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 football-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/football-data)<a href="https://agentmods.dev/skills/machina-sports/sports-skills/football-data"><img src="https://agentmods.dev/badge/skills/machina-sports/sports-skills/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/machina-sports/sports-skills/football-data"><img src="https://agentmods.dev/badge/skills/machina-sports/sports-skills/football-data.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk warn
- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high YARA Match · line 26 YARA rule matched a known malware signature (reverse shell, backdoor, ransomware, C2 framework, or info stealer).Fix: Remove the malware payload or compromised file entirely. Investigate how it entered the skill and audit all other artifacts for additional indicators of compromise.
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 3d 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- football-data — 91% identical, 0 lines differ
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.
- 3d ago Changed · +2 lines 380e4790bbaa
- 7d ago Changed · +1 lines d593feca09f7
- 12d ago First seen · 237 lines · 342 tokens per session scan A 56188c3c9e37
football-data is a skill published in the GitHub repository machina-sports/sports-skills (218 stars, last pushed 4d ago), 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. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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