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/learn-startgit 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/learn-start)<a href="https://agentmods.dev/commands/sean-xhz/ai-learning-platform/learn-start"><img src="https://agentmods.dev/badge/commands/sean-xhz/ai-learning-platform/learn-start.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 5.1 | $0.00039 | $0.00412 |
| Opus 5 | $0.00019 | $0.00206 |
| Sonnet 5 | $0.00008 | $0.00082 |
| Haiku 4.5 | $0.00004 | $0.00041 |
Grade A, and why
learn-start 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 5d 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
/learn-start
请帮我设计一个新的学习计划。
$ARGUMENTS
首先确认以下信息：
- 学什么：具体领域或技能？
- 为什么学：学习动机和应用场景？
- 学多久：总时间预算和每天可用时长？
- 什么水平：当前对该领域的了解程度（零基础 / 有概念 / 有实操）？
- 期望产出：学完后要能做什么？（具体可验证的）
- 学习模式：
- 🎯 项目驱动（有具体项目，学以致用）
- 🔭 领域探索（关注趋势，拓展视野）
- 💡 纯粹认知（好奇心驱动，纯粹学习）
如果 $ARGUMENTS 中已包含部分信息，直接使用已知信息，只询问缺失的部分。
覆盖保护（调用 planner 之前必查）：若工作目录根已存在 learning-plan.md：
- 先读出旧计划概况（标题、
| 当前进度 | ... |）告知用户，并说明"继续会覆盖现有计划" - 用户确认继续 → 旧文件改名为
learning-plan-archive-YYYYMMDD.md（归档而非抹除；sessions/与review-queue.md保持不动，新计划从零开始自己的 Day 计数） - 用户未明确确认 → 中止，不得静默覆盖
通过覆盖保护检查后，调用 learning-planner Skill 生成完整的结构化课程计划，写入 learning-plan.md。
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.
- 5d ago First seen · 31 lines · 39 tokens per session scan A 91b4ca946a29
learn-start is a command published in the GitHub repository Sean-xhz/ai-learning-platform (2 stars, last pushed 1mo ago), licensed MIT. It adds 39 tokens to every session and 412 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
lrn
Execute the /vibeguard:learn command. $ARGUMENTS.
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.
annex-a-deep-dive
Deep dive analysis of ISO 27001 Annex A control domains with implementation guidance.
start-10-1
Command "start-10-1" from minicoohei/ai-agent-camp, covering 🎓 lesson 10-1: clasp基本・gasプロジェクト管理, 📍 このセッションでやること, 🎯 準備チェック, 🚀 step 1: claspのインストールと apps script api の確認 and 🚀 step 2: google認証.
start-13-4.en
Welcome to Lesson 13-4: Landing Page Implementation!