skills-weekly（技能周刊）

OpenClaw Skills Weekly

Automated pipeline for tracking trending ClawHub skills and generating YouTube-ready video scripts in the GitHubAwesome format.

What This Skill Does

1. ClawHub API Discovery — Fetches all ~13K skills from GET https://clawhub.ai/api/v1/skills with cursor pagination. No auth required.
2. SQLite Time-Series Snapshots — Records daily metrics (installs, downloads, stars) to build 7-day velocity history.
3. Two-Track Ranking — MOVERS (established skills, 30+ days, ranked by install velocity) and ROCKETS (new skills <30 days, with recency bonus). Author diversity cap prevents one author from dominating.
4. Content Harvesting — Fetches documentation and author info from ClawHub detail API for top-ranked skills.
5. YouTube Script Generation — Generates GitHubAwesome-style video segments via Claude Haiku: hook-first, technical specs, no popularity metrics, dry newscast tone.
6. Dual Output — Markdown report (.md) + voice-ready video script (.txt).

Commands

Parse the user's request and route to the correct mode:

Full Pipeline (Weekly Report)

First, install dependencies if not already present:

cd "${SKILL_ROOT}" && pip install -r requirements.txt --quiet 2>/dev/null || pip3 install -r requirements.txt --quiet

Then run the full pipeline:

cd "${SKILL_ROOT}" && python3 run_weekly.py --top 10 --episode ${EPISODE_NUM:-1}

Replace ${EPISODE_NUM} with the episode number the user specifies, or default to 1.

If the user says --skip-x or doesn't want X/Twitter capture, add --skip-x:

cd "${SKILL_ROOT}" && python3 run_weekly.py --top 10 --skip-x --episode ${EPISODE_NUM:-1}

What this produces:

• openclaw_weekly_YYYYMMDD.md — Data-rich markdown report with metrics, rankings, and scripts
• openclaw_weekly_YYYYMMDD_script.txt — Voice-ready video script in GitHubAwesome format

Present both file paths to the user when done.

Expected output:

============================================================
  OpenClaw Skills Weekly — Full Pipeline (v4)
  Week of Mar 01, 2026
============================================================
  PHASE 1: X/Twitter Signal Capture
  PHASE 2: ClawHub Data Pipeline
  [1/5] Discovering ClawHub skills...
  [2/5] Saving snapshot...
  [3/5] Ranking by 7-day velocity...
  [4/5] Harvesting content...
  [5/5] Generating YouTube scripts...
  DONE:
    Report: openclaw_weekly_20260301.md
    Script: openclaw_weekly_20260301_script.txt

Snapshot Only (Daily Cron)

For daily snapshot accumulation without script generation:

cd "${SKILL_ROOT}" && python3 run_weekly.py --snapshot-only --skip-x

Tell the user how many skills were captured and how many snapshot dates exist in the DB.

Quick Trending

Show what's trending from existing DB data without re-fetching:

cd "${SKILL_ROOT}" && python3 main.py --list-db

Status

cd "${SKILL_ROOT}" && python3 main.py --list-db

Shows: DB path, total snapshot rows, distinct dates, top skills by current installs.

CLI Options Reference

Environment Variables

Video Script Format

Scripts follow the GitHubAwesome "GitHub Trending Weekly" format:

• Cold open: "It is time for OpenClaw Skills Weekly, episode number N..."
• Per-skill segments (~20 sec each): Hook first → technical specs → sharp closer
• No popularity metrics in narration (no download/install/star counts)
• Dry, confident newscast tone — no hype, no superlatives
• No outro — last item ends the episode

Architecture

run_weekly.py          # Full pipeline orchestrator
main.py                # Alternative CLI with --list-db
discovery.py           # ClawHub API cursor pagination (~13K skills)
storage.py             # SQLite time-series (slug-scoped dedup, CTE velocity)
ranker.py              # Two-track: Movers + Rockets, author diversity cap
harvester.py           # ClawHub detail API content + author extraction
script_generator.py    # LLM script gen + markdown + video script rendering
community_signals.py   # X/Twitter signal loading and rendering
x_capture.py           # xAI x_search API integration
data/metrics.db        # SQLite database (auto-created)