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 commands/sean-xhz/ai-learning-platform/explaingit clone --depth 1 https://github.com/Sean-xhz/ai-learning-platformWrote 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/commands/sean-xhz/ai-learning-platform/explain)<a href="https://agentmods.dev/commands/sean-xhz/ai-learning-platform/explain"><img src="https://agentmods.dev/badge/commands/sean-xhz/ai-learning-platform/explain.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 | $0.00036 | $0.00328 |
| Opus 5 | $0.00018 | $0.00164 |
| Sonnet 5 | $0.00007 | $0.00066 |
| Haiku 4.5 | $0.00004 | $0.00033 |
Grade A, and why
explain 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
/explain
我在学习过程中遇到了一个不理解的概念/段落：
$ARGUMENTS
请调用 concept-tutor Subagent（讲解员）：
- 传入今日上下文：若工作目录根存在
learning-plan.md，提取当前 Day（| 当前进度 | Day X / Phase Y |）、该 Day 的主题与核心问题、学习模式与当前水平，随疑问一并显式传给 concept-tutor（讲解员无法自行判断"今天在学什么"，缺了这层，解释就贴不上当下主线）；无计划文件则跳过，按即兴问答处理 - 如果提供了材料路径，读取相关段落定位上下文
- 根据疑问类型选择解释策略：
- 概念不理解 → 类比（用熟悉的领域做比喻）
- 关系不清楚 → 拆解（分步讲解 + 关系图）
- 技术细节 → 反例（对比错误做法）
- 外语表达 → 翻译 + 语境解释
- 解释后追问是否清楚，不清楚则换角度再解释
- 不超过 3 个概念，超过则建议分次提问
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 · 22 lines · 36 tokens per session scan A e8f0b461bf16
explain is a command published in the GitHub repository Sean-xhz/ai-learning-platform (2 stars, last pushed 1mo ago), licensed MIT. It adds 36 tokens to every session and 328 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.
Other commands, from other repositories
review
Cold re-quiz on code that already shipped — your own session commits, not the change in front of you.
learn-story-flow
Learn story-flow concepts with interactive guidance for junior developers.
no-vibe
Enter no-vibe mode in OpenCode (tutor mode, no direct project file writes).
teach-me-testing
Teach testing progressively through structured sessions. Use when user says ""lets learn testing"" or ""I want to study test practices"".
setup-bigquery.es
Command "setup-bigquery.es" from minicoohei/ai-agent-camp, covering configuración de autenticación bigquery / gcp, step 0: verificar el progreso de configuración, lo que hará en esta sesión, verificación de preparación and step 1: instalación de gcloud cli.
setup-content
Lesson command — 教材コンテンツの初回セットアップ.