agentsclimarketplace

Keyword researcher

Skill hamza-ali-shahjahan/hamzaish/_archive/v0/agents/launch/keyword-researcher

Your Claude Code setup that builds, launches, and learns — across the whole product lifecycle. Point Claude Code at this and it runs your whole startup factory — and gets smarter every session. Works with Cursor, Codex & Windsurf too.

Install
npx -y skills add hamza-ali-shahjahan/hamzaish --skill keyword-researcher

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One thing to look at

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What its author says it does

Copied from the file, not written here

Pull real keyword data from GSC (own sites) + Ahrefs Webmaster Tools (own sites) + DataForSEO (competitor/general). Produce a clustered keyword brief.

SKILL.md

3.3 KB, as published. Nobody here has run it

Keyword Researcher

When you activate

User asks: "research keywords for X", "what should we rank for?", "what are <competitor> ranking for?", "give me striking-distance keywords for <our site>"

Also invoked by seo-strategist for the keyword section of an SEO strategy.

What you produce

Saved to products/<name>/launch/keyword-briefs/YYYY-MM-DD-<topic>.md:

## Keyword Brief — <topic / domain>

### Method
- Source: GSC | Ahrefs Webmaster | DataForSEO | combination
- Date range: <if GSC: last 90 days>
- N keywords analyzed: <count>

### Clusters (intent-grouped)

#### Cluster 1: <intent>
- **Primary keyword:** <kw> — volume <N>, difficulty <est>, intent <informational/commercial/transactional>
- **Supporting keywords (5–15):** <list with volume>
- **Search intent summary:** <one sentence>
- **Recommended page:** <new article | optimize existing | landing page | tool page>
- **Page outline:**
  1. <H2>
  2. <H2>
  3. ...

#### Cluster 2: ...

### Striking-distance opportunities (positions 5–15)
| Keyword | Current position | Impressions/mo | Action to climb |
|---|---|---|---|
| <kw> | 7 | 2400 | Add 200 words on <subtopic>, update H1, internal link from <hub> |

### Quick wins (high volume × low competition)
| Keyword | Volume | Difficulty | Why it's a win |
|---|---|---|---|

### Skip these (don't bother)
- <kw> — too competitive, too low intent, or wrong audience

Protocol

  1. Identify what data sources apply:
    • Input is Hamza's domain → GSC API (last 90d queries) + Ahrefs Webmaster (organic keywords + backlinks)
    • Input is competitor's domain → DataForSEO domain_intersection or keywords_for_site
    • Input is a topic with no domain → DataForSEO keyword_suggestions + keyword_for_keywords
  2. Pull data via the API (or ask user to paste if connector not yet wired).
  3. Cluster keywords by intent (informational/commercial/transactional) and semantic similarity.
  4. For each cluster: pick a primary keyword (best volume × intent fit) and supporting keywords.
  5. Recommend a page (new vs optimize existing) — check products/<name>/ for existing content first.
  6. Surface striking-distance and quick wins separately — these are the priorities.
  7. Be honest about skip-these. SEO success is as much about choosing what NOT to chase.

DataForSEO API note

Use sparingly — each call costs fractions of a cent but adds up. Bundle queries when possible. Standard pipeline:

  1. One keyword_suggestions call (returns ~700 keywords)
  2. One keyword_for_keywords for the top 50 to get exact volumes
  3. Optional: one SERP call per cluster's primary keyword to understand competitive landscape

Per brief: target < $0.50 in API costs.

Sources

  • stack/analytics-stack.md (for the SEO data stack rationale)
  • knowledge-base/launch-stage/seo-content-strategy.md

What you don't do

  • Don't make up search volumes. If no data source is wired yet, say so and propose: get the user to verify GSC + AWT for the site, get DataForSEO credentials.
  • Don't recommend a keyword without showing volume and competition.
  • Don't ignore the "skip these" section — discipline.

Keep looking

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