📡 22B Labs · Open Source Release

Trend Collection Doesn't Fail Because You Can't Find Data

Short-Trend-Rader (trend-radar) — Collect YouTube, Reddit, Google Trends, and RSS signals once. Leave them as Markdown for humans, JSON for tools.

📅 April 2026 · v0.2.1 ✍️ 22B Labs ⏱ 5 min read

Most trend workflows don't fail because people can't find data. They fail because the handoff is messy. One person collects links, another writes notes somewhere else, a third has to search the web again later. By then, the timing is gone.

trend-radar exists to reduce that gap. It collects public trend signals from YouTube, Reddit, Google Trends, and RSS once, then leaves them behind as Markdown for humans and JSON for tools — in the same place, every time.

"A good system is not the one that collects the most noise.
It is the one that gives signal a place to survive."

📌 Naming Note

The GitHub repository is named Short-Trend-Rader, but the Python package and CLI are named trend-radar. In the terminal, you type trend-radar.

architecture

4-Layer Structure

LAYER 1

collectors

Per-platform collection modules: YouTube, Reddit, Google Trends, RSS, Naver DataLab.

LAYER 2

runner

Orchestrator: selects collectors, runs in parallel, deduplicates, normalizes shared fields.

LAYER 3

outputs

Writes Markdown, JSON, and digest files to ~/.22b/trends.

LAYER 4

cli

init, run, status, digest, doctor entry points.

data sources

Collection Sources

DEFAULT

▶️ YouTube

Trending and Shorts-like items from public pages

DEFAULT

💬 Reddit

Public subreddit JSON endpoints

DEFAULT

📈 Google Trends

RSS as stable path, pytrends as fallback

DEFAULT

📰 Generic RSS

Add any RSS/Atom feed you care about

OPTIONAL

🇰🇷 Naver DataLab

Activates when API keys are set

📌 Not yet supported — TikTok, Instagram, X/Twitter, Whisper transcription, and long-running daemon mode are later steps. Intentionally deferred to keep the default path stable at release time.

outputs

Output Files — ~/.22b/trends

File	Purpose
feeds/<platform>/YYYY-MM-DD.json	Structured platform data (for tools)
feeds/<platform>/YYYY-MM-DD.md	Per-platform summary (for humans)
digest/daily-YYYY-MM-DD.md	Daily brief across all collected data
index.json	Shared summary index for 22B Labs tools
run-state.json	Last run metadata + per-collector warnings

Both Markdown and JSON exist for a reason. Markdown increases human judgment speed. JSON lowers integration cost between tools. If you only keep one, the other usually reappears later in a messier form.

installation

Install — One Command

# Clone git clone https://github.com/sinmb79/Short-Trend-Rader.git cd Short-Trend-Rader # Linux / macOS chmod +x setup.sh && ./setup.sh # Windows setup.bat # When done, open http://localhost:5678 # n8n workflows are already imported and ready

💡 What setup.sh / setup.bat handles automatically
Python package install → n8n install → n8n start → workflow import. All in one run.

commands

Key Commands

• trend-radar initCreate config.yaml interactively
• trend-radar run --onceRun one collection pass and write output files
• trend-radar statusShow last run time, active platforms, item count
• trend-radar digest todayPrint a readable digest from today's data
• trend-radar doctorCheck Python, config, output path, env vars
• trend-radar config showShow merged effective configuration

n8n integration

n8n Integration

n8n doesn't replace the CLI — it wraps a solid CLI in repeatable, connectable workflows. The n8n/ directory includes two import-ready workflows.

n8n/workflow.json # Main collection: manual + webhook + scheduled n8n/workflow-digest.json # Daily digest generation workflow n8n/README.md # Setup, import, path edits, security guide

Get Started on GitHub

MIT License · Completely Free · Python 3.11+
v0.2.1 · YouTube / Reddit / Google Trends / RSS / Naver DataLab
n8n workflows included

🔗 View on GitHub

#TrendRadar #TrendIntelligence #YouTubeTrends #Reddit #GoogleTrends #n8n #OpenSource #Python #CLI #22BLabs #The4thPath

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22B Labs · The 4th Path GitHub: sinmb79 · the4thpath.com
The 4th Path: ⟨H⊕A⟩ ↦ Ω — Human × AI → a better world.