Search terms
Skill foxgeeek/adskills/.claude/skills/google-ads/search-terms
Extract Google Ads search terms report and classify by intent (commercial, informational, navigational, unknown) using PT/EN keyword hints. Triggers on prompts about search terms, intent analysis, or finding keyword opportunities.From its SKILL.md
npx -y skills add foxgeeek/adskills --skill search-termsAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
One thing to look at
- 0 stars0 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.
SKILL.md
1.3 KB, 261 tokens by cl100k_base, as published. Nobody here has run it
Google Ads — Search Terms
When to use
- "Quais search terms estão vindo na conta?"
- "Classifica os search terms por intenção"
- "Find commercial intent search terms I should add as keywords"
Inputs
--account— account ref--campaign— optional campaign scope--lookback— days (default 30)
Classification
- Commercial — PT/EN purchase-intent words (comprar, preço, contratar, buy, price, hire, ...)
- Informational — PT/EN how/what/guide words (como, tutorial, how to, guide, ...)
- Navigational — login/entrar/site
- Unknown — everything else (review manually)
Output
- 5 summary cards (one per intent)
- 4 tables (50 rows each) sorted by clicks
- Columns: term, campaign, clicks, impr, CTR, cost, conv
Invocation
adskills google search-terms --account acme --lookback 30
Guardrails
- Read-only
- Intent classifier is naive keyword-hint matching — always sanity-check before acting on "unknown" bucket
What ships with it
Read from the repository
Just SKILL.md. No reference files, no scripts.
Gives 0 of the 12 instructions most marketing audience skills give in 261 tokens
Counted across 690 of the 894 authors here whose files we hold, read 2026-08-07
- Apply Poppins font to headingsin 41 of 690, across 6 files
- Apply Lora font to body textin 41 of 690, across 6 files
- Use Arial fallback for headingsin 39 of 690, across 4 files
- Use Georgia fallback for body textin 39 of 690, across 4 files
- Maintain text hierarchy and formattingin 39 of 690, across 4 files
- Use accent colors for non-text shapesin 38 of 690, across 3 files
- Use RGB values for precise color matchingin 38 of 690, across 3 files
- Use brand colors for primary text and backgroundsin 36 of 690, across 1 file
- Read product marketing context file before asking questions, starting, or auditingin 35 of 690, across 23 files
- Use active voice instead of passive voicein 26 of 690, across 10 files
- Implement or generate appropriate JSON-LD structured datain 24 of 690, across 17 files
- Prioritize clarity over clevernessin 22 of 690, across 8 files
Said here and by no other author read
- scope queries by account campaign and lookback days
- classify commercial intent using purchase words
- classify informational intent using how or guide words
- classify navigational intent using login or site words
- label unclassified terms as unknown
- generate one summary card per intent bucket
Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once. Length counted with cl100k_base; the agent that loads this file may tokenize it differently.