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learn-start

learn-start is a command for Claude Code from Sean-xhz/ai-learning-platform. It costs 39 tokens per session (412 once invoked), scanned A, original, MIT.

A command that starts a structured learning plan by collecting your goal, reason, available time, skill level, desired outcome, and learning style.

In plain words
What is it for?
Use it to plan project-based learning, subject exploration, or curiosity-driven study, with protection against silently overwriting an existing plan.
Why use it?
It turns a vague intention to learn into a course plan with a clear schedule and a verifiable result.

Command for Claude Code

Written for Claude Code: $ARGUMENTS substitution.

Part of the ai-learning-platform plugin — 2 skills, 5 commands, 3 agents, 2 hooks shipped together

not rated 2repo 3mo ago A scan 39 tokens original MIT

Good fit Use it to plan project-based learning, subject exploration, or curiosity-driven study, with protection against silently overwriting an existing plan.

Compare 6 commands from other repositories ↓
Install with agentmods
npx agentmods add commands/sean-xhz/ai-learning-platform/learn-start
View source ↗ Sean-xhz/ai-learning-platform
Install

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.

Clone the repo
git clone --depth 1 https://github.com/Sean-xhz/ai-learning-platform

Made for: Claude Code.

Or install ai-learning-platform, the plugin that ships this one along with the rest of its 2 skills, 5 commands, 3 agents, 2 hooks.

Wrote 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.

agentmods badge for learn-start

README.md
[![agentmods](https://agentmods.dev/badge/commands/sean-xhz/ai-learning-platform/learn-start/github.svg)](https://agentmods.dev/commands/sean-xhz/ai-learning-platform/learn-start)
Your own site
<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/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.

agentmods 80×15 button for learn-start

Your own site · 80×15
<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="Reviewed on agentmods" width="80" height="20"></a>
Per session 39 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 412 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00039 $0.00412
Opus 5.5 $0.00016 $0.00165
Sonnet 5.5 $0.00008 $0.00082
Haiku 4.5 $0.00004 $0.00041

Measured 2mo ago against content hash 91b4ca946a29, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

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 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.

commands/learn-start.md · 31 lines

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：

  1. 学什么：具体领域或技能？
  2. 为什么学：学习动机和应用场景？
  3. 学多久：总时间预算和每天可用时长？
  4. 什么水平：当前对该领域的了解程度（零基础 / 有概念 / 有实操）？
  5. 期望产出：学完后要能做什么？（具体可验证的）
  6. 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。

Changes

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.

  1. 2mo ago First seen · 31 lines · 39 tokens per session scan A 91b4ca946a29

Subscribe to this mod's changes

learn-start is a command published in the GitHub repository Sean-xhz/ai-learning-platform (2 stars, last pushed 3mo ago), licensed MIT. It adds 39 tokens to every session and 412 once invoked, about $0.0002 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 2026-08-31.

Learning and teaching
Related

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