betting
Betting analysis — odds conversion, de-vigging, edge detection, Kelly criterion, arbitrage…
Formula 1 data — race schedules, results, lap timing, driver and team info. Powered by the FastF1 library. Covers F1 sessions, qualifying, practice, race results, sector times, tire strategy. Use when: user asks about F1 race results, qualifying, lap times, driver stats, team
$ npx -y skills add machina-sports/sports-skills --skill fastf1 --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/fastf1Context preview
The summary Claude sees to decide when to auto-load this skill.
Formula 1 data — race schedules, results, lap timing, driver and team info. Powered by the FastF1 library. Covers F1 sessions, qualifying, practice, race results, sector times, tire strategy. Use when: user asks about F1 race results, qualifying, lap times, driver stats, team
name: fastf1 description: | Formula 1 data — race schedules, results, lap timing, driver and team info. Powered by the FastF1 library. Covers F1 sessions, qualifying, practice, race results, sector times, tire strategy. Use when: user asks about F1 race results, qualifying, lap times, driver stats, team info, the F1 calendar, or Formula 1 data. Don't use when: user asks about other motorsports (MotoGP, NASCAR, IndyCar, WEC, Formula E). Don't use for F1 betting odds or predictions — use kalshi or polymarket instead. Don't use for F1 news articles — use sports-news instead. license: MIT compatibility: "Requires Python 3.10+ (install with: pip install sports-skills)" metadata: author: machina-sports version: "0.1.0"
Before writing queries, consult `references/api-reference.md` for endpoints, ID conventions, and data shapes.
Prefer the CLI — it avoids Python import path issues:
sports-skills f1 get_race_schedule --year=2025 sports-skills f1 get_race_results --year=2025 --event=Monza
Python SDK (alternative):
from sports_skills import f1 schedule = f1.get_race_schedule(year=2025) results = f1.get_race_results(year=2025, event="Monza")
CRITICAL: Before calling any data endpoint, verify:
Derive the current year from the system prompt's date (e.g., `currentDate: 2026-02-16` → current year is 2026).
1. `get_race_schedule --year=<year>` — find the event name and date 2. `get_race_results --year=<year> --event=<name>` — final classification (positions, times, points) 3. `get_lap_data --year=<year> --event=<name> --session_type=R` — lap-by-lap pace analysis 4. `get_tire_analysis --year=<year> --event=<name>` — strategy breakdown (compounds, stint lengths, degradation)
1. `get_championship_standings --year=<year>` — championship context (points, wins, podiums) 2. `get_team_comparison --year=<year> --team1=<t1> --team2=<t2>` OR `get_driver_comparison --year=<year> --driver1=<d1> --driver2=<d2>` 3. `get_season_stats --year=<year>` — aggregate performance (fastest laps, top speeds)
1. `get_race_schedule --year=<year>` — full calendar with dates and circuits 2. `get_championship_standings --year=<year>` — driver and constructor standings 3. `get_season_stats --year=<year>` — season-wide fastest laps, top speeds, points leaders 4. `get_driver_info --year=<year>` — current grid (driver numbers, teams, nationalities)
| Command | Description | |---|---| | `get_race_schedule` | Full season calendar with dates and circuits | | `get_race_results` | Final race classification (positions, times, points) | | `get_session_data` | Raw session info (Q, FP1, FP2, FP3, R) | | `get_driver_info` | Driver details from the grid | | `get_team_info` | Team info with driver lineup | | `get_lap_data` | Lap-by-lap timing with sectors and tire data | | `get_pit_stops` | Pit stop durations and team averages | | `get_speed_data` | Speed trap and intermediate speed data | | `get_championship_standings` | Driver and constructor championship standings | | `get_season_stats` | Aggregate season performance | | `get_team_comparison` | Team head-to-head: qualifying, race pace, sectors | | `get_driver_comparison` | Driver head-to-head: qualifying H2H, race H2H, pace delta | | `get_tire_analysis` | Tire strategy, stint lengths, degradation rates |
See `references/api-reference.md` for full parameter lists and return shapes.
Example 1: F1 calendar User says: "Show me the F1 calendar" Actions: 1. Derive year from `currentDate` 2. Call `get_race_schedule(year=<derived_year>)` Result: Full calendar with event names, dates, and circuits
Example 2: Driver race performance User says: "How did Verstappen do at Monza?" Actions: 1. Derive year from `currentDate` (or from context) 2. Call `get_race_results(year=<year>, event="Monza")` for final classification 3. Call `get_lap_data(year=<year>, event="Monza", session_type="R", driver="VER")` for lap times Result: Finishing position, gap to leader, fastest lap, and tire strategy
Example 3: Latest results queried in pre-season User says: "What were the latest F1 results?" (asked in February 2026) Actions: 1. Current month is February → season not yet started → use `year = 2025` 2. Call `get_race_schedule(year=2025)` to find the last event of that season 3. Call `get_race_results(year=2025, event=<last_event>)` for the final race results Result: Results of the final 2025 race
If a command is not listed in the Commands table above, it does not exist.
Error: Event name not found Cause: Event name spelling does not match FastF1's internal naming Solution: Call `get_race_schedule(year=<year>)` first to get the exact event names, then retry with the correct name
Error: Session data is empty Cause: The session has not happened yet Solution: FastF1 only returns data for completed sessions. Check `get_race_schedule` fo
Open-source agent skills for live sports data and prediction markets. Built for the Agent Skills spec. Works with sportsclaw, OpenClaw, Claude Code, Cursor, Copilot, Gemini CLI, Hermes Agent, and every major AI agent. Zero API keys. Zero signup.
Betting analysis — odds conversion, de-vigging, edge detection, Kelly criterion, arbitrage…
College Basketball (CBB) data via ESPN public endpoints and the NCAA's official endpoints —…
College Football (CFB) data via ESPN public endpoints and the NCAA's official endpoints —…
Cricket data via ESPN public endpoints and Cricsheet open data — live-ish series scoreboards,…
Esports data — Dota 2 (OpenDota) and League of Legends esports (Leaguepedia). Pro matches,…
Football (soccer) data across the world's major leagues — standings, schedules, match stats,…