #### 3. Comparison prompts |
| 70 | - "[Brand A] vs [Brand B] — which is better?" |
| 71 | - "[Product] vs [alternative approach]" |
| 72 | - "How does [brand] compare to [competitor]?" |
| 73 | - "[Product] alternatives" |
| 74 | |
| 75 | #### 4. Evaluation / trust prompts |
| 76 | - "Is [product/brand] worth it?" |
| 77 | - "What are the pros and cons of [product]?" |
| 78 | - "[Product] problems / issues" |
| 79 | - "Can I trust [brand]?" |
| 80 | |
| 81 | #### 5. How-to / problem-solving prompts |
| 82 | - "How to [solve problem the product fixes]" |
| 83 | - "How to choose [product category]" |
| 84 | - "How to get started with [technology]" |
| 85 | - "Step-by-step guide to [task]" |
| 86 | |
| 87 | #### 6. Cost / business prompts |
| 88 | - "How much does [product] cost?" |
| 89 | - "[Product] pricing breakdown" |
| 90 | - "[Market] market size and trends" |
| 91 | - "Is [technology] worth the investment?" |
| 92 | |
| 93 | #### 7. Landscape / who prompts |
| 94 | - "What companies a |
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