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 agentmods add skills/yyz666ai/learning-agent/practice-drillnpx skills add yyz666ai/Learning-Agent --skill practice-drillgit clone --depth 1 https://github.com/yyz666ai/Learning-AgentWrote 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/yyz666ai/learning-agent/practice-drill)<a href="https://agentmods.dev/skills/yyz666ai/learning-agent/practice-drill"><img src="https://agentmods.dev/badge/skills/yyz666ai/learning-agent/practice-drill.svg" alt="Measured on agentmods" 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 | $0.00048 | $0.00463 |
| Opus 5 | $0.00024 | $0.00231 |
| Sonnet 5 | $0.00010 | $0.00093 |
| Haiku 4.5 | $0.00005 | $0.00046 |
Grade A, and why
practice-drill 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 4d 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.
What it actually says
出题刷题（精进练习）
面向「想多练、精进」的学习者，按掌握度出难度合适的题，练完交批改，形成「练 → 批 → 复习」循环。
执行流程
- 读画像 + 掌握状态：确定当前水平（新手/熟练）、目标语言、已掌握点与薄弱点。
- 选题：新手出「刚学概念的巩固题」；熟练者出「变体题、迁移题、跨概念综合题、小项目改造」。
- 难度对齐掌握度：太简单浪费时间，太难挫败；熟练者优先给 L5 迁移题（结构相同、表面不同，独立完成才算掌握）。
- 出题要「能验证」：每题带明确完成标准 + 预期输出/行为，练完能自己判断对错。
- 做完 → 交
assignment-review批改；正确推进掌握，错误记录误区并降级重练。 - 长期精进：结合
spaced-review的到期复习点 +project-practice的变体改造，持续循环。
边界
- 一次只展示一道练习，做完、评价完再给下一题；题库可以提前生成，但不能一次抛给学习者。
- 跳过不算答对，也不能触发掌握推进或庆祝反馈。
- 不提前给答案；卡住转
exercise-coach给最小提示。 - 题目基于 curriculum 原子/概念图，不编造超纲内容。
- 只记录真实完成的练习证据；不得伪造「已做完」。
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.
- 4d ago First seen · 26 lines · 48 tokens per session scan A f0daec61ef2f
practice-drill is a skill published in the GitHub repository yyz666ai/Learning-Agent (1 stars, last pushed 4d ago), licensed MIT. It adds 48 tokens to every session and 463 once invoked, about $0.0002 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 2026-08-31.
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