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Agent skill

Cbb Data

by machina-sports in machina-sports/sports-skills

College Basketball (CBB) data via ESPN public endpoints and the NCAA's official endpoints — scores, standings, rosters, schedules, game summaries, play-by-play, win probability, rankings, futures…

MITAuto-check passedData & Analytics

Install Cbb Data

skills CLI
$ npx skills add machina-sports/sports-skills --skill cbb-data -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install machina-sports/sports-skills cbb-data --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/machina-sports/sports-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/cbb-data .claude/skills/cbb-data && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
cbb-data
GitHub stars
245
Token cost
~2.2k tokens
SKILL.md length
994 words
Files
5 (incl. scripts, references)
Skills in repo
23
Repo updated
First seen
Licence
MIT

At a glance

College Basketball (CBB) data via ESPN public endpoints and the NCAA's official endpoints — scores, standings, rosters, schedules, game summaries, play-by-play, win probability, rankings, futures…

  • Works in 2 steps: Derive season year from currentDate → Call get_standings(group=23, season=)…
  • : user asks about college basketball scores
  • SKILL.md covers Setup, Quick Start, CRITICAL: Before Any Query and Choosing the Season, plus 7 more sections
  • Runs Shell scripts from its folder; calls pip and python3

What it does

Cbb Data is an agent skill from machina-sports/sports-skills. College Basketball (CBB) data via ESPN public endpoints and the NCAA's official endpoints — scores, standings, rosters, schedules, game summaries, play-by-play, win probability, rankings, futures, team/player stats, and news for Division I men's basketball, plus official D2/D3 scoreboards, NCAA game detail, the March Madness bracket with live scores, and the schools index. Zero config, no API keys. Use when: user asks about college basketball scores, March Madness, the NCAA tournament bracket, standings…

Its SKILL.md is about 2.2k tokens, which your agent loads only when the skill is triggered. The skill folder holds 6 other files, including scripts and reference files (for example `references/api-reference.md`, `references/conference-ids.md` and `references/team-ids.md`).

It sits in Data & Analytics, covering Statistics. It works with Python. The repository describes itself as: Open-source agent skills for live sports data and prediction markets. Football, F1, Kalshi, Polymarket. Zero API keys. SKILL.md format. The licence is MIT.

When your agent uses it

  • : user asks about college basketball scores
  • The NCAA tournament bracket
  • Betting futures
  • Team/player statistics

Example prompts

  • “/cbb-data”

Requirements

  • Python 3
  • A Bash shell

Workflow steps

2 steps, taken from the first numbered list in SKILL.md.

  1. Derive season year from currentDate
  2. Call get_standings(group=23, season=) (group 23 = SEC)

What it can do on your machine

Read from SKILL.md and the folder at commit 0420a7c. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 1 file in scripts/ (Shell), which the agent can run.

    Shell commands in SKILL.md call:

    • pip
    • python3

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md. Its commands use pip, which can reach the network depending on how they are called.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Cbb Data loads about 2.2k tokens when it runs, and up to ~4.1k if it reads all its reference files. Until then it costs about 189 tokens; SKILL.md has 994 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~189
When it runs · the whole SKILL.md, loaded when a task matches
~2.2k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~4.1k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from machina-sports/sports-skills at commit 0420a7c, republished under its MIT licence (© machina-sports). 994 words, ~2,234 tokens.

Download SKILL.mdSave it as .claude/skills/cbb-data/SKILL.md (or your agent's skills folder). This skill also uses 4 other files; get the full folder from GitHub.
name
cbb-data
description
College Basketball (CBB) data via ESPN public endpoints and the NCAA's official endpoints — scores, standings, rosters, schedules, game summaries, play-by-play, win probability, rankings, futures, team/player stats, and news for Division I men's basketball, plus official D2/D3 scoreboards, NCAA game detail, the March Madness bracket with live scores, and the schools index. Zero config, no API keys. Use when: user asks about college basketball scores, March Madness, the NCAA tournament bracket, standings, rankings, team rosters, schedules, play-by-play, betting futures, team/player statistics, CBB news, or D2/D3 games. Don't use when: user asks about NBA/WNBA (use nba-data/wnba-data), college football (use cfb-data), or non-sports topics.
license
MIT
metadata.author
machina-sports
metadata.version
0.1.0

College Basketball Data (CBB)

Before writing queries, consult references/api-reference.md for endpoints, conference IDs, team IDs, and data shapes.

Setup

Before first use, check if the CLI is available:

bash
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:

bash
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:

bash
sports-skills cbb get_scoreboard
sports-skills cbb get_rankings
sports-skills cbb get_standings --group=23

CRITICAL: Before Any Query

CRITICAL: Before calling any data endpoint, verify:

  • Season year is derived from the system prompt's currentDate — never hardcoded.
  • For standings, the group parameter is set to the correct conference ID (see references/api-reference.md).
  • If only a team name is provided, use get_teams to resolve the team ID.

Choosing the Season

Derive the current year from the system prompt's date (e.g., currentDate: 2026-02-28 → 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 CBB season runs November–April. If the current month is November or December, use season = current_year + 1. If January–April, use season = current_year. If May–October (offseason), use season = current_year (most recently completed season).

Important: College vs. Pro Differences

  • Standings are per-conference — use the group parameter to filter
  • Rankings replace leaders — college uses AP Top 25 and Coaches Poll
  • Ranked teams have a rank field (null = unranked) on scoreboard competitors
  • 360+ D1 teams — many games per day during the season (50+ during conference play)
  • March Madness — NCAA Tournament runs in March/April with 68 teams

Commands

CommandDescription
get_scoreboardLive/recent college basketball scores
get_standingsStandings by conference (use group parameter)
get_teamsAll 360+ D1 men's basketball teams
get_team_rosterFull roster for a team
get_team_scheduleSchedule for a specific team
get_game_summaryDetailed box score and player stats
get_rankingsAP Top 25 and Coaches Poll rankings
get_newsCollege basketball news
get_play_by_playFull play-by-play for a game
get_win_probabilityWin probability chart data
get_scheduleSchedule for a date or season
get_futuresFutures/odds markets (National Championship, etc.)
get_team_statsTeam statistical profile
get_player_statsPlayer statistical profile
get_ncaa_scoreboardOfficial NCAA scoreboard — D1, D2, and D3
get_ncaa_scheduleWhich dates have games (official index)
get_ncaa_gameOfficial NCAA game information
get_ncaa_boxscoreOfficial NCAA box score
get_ncaa_play_by_playOfficial play-by-play
get_ncaa_bracketMarch Madness bracket with live scores
get_ncaa_schoolsNCAA schools index (all divisions)
get_power_indexBPI (Basketball Power Index) ratings for D1 teams
get_tournament_projectionsNCAA tournament projections with seeds, regions, and advancement probabilities
compare_teamsCompare two teams using BPI ratings and season stats
find_upset_candidatesPotential upsets based on BPI vs seed differential

See references/api-reference.md for full parameter lists and return shapes.

Official NCAA Backend

The get_ncaa_* commands read the NCAA's own endpoints (sdataprod.ncaa.com + ncaa.com) — coverage ESPN does not carry:

  • D2 and D3 scoreboards via division="d2"/"d3" — ESPN's college coverage is D1-centric.
  • Both scoreboards now return all of Division I by default — the ESPN-backed get_scoreboard/get_schedule previously inherited ESPN's Top-25-only un-grouped default (1 game on an ordinary Friday instead of ~24). Pass group explicitly for a narrower ESPN grouping.
  • The official March Madness bracket with live scores: get_ncaa_bracket.
  • Official game detail: get_ncaa_game, get_ncaa_boxscore, get_ncaa_play_by_play.
  • The schools index (~1,200 schools, all divisions): get_ncaa_schools.

NCAA game ids (from get_ncaa_scoreboard) and ESPN event ids share nothing — join on game date plus team names. NCAA reissues game ids, so take them from a fresh get_ncaa_scoreboard call rather than storing them. get_ncaa_bracket returns an error, not a placeholder bracket, when no game has teams: the 2020 tournaments were cancelled, and future brackets appear once the field is announced. All get_ncaa_* commands except get_ncaa_schools ride NCAA's GraphQL persisted queries, whose hashes rotate when ncaa.com redeploys; when that happens they say so explicitly, and the ESPN-backed get_scoreboard / get_schedule cover the same D1 games.

Show full SKILL.md (398 more words)Show less

Examples

Example 1: Current rankings User says: "What are the college basketball rankings?" Actions:

  1. Call get_rankings() Result: AP Top 25 and Coaches Poll with rank, previous rank, record, and points

Example 2: Conference standings User says: "Show me SEC basketball standings" Actions:

  1. Derive season year from currentDate
  2. Call get_standings(group=23, season=<derived_year>) (group 23 = SEC) Result: SEC standings with W-L records per team

Example 3: Today's scores User says: "What are today's college basketball scores?" Actions:

  1. Call get_scoreboard() Result: All live and recent CBB games with scores and ranked status

Example 4: Team roster User says: "Show me Duke's roster" Actions:

  1. Call get_team_roster(team_id="150") Result: Full Duke roster with name, position, jersey number

Example 5: March Madness futures User says: "Who's favored to win March Madness?" Actions:

  1. Call get_futures(limit=10) Result: Top National Championship contenders with odds values

Example 6: Team statistics User says: "Show me Duke's team stats" Actions:

  1. Derive season year from currentDate
  2. Call get_team_stats(team_id="150", season_year=<derived_year>) Result: Duke's season stats by category with value, rank, and per-game averages

Commands that DO NOT exist — never call these

  • get_odds / get_betting_odds — not available. For prediction market odds, use the polymarket or kalshi skill.
  • search_teams — does not exist. Use get_teams instead.
  • get_box_score — does not exist. Use get_game_summary instead.
  • get_player_ratings — does not exist. Use get_player_stats instead.
  • get_ap_poll — does not exist. Use get_rankings instead.

If a command is not listed in the Commands table above, it does not exist.

Error Handling

When a command fails, do not surface raw errors to the user. Instead:

  1. If no events found, check if it's the off-season (CBB runs November–April)
  2. If standings are empty without a group filter, try a specific conference
  3. During March Madness, the scoreboard will have tournament games
  4. Only report failure with a clean message after exhausting alternatives

Troubleshooting

Error: sports-skills command not found Cause: Package not installed Solution: Run pip install sports-skills

Error: No games found on scoreboard Cause: CBB is seasonal (November–April); off-season scoreboard will be empty Solution: Use get_rankings or get_news year-round; check get_schedule for when the season resumes

Error: Too many games returned — hard to filter Cause: During the season, 50+ games per day are scheduled Solution: Use --group to filter by conference, or --limit to cap results

Error: Rankings empty Cause: Rankings are published weekly during the season (November–March) only Solution: Use get_news in the offseason; rankings resume in November

© machina-sports, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 4 other files (scripts, references) in skills/cbb-data of machina-sports/sports-skills.

  • SKILL.md
  • references/api-reference.md
  • references/conference-ids.md
  • references/team-ids.md
  • scripts/validate_params.sh

Open the folder on GitHubat commit 0420a7c

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Works with

Categories

Questions about Cbb Data

What does Cbb Data do?

College Basketball (CBB) data via ESPN public endpoints and the NCAA's official endpoints — scores, standings, rosters, schedules, game summaries, play-by-play, win probability, rankings, futures…. Cbb Data is an agent skill from machina-sports/sports-skills. College Basketball (CBB) data via ESPN public endpoints and the NCAA's official endpoints — scores, standings, rosters, schedules, game summaries, play-by-play, win probability, rankings, futures, team/player stats, and news for Division I men's basketball, plus official D2/D3 scoreboards, NCAA game detail, the March Madness bracket with live scores, and the schools index.

When should I use Cbb Data?

Cbb Data fits situations like: : user asks about college basketball scores; the NCAA tournament bracket; betting futures; team/player statistics.

How do I install Cbb Data in Claude Code?

Run `npx skills add machina-sports/sports-skills --skill cbb-data -a claude-code`. Or copy the skill folder (skills/cbb-data in machina-sports/sports-skills) into .claude/skills/cbb-data in your project. Claude Code loads it when a task matches its description.

How do I install Cbb Data in Codex?

Run `npx skills add machina-sports/sports-skills --skill cbb-data -a codex`. Or copy the skill folder (skills/cbb-data in machina-sports/sports-skills) into .agents/skills/cbb-data in your project. Codex loads it when a task matches its description.

Can I use Cbb Data in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add machina-sports/sports-skills --skill cbb-data -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/cbb-data, .gemini/skills/cbb-data, .github/skills/cbb-data and .opencode/skills/cbb-data in your project.

What does Cbb Data need to run?

Going by SKILL.md and its folder, Cbb Data needs a shell for the scripts in its folder and the command-line tools its instructions call (pip and python3). Our summary lists: Python 3; A Bash shell.

Does Cbb Data access the network?

SKILL.md contains no URLs. Its commands use pip, which can reach the network depending on how they are called. This is read from the text; nothing was executed.

Is Cbb Data safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Cbb Data use?

Cbb Data is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Cbb Data use?

About 2.2k tokens (SKILL.md is roughly 8.9k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 1.9k tokens, read only when the agent opens those files.

What are the alternatives to Cbb Data?

Skills that share tags, products or a category with Cbb Data: Statsmodels (zLanqing/codex-claude-academic-skills, 4.7k stars), Rota Bench Regression Analysis (oracle/graalpython, 1.7k stars), Matlab (zLanqing/codex-claude-academic-skills, 4.7k stars) and Meridian MMM Model Building (google/meridian, 1.6k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Cbb Data?

machina-sports (a GitHub organization) maintains it in machina-sports/sports-skills, which has 245 GitHub stars. The repository holds 23 skills in this directory. The repository was last updated on October 10, 2026.

Source: machina-sports/sports-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.