Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add machina-sports/sports-skills --skill nba-datagit clone --depth 1 https://github.com/machina-sports/sports-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/machina-sports/sports-skills/nba-data)<a href="https://agentmods.dev/skills/machina-sports/sports-skills/nba-data"><img src="https://agentmods.dev/badge/skills/machina-sports/sports-skills/nba-data/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/machina-sports/sports-skills/nba-data"><img src="https://agentmods.dev/badge/skills/machina-sports/sports-skills/nba-data.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk pass
- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00170 | $0.02182 |
| Opus 5 | $0.00085 | $0.01091 |
| Sonnet 5 | $0.00034 | $0.00436 |
| Haiku 4.5 | $0.00017 | $0.00218 |
Grade A, and why
nba-data scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 7d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 190 lines — stays where its author put it; the contents beside it link to each section on GitHub.
NBA Data
Before writing queries, consult references/api-reference.md for endpoints, ID conventions, and data shapes.
Setup
Before first use, check if the CLI is available:
which sports-skills || pip install sports-skills
If pip install fails with a Python version error, the package requires Python 3.10+. Find a compatible Python:
python3 --version # check version
# If < 3.10, try: python3.12 -m pip install sports-skills
# On macOS with Homebrew: /opt/homebrew/bin/python3.12 -m pip install sports-skills
No API keys required.
Quick Start
Prefer the CLI — it avoids Python import path issues:
sports-skills nba get_scoreboard
sports-skills nba get_standings --season=2025
sports-skills nba get_teams
CRITICAL: Before Any Query
CRITICAL: Before calling any data endpoint, verify:
- Season year is derived from the system prompt's
currentDate— never hardcoded. - If only a team name is provided, call
get_teamsto resolve the team ID before using team-specific commands.
Choosing the Season
Derive the current year from the system prompt's date (e.g., currentDate: 2026-02-18 → current year is 2026).
- If the user specifies a season, use it as-is.
- If the user says "current", "this season", or doesn't specify: The NBA season runs October–June. If the current month is October–December, the active season year matches the current year. If January–June, the active season started the previous calendar year (use that year as the season).
Commands
| Command | Description |
|---|---|
get_scoreboard |
Live/recent NBA scores |
get_standings |
Standings by conference |
get_teams |
All 30 NBA teams |
get_team_roster |
Full roster for a team |
get_team_schedule |
Schedule for a specific team |
get_game_summary |
Detailed box score and scoring plays |
get_leaders |
NBA statistical leaders |
get_news |
NBA news articles |
get_play_by_play |
Full play-by-play for a game |
get_win_probability |
Win probability chart data |
get_schedule |
Schedule for a specific date or season |
get_injuries |
Injury reports across all teams |
get_transactions |
Recent transactions |
get_futures |
Futures/odds markets |
get_depth_chart |
Depth chart for a team |
get_team_stats |
Team statistical profile |
get_player_stats |
Player statistical profile |
find_nba_player |
Search the NBA Stats player registry (all eras) |
get_nbastats_game_log |
League game log via NBA Stats — history to 1946, carries NBA game ids |
get_nbastats_player_career |
Career stats season by season via NBA Stats |
get_nbastats_team_stats |
League team stats via NBA Stats — advanced ratings, pace, four factors |
get_nbastats_shot_chart |
Per-shot court coordinates via NBA Stats |
get_nbastats_play_by_play |
Play-by-play with coordinates for past seasons via NBA Stats |
get_nbastats_advanced_boxscore |
Advanced box score (ratings, usage) via NBA Stats |
get_live_scoreboard |
Real-time scores. Primary cdn.nba.com, fallback ESPN |
get_live_boxscore |
Real-time box score. Primary cdn.nba.com, fallback ESPN |
get_live_playbyplay |
Real-time play-by-play, most recent plays first |
get_player_live_stats |
Real-time stats for one player in today's games |
What ships with it
3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 7d ago Changed · +4 lines 81894b3e2eeb
- 13d ago First seen · 186 lines · 170 tokens per session scan A 787feee5273e
nba-data is a skill published in the GitHub repository machina-sports/sports-skills (218 stars, last pushed 5d ago), licensed MIT. It adds 170 tokens to every session and 2,182 once invoked, about $0.0009 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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