gh-radar

A daily email of the GitHub tools people are actually sharing — without touching the X API.

You saw mempalace on X and thought "how did I not know about this?". gh-radar is the cron job that makes sure you find the next one. Every morning it pulls the tools that are trending and being discussed, dedupes them, drops the ones you've already seen, and emails you a ranked digest.

It reads the places tools surface, across many angles. Six of the seven sources need no API key at all; only Reddit is opt-in. A Claude subscription (CLI or token) adds the Chinese summaries and resolves Chinese-prose tweets — without it the digest still ships in English.

Source	Signal	How	Key
GitHub Trending	star velocity — daily + weekly + per-language	public HTML	—
Hacker News	what devs are discussing now	Algolia API	—
GitHub Search	brand-new repos gaining stars	official API	—
Lobsters	curated programming community	hottest.json	—
X / Twitter	tools shared by curated accounts	Firecrawl scrape (free, keyless)	—
web articles	tool round-up listicles	Firecrawl search + scrape	—
Reddit	r/commandline, r/selfhosted, …	OAuth API	REDDIT_CLIENT_ID + REDDIT_CLIENT_SECRET

The X layer is the one that catches an already-popular tool being re-shared (the "I saw it on X" case). Chinese tool accounts rarely link GitHub directly — they describe the tool in prose — so the LLM extracts the tool name and a GitHub search, disambiguated by the star count mentioned in the post, resolves the real repo (e.g. "记忆宫殿 55K star" → MemPalace/mempalace). A free FIRECRAWL_API_KEY raises rate limits if the keyless tier starts returning 429s.

Each repo is scored (HN/X discussion weighted highest, novelty bonus, multi-source bonus), and a 14-day memory stops the same repo showing up every day. Any single source can fail or be disabled without affecting the rest.

Run it on GitHub Actions (recommended — laptop can be off)

The included workflow (.github/workflows/radar.yml) runs daily at 08:00 Taipei on GitHub's servers, emails you the digest, commits a browsable copy to digests/, and persists the de-dup memory in state/.

Setup — Repo → Settings → Secrets and variables → Actions, add:

Secret	Value
GMAIL_USER	your gmail address
GMAIL_APP_PASSWORD	a Gmail App Password (needs 2FA)

GITHUB_TOKEN is injected automatically (lifts the API limit to 5000/hr). Trigger a run any time from the Actions tab → gh-radar → Run workflow.

Run it locally instead

cd gh-radar
cp config.example.env config.env   # then fill in SMTP_PASS (Gmail App Password)
./run.sh                           # run once, prints to stdout if SMTP unset
./install.sh 8                     # schedule daily at 08:00 via cron

Zero pip dependencies — Python 3.9+ standard library only.

Sample output

gh-radar: collecting…
  trending: 120 repos
  hn: 91 repos
  new: 30 repos
  lobsters: 1 repos
  x: 3 repos
  ✓ X: 3 repo(s) resolved from prose tweets
  web: 12 repos
  ✓ Chinese summaries: 50/50
  ✓ emailed digest to you@example.com

### 1. [MemPalace/mempalace](https://github.com/MemPalace/mempalace)
⭐ 55,992 · 𝕏 @axichuhai

> 將 AI 長期記憶從摘要快取改造成可翻閱的檔案空間，本地運行、近乎零成本。
> _A memory palace for AI agents — a browsable archive replacing summary caches._

📍 出處 / via: Firecrawl → X @axichuhai

[X post](https://x.com/axichuhai/status/...)

Config

All via env (see config.example.env):

• GITHUB_TOKEN — recommended: lifts API limit 60→5000/hr. Without it, enrich rate-limits and only the Trending source survives.
• FIRECRAWL_API_KEY — optional: lifts Firecrawl's keyless 429 cap (X + web).
• CLAUDE_CODE_OAUTH_TOKEN — optional: enables Chinese summaries + X-prose resolution.
• SMTP_* / EMAIL_TO — Gmail App Password delivery (EMAIL_TO falls back to SMTP_USER).
• MIN_STARS (30), SEEN_TTL_DAYS (14), GH_RADAR_MAX_ITEMS (50), GH_RADAR_EVERGREEN_STARS (50000) — tuning.
• GH_RADAR_X_ACCOUNTS, GH_RADAR_SUBREDDITS, GH_RADAR_TREND_LANGS, GH_RADAR_FC_QUERIES — what each source watches.
• GH_RADAR_VAULT / GH_RADAR_DIGEST_DIR — also save each digest as Markdown.

Project layout

A single radar.py shim (keeps python radar.py working) over the gh_radar/ package:

gh_radar/
  config.py     constants, scoring weights (config.W), env helpers
  models.py     the Repo dataclass — typed core model (merge() rejects unknown keys)
  clients.py    github / firecrawl / claude / http — every call degrades to None
  sources.py    one src_*() per signal; SOURCES table; enrich()
  scoring.py    score() + evergreen-noise filter
  state.py      de-dup memory (seen.json), atomic writes
  render.py     zh summaries, Markdown digest, HTML
  email_out.py  SMTP delivery
  cli.py        collect → select → render → email → remember

Standard library only — zero pip dependencies.

Honest limitations

• GitHub Trending has no official API, so that source is an HTML scrape that can break on a redesign. The other six keep the digest alive if it does.
• No GITHUB_TOKEN = trending-only. Without a token the GitHub API rate-limits and every non-trending repo is dropped at the enrich step. CI injects one.
• X prose resolution needs Claude. Without the CLI/token, X keeps only tweets that link a repo directly; Chinese-prose tools are skipped (graceful).
• Web articles can over-list. A "best tools" listicle may surface a famous giant; the evergreen filter drops web-only repos ≥50k stars, but precision here is lower than the velocity sources.

How scoring works (config.W)

score = stars_today                       # trending velocity
      + 2 × hn_points                     # discussion = strong "people care" signal
      + 120 if shared on a curated X acct # a human you follow chose it — strongest
      + 15 × min(x_mentions, 5)
      + 0.02 × min(reddit_points, 1000)
      + 0.3 × min(lobsters_score, 200)
      + 25 if surfaced in a web article
      + 40 if brand-new repo              # novelty
      + 0.01 × min(stars, 5000)           # mild popularity tiebreak
      + 15 × (number of sources)          # multi-source = stronger signal

Top 50 by score go in the digest; a 14-day memory stops repeats.