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 sutchan/Agent-Skills-Hub --skill football-datagit clone --depth 1 https://github.com/sutchan/Agent-Skills-HubWrote 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/sutchan/agent-skills-hub/football-data)<a href="https://agentmods.dev/skills/sutchan/agent-skills-hub/football-data"><img src="https://agentmods.dev/badge/skills/sutchan/agent-skills-hub/football-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/sutchan/agent-skills-hub/football-data"><img src="https://agentmods.dev/badge/skills/sutchan/agent-skills-hub/football-data.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00342 | $0.04260 |
| Opus 5 | $0.00171 | $0.02130 |
| Sonnet 5 | $0.00068 | $0.00852 |
| Haiku 4.5 | $0.00034 | $0.00426 |
Grade A, and why
football-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 2d 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.
This is a copy
91% identical to football-data — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 240 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Football 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 (package not found or Python version error), install from GitHub:
pip install git+https://github.com/machina-sports/sports-skills.git
The package requires Python 3.10+. If your default Python is older, use a specific version:
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 football get_daily_schedule
sports-skills football get_season_standings --season_id=premier-league-2025
Python SDK (alternative):
from sports_skills import football
standings = football.get_season_standings(season_id="premier-league-2025")
schedule = football.get_daily_schedule()
CRITICAL: Before Any Query
CRITICAL: Before calling any data endpoint, verify:
- Season ID is derived from
get_current_season(competition_id="...")— never hardcoded. - Team ID is resolved via
search_team(query="...")and passed as the numericteam_id. Forget_head_to_head,get_team_strength, andget_match_forecast, always pass IDs — ambiguous names (e.g. two "Paris" clubs) can resolve to the wrong team. - The endpoint actually covers the league in question — see the Coverage & Source Map below. Coverage is uneven across sources; an uncovered call returns an empty payload with a
message, not data. get_event_xgandget_event_players_statistics(with xG) are only called for top-5 leagues (EPL, La Liga, Bundesliga, Serie A, Ligue 1).get_season_leadersandget_missing_playersare only called for Premier League seasons (season_id must start withpremier-league-).
What ships with it
5 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.
- 2d ago Changed · +4 lines · +342 tokens per session 380e4790bbaa
- 8d ago First seen · 236 lines · 0 tokens per session scan A efb6c9f56126
football-data is a skill published in the GitHub repository sutchan/Agent-Skills-Hub (2 stars, last pushed yesterday), licensed MIT. It adds 342 tokens to every session and 4,260 once invoked, about $0.0017 per session on Opus 5. A static security scan graded it A with 0 findings. It is 91% identical to football-data, differing in 0 lines, and is treated as a copy.
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