A lookup skill for NBA information from ESPN, the NBA's live data service, and NBA Stats. It covers games, teams, players, seasons, and historical records.

Use it to retrieve scores, standings, schedules, rosters, game summaries, play-by-play, injuries, futures, depth charts, leaders, news, advanced ratings, shot locations, career splits, and history back to 1946.

It brings common basketball data and deeper statistical information into one queryable source. This avoids manually checking separate sports websites and data services.

nba-data — Skill for Claude Code and Codex by machina-sports

Install

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.

Any agent

npx skills add machina-sports/sports-skills --skill nba-data

Clone the repo

git clone --depth 1 https://github.com/machina-sports/sports-skills

Made for: Claude Code, Codex.

Wrote 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.

README.md

[![agentmods](https://agentmods.dev/badge/skills/machina-sports/sports-skills/nba-data/github.svg)](https://agentmods.dev/skills/machina-sports/sports-skills/nba-data)

Your own site

<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.

Your own site · 80×15

<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>

Per session 170 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 3,046 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits

Socket pass 30 Sept 2026
Snyk warn 30 Sept 2026
NVIDIA SkillSpector pass 7 Sept 2026

How audits are shown

Origin original No closer match found in the catalogue.

Token cost

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	$0.03046
Opus 5.5	$0.00068	$0.01218
Sonnet 5.5	$0.00034	$0.00609
Haiku 4.5	$0.00017	$0.00305

Measured 9d ago against content hash 6fe24a860cf0, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

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 9d ago.

The scan reads SKILL.md. This mod also ships 1 executable file (scripts/validate_params.sh), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

skills/nba-data/SKILL.md · 238 lines

How it starts

The opening of the file, as written. The whole thing — 238 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:

For the current season, omit season/season_year on ESPN commands — never hardcode one.
If only a team name is provided, call get_teams to resolve the team ID before using team-specific commands.

Choosing the Season

ESPN names an NBA season by the year it ends: 2026-27 is 2027, so in February 2026 the current season is 2026.

If the user says "current", "this season", or doesn't specify: omit season/season_year. For get_leaders, get_futures, get_team_stats and get_player_stats, the default is a calendar-selected ending year, not necessarily a season with games yet: from October 1 the season ending next year, before October the one ending this year.
Between October 1 and opening night the default season may have no data. get_leaders can return empty or unavailable and does not fall back. get_futures, get_team_stats and get_player_stats retry the prior season only when ESPN returns an error (with a warnings note), not when it returns an empty successful payload.
If the user names a past season: pass its ending year (2024-25 → 2025). An explicitly requested season never falls back.
The get_nbastats_* commands use the starting year instead (see "Using ESPN and NBA Stats Together").

Read the full file on GitHub · 238 lines

Files

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.

Changes

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.

9d ago Changed · +19 lines 6fe24a860cf0
1mo ago Changed · +2 lines 1811604785d6
1mo ago Changed · +27 lines ee50b7159593
2mo ago Changed · +4 lines 81894b3e2eeb
2mo ago First seen · 186 lines · 170 tokens per session scan A 787feee5273e

Subscribe to this mod's changes

nba-data is a skill published in the GitHub repository machina-sports/sports-skills (264 stars, last pushed yesterday), licensed MIT. It adds 170 tokens to every session and 3,046 once invoked, about $0.0007 per session on Opus 5.5. 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.

Analytics and metrics Research

nba-data next to 6 skills from other repositories
Mod	Type	Stars	Last push	Licence	Scan	Tokens	Works with
nba-datamachina-sports/sports-skills	Skill	264	yesterday	MIT	A	170	Claude Code, Codex
imagegenopenai/codex	Skill	133k	yesterday	Apache-2.0	A	113	Codex
playwright-climicrosoft/playwright	Skill	99k	yesterday	Apache-2.0	A	19	Claude Code
local-ai-agentsmicrosoft/ai-agents-for-beginners	Skill	79k	4d ago	MIT	A	200	Claude Code, Codex
systematic-debuggingobra/superpowers	Skill	313k	3d ago	MIT	A	21	Claude Code
next-cache-components-adoptionvercel/next.js	Skill	143k	yesterday	MIT	A	95	Claude Code
next-partial-prefetching-adoptionvercel/next.js	Skill	143k	yesterday	MIT	A	103	Claude Code