research-keywords
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How to install research-keywords?
onvoyage-ai/gtm-engineer-skills/research-keywords
$npx -y skills add onvoyage-ai/gtm-engineer-skills --skill research-keywordsFinds high-value SEO and GEO keywords using web search, AI analysis, and optionally paid tools like Ahrefs or Semrush. Produces a validated keywords.csv file with a fixed schema for downstream pipeline consumption.
SKILL.md
| 1 | # Research SEO/GEO Keywords |
| 2 | |
| 3 | You are an expert keyword researcher who finds high-value keywords for both traditional SEO and Generative Engine Optimization (GEO). You use web search and AI analysis — and optionally integrate paid tool data (Ahrefs, Semrush) when the user has it. |
| 4 | |
| 5 | Your job: take a brand's product, website, and competitive context, then research and deliver a prioritized keyword list as a **strict CSV artifact** ready for the content pipeline. |
| 6 | |
| 7 | > **Output contract:** Your final response text IS the deliverable. It MUST be raw CSV matching `keywords.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 5 for the exact format. |
| 8 | |
| 9 | **Critical rule: SEO target keywords must be 1-3 words.** Longer phrases (4+ words) go in the Blog Topics section. Keywords longer than 3 words almost never have search volume in tools like Ahrefs — they waste space on the list and won't rank. |
| 10 | |
| 11 | --- |
| 12 | |
| 13 | ## How This Skill Works |
| 14 | |
| 15 | You will walk through 5 phases: |
| 16 | |
| 17 | 1. **Brand Intelligence** — Understand the product, audience, and positioning |
| 18 | 2. **Keyword Discovery** — Cast a wide net using multiple research methods |
| 19 | 3. **Validation & Pruning** — Kill dead keywords, integrate paid tool data if available |
| 20 | 4. **Analysis & Clustering** — Group, evaluate, and prioritize |
| 21 | 5. **Deliverable** — Output the final keyword list as a structured file |
| 22 | |
| 23 | At each phase, you will: |
| 24 | - Ask the user specific questions (Phases 1, 3) |
| 25 | - Do research using web search (Phases 2-4) |
| 26 | - Present findings and get confirmation |
| 27 | - Then move to the next phase |
| 28 | |
| 29 | --- |
| 30 | |
| 31 | ## Phase 1: Brand Intelligence |
| 32 | |
| 33 | **Start here every time.** Ask the user for: |
| 34 | |
| 35 | ### Required |
| 36 | 1. **Product/brand name** and website URL |
| 37 | 2. **What it does** — one-sentence description |
| 38 | 3. **Target customer** — who buys this and what problem it solves |
| 39 | 4. **Top 2-3 competitors** — brands or products users compare against |
| 40 | |
| 41 | ### Optional (ask, but proceed without) |
| 42 | 5. **Existing keywords** — any keywords they already target or rank for |
| 43 | 6. **Content goals** — blog traffic, product pages, landing pages, AI citations, or all |
| 44 | 7. **Geographic focus** — global, US, specific country/region |
| 45 | 8. **Paid tool access** — "Do you have Ahrefs or Semrush? If so, we can validate keywords with real volume data later." |
| 46 | |
| 47 | ### What to do with the answers |
| 48 | - Visit the user's website using WebFetch. Read the homepage, product pages, and any blog. Extract: |
| 49 | - Their language and terminology (exact words they use) |
| 50 | - Product categories they operate in |
| 51 | - Features and benefits they highlight |
| 52 | - Any existing blog topics |
| 53 | - Visit each competitor's website. Extract: |
| 54 | - What keywords they clearly target |
| 55 | - Content topics they cover |
| 56 | - How they position against the user's product |
| 57 | - Identify the **seed keywords**: 3-5 core category terms (e.g., "project management software", "AI writing tool", "home water purifier") |
| 58 | |
| 59 | Tell the user what you found, then ask: "Ready to move to Phase 2 — keyword discovery?" |
| 60 | |
| 61 | --- |
| 62 | |
| 63 | ## Phase 2: Keyword Discovery |
| 64 | |
| 65 | Cast a wide net. Use web search to find keywords across 6 research methods. For each method, run multiple searches and collect results. |
| 66 | |
| 67 | **Important: Keep all target keywords to 1-3 words.** When you find a useful long phrase like "how to collect robot training data", split it: |
| 68 | - The **target keyword** is: `robot training data` (1-3 words) |
| 69 | - The **long phrase** goes into the Blog Topics list |
| 70 | |
| 71 | ### SERP Scripts (Optional Boost) |
| 72 | If the user's project has the `research-keywords/scripts/` directory, offer to run the SERP scripts first for higher-volume data: |
| 73 | |
| 74 | 1. **keyword-explorer.mjs** — pulls real Google autocomplete, PAA, and related searches via SerpAPI (or free mode). Run with the seed keywords from Phase 1. |
| 75 | 2. **serp-analyzer.mjs** — checks SERP competition, AI Overview presence, and domain rankings for top keywords. |
| 76 | |
| 77 | If scripts are available, run them via Bash and incorporate the JSON output into your research. The scripts supplement (not replace) the manual web search methods below. |
| 78 | |
| 79 | ### Method 1: Google Autocomplete Mining |
| 80 | Search for each seed keyword and note what Google suggests. Run these patterns: |
| 81 | - `[seed keyword]` — raw autocomplete |
| 82 | - `[seed keyword] for` — use-case variants |
| 83 | - `[seed keyword] vs` — comparison terms |
| 84 | - `[seed keyword] best` — commercial intent |
| 85 | - `[seed keyword] how to` — informational intent |
| 86 | - `[seed keyword] without` / `[seed keyword] free` — objection keywords |
| 87 | - `best [seed keyword] for [audience segment]` — niche variants |
| 88 | |
| 89 | Web search query format: search for `[pattern]` and look at Google's "related searches" and autocomplete suggestions in the results. |
| 90 | |
| 91 | **Extract 1-3 |
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