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SKILL verified MIT Self-run

Keyword Research

skill-nachoal-my-skills-keyword-research · by nachoal

Run public-safe DataForSEO keyword research, SERP checks, competitor discovery, backlink opportunity analysis, gap analysis, and SEO brief planning. Use when Codex is asked for keyword research, niche validation, search demand, CPC/difficulty data, competitor domains, content gaps, backlink prospects, SEO topic prioritization, or article briefs using DataForSEO credentials.

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Install

$ agentstack add skill-nachoal-my-skills-keyword-research

✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.

Security review

✓ Passed

No issues found. Passed automated security review. · v0.1.0 How review works →

  • ✓ Prompt-injection patterns
  • ✓ Secret / credential exfiltration
  • ✓ Dangerous shell & filesystem operations
  • ✓ Untrusted network calls
  • ✓ Known-malicious package signatures

What it can access

  • ✓ Network access No
  • ✓ Filesystem access No
  • ✓ Shell / process execution No
  • ✓ Environment & secrets No
  • ✓ Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

View the full security report →

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Reliability & compatibility

✓ Security review passed
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Declared compatibility

Claude CodeClaude Desktop

Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.

Preview Execution monitoring

We're building live execution health for every listing: tool-call success rate, median latency, uptime, and last-checked timestamps, measured, not self-reported. It isn't live yet, so we don't show numbers we can't stand behind.

How agent discovery & health will work →
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About

Keyword Research

Use the bundled DataForSEO helper:

python3 scripts/dataforseo_keyword_research.py --help

Start with the smallest paid call that answers the question. Run --dry-run first when the scope or cost is unclear, and pass --yes only after the user asked for live DataForSEO data.

Default Flow

  1. Seed demand: keyword-overview, keyword-ideas, related-keywords, or google-ads-volume.
  2. SERP proof: serp-check for representative commercial terms.
  3. Competitors: competitors from a known domain, or use SERP domains when no seed domain exists.
  4. Competitor keywords: ranked-keywords / research.
  5. Offline analysis: gap-analysis, then briefs only if content planning is requested.
  6. Link building: backlink-opportunities only when outreach/link acquisition is in scope.

Common Commands

python3 scripts/dataforseo_keyword_research.py keyword-overview \
  --keywords "local seo services,seo automation" \
  --location 2840 --language en --dry-run

python3 scripts/dataforseo_keyword_research.py serp-check \
  --keywords "local seo services,seo automation" \
  --location 2840 --language en --yes

python3 scripts/dataforseo_keyword_research.py competitors \
  --target example.com --limit 20 --yes

python3 scripts/dataforseo_keyword_research.py ranked-keywords \
  --target example.com --limit 200 --yes

python3 scripts/dataforseo_keyword_research.py gap-analysis \
  --input dataforseo-results/ranked-keywords-latest.json \
  --min-volume 100 --max-difficulty 40

Rules

  • Use DATAFORSEO_LOGIN and DATAFORSEO_PASSWORD; never ask for or print secret values.
  • Keep examples generic unless the user provides a real project, domain, locale, or niche.
  • Pass locale explicitly for non-US/non-English work, for example Mexico/Spanish: --location 2484 --language es.
  • Review live SERP results before recommending a content plan.
  • Treat generated briefs as planning artifacts; do not publish content without a separate content-quality workflow.

Resources

  • Workflow guide: references/workflow.md
  • API surface map: references/dataforseo-endpoints.md
  • Helper script: scripts/dataforseo_keyword_research.py

Read references/workflow.md when choosing command order. Read references/dataforseo-endpoints.md when you need endpoint coverage, payload shape, or cost/safety notes.

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

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Versions

  • v0.1.0 Imported from the upstream source.

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