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 nfl-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/nfl-data)<a href="https://agentmods.dev/skills/machina-sports/sports-skills/nfl-data"><img src="https://agentmods.dev/badge/skills/machina-sports/sports-skills/nfl-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/nfl-data"><img src="https://agentmods.dev/badge/skills/machina-sports/sports-skills/nfl-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 | $0.00123 | $0.03780 |
| Opus 5.5 | $0.00049 | $0.01512 |
| Sonnet 5.5 | $0.00025 | $0.00756 |
| Haiku 4.5 | $0.00012 | $0.00378 |
Grade A, and why
nfl-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.
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 — 297 lines — stays where its author put it; the contents beside it link to each section on GitHub.
NFL 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.
For nflverse-backed commands (get_nflverse_*), install the NFL extra:
pip install sports-skills[nfl]
On Python 3.10+ this installs nflreadpy (the preferred backend) plus pyarrow, which is needed for most nflverse data beyond schedules. On Python 3.9 it installs nfl-data-py instead, since nflreadpy requires 3.10+.
The nfl-data-py backend is a reduced fallback: it cannot serve get_nflverse_team_stats, which returns an explanatory error there. Use Python 3.10+ for full nflverse coverage.
Quick Start
Prefer the CLI — it avoids Python import path issues:
sports-skills nfl get_scoreboard
sports-skills nfl get_standings --season=2025
sports-skills nfl get_teams
Python SDK (alternative):
from sports_skills import nfl
scores = nfl.get_scoreboard({})
standings = nfl.get_standings({"params": {"season": "2025"}})
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: 2026-02-16 → current year is 2026).
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.
- 9d ago Changed · +19 lines cd4e9b336e7c
- 27d ago Changed · +7 lines 7d8e4fdc3978
- 1mo ago Changed · +24 lines · +10 tokens per session 5d392a31132c
- 1mo ago Changed · +28 lines 220743bb84d1
- 2mo ago First seen · 219 lines · 113 tokens per session scan A 8e5ad906e475
nfl-data is a skill published in the GitHub repository machina-sports/sports-skills (264 stars, last pushed yesterday), licensed MIT. It adds 123 tokens to every session and 3,780 once invoked, about $0.0005 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.
nfl-data compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| nfl-datamachina-sports/sports-skills | Skill | 264 | yesterday | MIT | A | 123 | 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 |