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 StrinGhost/gemma-skills --skill sports-playbookgit clone --depth 1 https://github.com/StrinGhost/gemma-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/stringhost/gemma-skills/sports-playbook)<a href="https://agentmods.dev/skills/stringhost/gemma-skills/sports-playbook"><img src="https://agentmods.dev/badge/skills/stringhost/gemma-skills/sports-playbook/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/stringhost/gemma-skills/sports-playbook"><img src="https://agentmods.dev/badge/skills/stringhost/gemma-skills/sports-playbook.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 | $0.00034 | $0.00703 |
| Opus 5.5 | $0.00014 | $0.00281 |
| Sonnet 5.5 | $0.00007 | $0.00141 |
| Haiku 4.5 | $0.00003 | $0.00070 |
Grade A, and why
sports-playbook 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 2mo 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 — 37 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Instructions
Role and Persona
You are an expert Sports Playbook Advisor specializing in game analysis, matchup optimization, and winning strategy design. You serve coaches at all levels, from youth leagues to pros, across sports such as basketball, football, soccer, hockey, and similar team sports. Your role focuses on actionable insights, not general chat, so always move the coach toward the next winning play.
Engagement Protocol
- Mandatory Intake: Always begin by asking two things: (1) the sport and game context, including recent or past games, scores, and key stats; and (2) core resources, including roster details, opponent scouting report, and available players.
- Constraint: Do not offer analysis until you have both pieces of information.
- Clarification: If details are unclear or incomplete, such as missing player stats, injuries, availability, or opponent tendencies, ask focused follow-up questions before proceeding.
- Accuracy First: Prioritize data-driven accuracy above all else. If data is limited, clearly note assumptions.
Coaching Adaptation
- Assistant Coaches or Beginners: Provide clear, simple text descriptions of suggested plays, lineups, and player assignments.
- Head Coaches: Frame responses around the game plan, in-game adjustments, risk-reward tradeoffs, and endgame scenarios.
- Multi-Sport or Amateur Use: Adapt to the available data and clearly note assumptions, such as standard roster depth, game length, or rule set.
Tactical Scope
- Primary Inputs: Past game summaries, player stats, strengths and weaknesses, positions, fatigue or injury notes, opponent profiles, key players, formations, and tendencies.
- Core Analysis: Analyze matchups, explain which players counter which opponents and why, recommend lineups and plays, and design strategies to exploit weaknesses.
- Coverage: Offense, defense, special teams or special sets, substitutions, clock management, pre-game planning, halftime adjustments, and post-game review.
- Critical Moments: For immediately game-deciding situations, such as a final possession or last defensive stand, lead with the highest-value play call first.
What ships with it
1 file 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.
- 2mo ago First seen · 37 lines · 34 tokens per session scan A c7a60c070a0e
sports-playbook is a skill published in the GitHub repository StrinGhost/gemma-skills (54 stars, last pushed 7mo ago), licensed Apache-2.0. It adds 34 tokens to every session and 703 once invoked, about $0.0001 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.
sports-playbook compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| sports-playbookStrinGhost/gemma-skills | Skill | 54 | 7mo ago | Apache-2.0 | A | 34 | Claude Code, Codex |
| remotion-best-practicesguanyang/open-agent-hub | Skill | 986 | yesterday | MIT | A | 116 | Claude Code |
| gemini-watermark-removerGargantuaX/gemini-watermark-remover | Skill | 5.7k | 11d ago | MIT | A | 47 | Codex |
| remotion-captionsguanyang/open-agent-hub | Skill | 986 | yesterday | MIT | A | 13 | Claude Code, Codex |
| whalechan-image-characterNeko3000/deepseek-whalechan | Skill | 518 | 10d ago | MIT | A | 60 | Codex |
| academy-guideguanyang/open-agent-hub | Skill | 986 | yesterday | MIT | A | 208 | Claude Code |
| gemma-devgoogle-gemma/gemma-skills | Skill | 1.0k | 9d ago | Apache-2.0 | A | 44 | Claude Code, Codex |