SkillHub

google-trends-rss

v1.0.2

Fetch and structure Google Trends daily trending-search data by country/region via the public RSS feed. Use when users ask for Google Trends snapshots, country comparisons, top daily searches, related news context, or export-ready trend tables (JSON/CSV/markdown) for Sheets/docs/reporting.

Sourced from ClawHub, Authored by Joe Wong

Installation

Please help me install the skill `google-trends-rss` from SkillHub official store. npx skills add wsjwong/google-trends-rss

Google Trends

Use this skill to get Google Trends daily trending searches quickly, without browser scraping.

Quick start

python scripts/google_trends_rss.py list-geos
python scripts/google_trends_rss.py daily --geo HK --limit 20 --sort traffic --format table
python scripts/google_trends_rss.py daily --geo US --sort traffic --format json --out /tmp/us-trends.json
python scripts/google_trends_rss.py daily --geo JP --sort traffic --out /tmp/jp-trends.csv

Workflow

  1. Pick geo code (HK, US, JP, etc.).
  2. Fetch daily trends with daily --geo <CODE>.
  3. Choose output format:
  4. table for terminal quick check
  5. json for downstream automation
  6. markdown for chat/report paste
  7. If needed, save with --out:
  8. .json for structured pipelines
  9. .csv for Sheets import

Commands

1) List common geo codes

python scripts/google_trends_rss.py list-geos

python scripts/google_trends_rss.py daily --geo HK --limit 20 --sort traffic --format table

Options: - --geo (required): region code - --limit (default 20): max trend rows - --format (table|json|markdown, default table) - --sort (traffic|feed|recency, default traffic) - traffic: hottest-first by approx_traffic - feed: keep RSS original order - recency: newest-first by pubDate - --out: optional file path (.json or .csv) - --timeout (default 20)

Output schema

Each trend includes: - title - approx_traffic - link - pub_date - picture - up to 2 related news items (title/snippet/url/source)

Notes

  • This skill targets daily trending searches feed (not full historical keyword timeseries).
  • Feed source: Google Trends RSS endpoint by geo.
  • Keep parsing defensive; feed fields can evolve.
  • For implementation details aligned to the existing connector repo, read:
  • references/google-trends-connector-notes.md

Resources

  • Script: scripts/google_trends_rss.py
  • Reference: references/google-trends-connector-notes.md