dataforseo
Skill708 starsChanged 5 months agoMITView on GitHub
Keyword & SERP research via the DataForSEO API — search volume, competition, CPC, keyword ideas for naming/SEO decisions
- Reads credentials
2 other projects use a version of this.
Adopted by
Most recently taken up by
- alinaqi/maggyword for word, first seen Jun 12, 2026
- nikhilbhansali/dataforseo-skill-claudetheir own version, first seen Jan 27, 2026
Other versions2 projects use a version of this.
Word for word · 1
- alinaqi/maggy★ 711100% same
Edited · 0
None found.
Wrote their own version · 1
- nikhilbhansali/dataforseo-skill-claude★ 63same name
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository75 other files it gives its agents.
- templates/AGENTS.mdAGENTS.md
- CLAUDE.mdCLAUDE.md
- templates/CLAUDE.mdCLAUDE.md
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- The first 60 shown.
The file
We split this skill into the rules it gives an agent
2 rules. About 0 are common, 1 is distinctive, and 1 is very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈1
Distinctive · estimate
This author's own choices. Worth a look.
1
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Very specific: line 65
Check whoami for balance before large runs.
- Distinctive: line 77
All take the same Basic-auth header.
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
DataForSEO Skill — keyword & SERP research
Purpose: Get real search demand (monthly volume, competition, CPC) and keyword ideas from Google Ads data via DataForSEO, so naming and content decisions are grounded in data rather than intuition.
Auth (never commit the key)
DataForSEO uses HTTP Basic auth. Provide credentials via environment only:
export DATAFORSEO_LOGIN="you@example.com"
export DATAFORSEO_PASSWORD="…"
# or a single combined value:
export DATAFORSEO_API_KEY="login:password" # or its base64The helper reads these from the env — it never hardcodes or logs the secret,
and only ever calls api.dataforseo.com. Keep the key in a local .env that is
git-ignored; do not paste it into the repo, a URL, or chat.
Usage
The helper is dataforseo.py in this skill folder:
DFS="$(cat ~/.claude/.bootstrap-dir)/skills/dataforseo/dataforseo.py"
python3 "$DFS" whoami # auth check + balance
python3 "$DFS" volume "claude code" "coding agent" # search volume table
python3 "$DFS" ideas "coding agent" # related keyword ideas
# options: --location <code, default 2840=US> --language <code, default en>volume → each keyword's monthly search volume, competition (LOW/MEDIUM/HIGH),
and CPC. ideas → the searched long-tail around a seed.
Reading the results (naming decisions)
- Zero /
n/avolume on every candidate is itself the answer: the names aren't search terms, so SEO can't rank them against each other — decide on clarity/brand and accept that discovery happens on GitHub/HN/X, not search. - Category term vs. brand term: a huge-volume category word (e.g. the tool's ecosystem name) is where demand lives; a brand name rides it only if it contains it. Weigh discoverability against being on-brand for what you built.
- Wrong-intent volume is a trap: a candidate with existing volume may be drawing an audience searching for something else (a different industry meaning). That volume hurts, it doesn't help.
- Competition + CPC proxy commercial intent, not just popularity — high CPC means advertisers pay for that term (buyers), low CPC often means informational or noise.
Cost & etiquette
live endpoints bill per call (search volume / ideas ≈ $0.05–0.10 each). Batch
many keywords into ONE volume call (it accepts up to 1000) rather than looping.
Check whoami for balance before large runs.
Common endpoints (beyond the helper)
| Need | Endpoint |
| Search volume | keywords_data/google_ads/search_volume/live |
| Keyword ideas | keywords_data/google_ads/keywords_for_keywords/live |
| SERP (who ranks) | serp/google/organic/live/advanced |
| Ranked keywords for a domain | dataforseo_labs/google/ranked_keywords/live |
| Competitor domains | dataforseo_labs/google/competitors_domain/live |
All take the same Basic-auth header; POST a JSON array of task objects.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

