| name | leaderboard |
| version | 1.3.0 |
| description | Track AI model leaderboard rankings over time and detect rank/score changes between snapshots |
Leaderboard Snapshot Tracker
Track AI model leaderboard rankings over time using SQLite snapshots. Detect new models, removed models, rank changes, and score changes between dates.
Supported Leaderboards
Usage
Save a snapshot
cd {SKILL_DIR} && python3 skills/leaderboard/scripts/leaderboard_snapshot.py save \
--leaderboard "chatbot-arena" \
--date 2026-04-14 \
--data '[{"model": "claude-4-opus", "rank": 1, "score": 1350}]'
Prints the diff against the previous snapshot (new models, rank changes, score changes).
View latest snapshot
cd {SKILL_DIR} && python3 skills/leaderboard/scripts/leaderboard_snapshot.py latest \
--leaderboard "chatbot-arena"
Data Storage
Snapshots are stored in ~/.cache/morning-ai/leaderboard.db (SQLite). Each entry has:
leaderboard — leaderboard identifier
model — model name
rank — position on the leaderboard
score — numeric score (ELO, accuracy, etc.)
snapshot_date — date of the snapshot
Integration with Main Workflow
This skill is currently a standalone utility. It can be integrated into the main morning-ai workflow as a Benchmark data source:
- As a collector: Scrape leaderboard pages → save snapshot → diff against previous → generate
TrackerItem entries for rank changes
- As a report section: Add a "Leaderboard Movement" section to the daily report showing rank/score deltas
To integrate, a collector module (lib/leaderboard_collector.py) would:
- Fetch current leaderboard data from supported sites
- Call
save_snapshot() to persist
- Call
diff_snapshot() to detect changes
- Convert significant changes (new #1 model, big rank jumps) into
TrackerItem objects with Benchmark type