learn-today

learn-today is a command for Claude Code from Sean-xhz/ai-learning-platform. It costs 35 tokens per session (907 once invoked), scanned A, original, MIT.

A daily study command that organizes review and new learning. It uses spaced retrieval, a method of revisiting material at increasing intervals, before introducing the day’s topic.

In plain words
What is it for?
Use it to start the day’s lesson, check overdue review items, run a short recall test, identify the day’s topic, and gather supporting materials.
Why use it?
It prevents forgotten material from being silently skipped and keeps study sessions connected to a learning plan. It can also collect study materials and prepare a pre-test when the plan calls for one.

Command for Claude Code

Written for Claude Code: $ARGUMENTS substitution. Also seen: mentions subagents.

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

Good fit Use it to start the day’s lesson, check overdue review items, run a short recall test, identify the day’s topic, and gather supporting materials.

Compare 6 commands from other repositories ↓
Install with agentmods
npx agentmods add commands/sean-xhz/ai-learning-platform/learn-today
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-today

README.md
[![agentmods](https://agentmods.dev/badge/commands/sean-xhz/ai-learning-platform/learn-today/github.svg)](https://agentmods.dev/commands/sean-xhz/ai-learning-platform/learn-today)
Your own site
<a href="https://agentmods.dev/commands/sean-xhz/ai-learning-platform/learn-today"><img src="https://agentmods.dev/badge/commands/sean-xhz/ai-learning-platform/learn-today/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-today

Your own site · 80×15
<a href="https://agentmods.dev/commands/sean-xhz/ai-learning-platform/learn-today"><img src="https://agentmods.dev/badge/commands/sean-xhz/ai-learning-platform/learn-today.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 35 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 907 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 $0.00035 $0.00907
Opus 5 $0.00017 $0.00453
Sonnet 5 $0.00007 $0.00181
Haiku 4.5 $0.00003 $0.00091

Measured 8d ago against content hash e0a42e5fe5c3, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

learn-today 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 8d 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-today.md · 45 lines

What it actually says

/learn-today

今天是学习计划的第几天?让我看看今天的学习任务。

$ARGUMENTS

当前进度:grep '当前进度' learning-plan.md 2>/dev/null | head -1 已完成会话数:find sessions/ -name 'session-log*.md' -type f 2>/dev/null | wc -l | tr -d ' ' 学习模式:grep '学习模式' learning-plan.md 2>/dev/null | head -1

这是每日学习闭环的开环命令,与 /learn-done(收尾)成对。按以下步骤编排:

Step 0:唤起复习(P1-7,先还旧账再学新的)

检查 review-queue.md(若存在):

  • 若今天是缓冲日(计划中 Day 标题含 📥 缓冲日(复习日))→ 不学新内容(跳过 Step 1):
    • 队列有项 → 深度复习:调用 assessment-officer 复习模式(缓冲日深度变体),累积重测所有「待复习/已重置」项 + 迄今最弱的维度
    • 队列为空或不存在 → 轻量回顾:带学习者翻看迄今 session-log 的核心收获与仍存疑问,不召 material-steward、不做 Pre-test
  • 非缓冲日:筛出 下次复习Day ≤ 今天状态=待复习/已重置 的到期项:
    • 有到期项 → 先调用 assessment-officer 复习模式(日常到期变体)做检索小测(考你而非重讲),判定记得/模糊/忘了,回写队列更新间隔;然后再进入新内容
    • 无到期项 → 一句带过"今天没有到期复习项",直接进入新内容
    • review-queue.md 不存在 → 跳过本步(还没有积累盲区)

Step 1:今日主题

先按下方「判断今天学什么」定位今日。若今天是缓冲日,本步整体跳过(复习日不排新内容,由 Step 0 的深度复习/轻量回顾接管)。否则:

  1. 若该日 - **状态**: 行已是 ✅ 已完成:提示"今天已经完成了,要回顾还是继续下一天?",不执行后续步骤
  2. 把该日 - **状态**: 行更新为 🔄 进行中(幂等——重复运行无副作用;/learn-progress 的进行中统计以此为真实来源)
  3. 读取该日计划,输出今日主题和核心问题、预期产出(学完后要能做什么)
  4. 调用 material-steward Subagent 收集今日材料——显式传入上下文:Day N、今日主题、3-5 个核心问题、学习模式、当前水平、每日可用时长(子代理无法自行定位"今天",只说"收集今日材料"会断链)
  5. 提醒进行 Pre-test(调用 assessment-officer Skill)
  6. 告知学习者:自学过程中遇到不懂的概念,随时可以用 /explain 召唤讲解员

判断今天学什么

  • 如果 $ARGUMENTS 包含天数(如 "Day 3"),直接定位到对应天
  • 否则从上方反引号输出的"当前进度"读取
  • 学完一天后,引导用 /learn-done 收尾(Post-test + 价值转化 + 盲区入队)
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. 8d ago First seen · 45 lines · 35 tokens per session scan A e0a42e5fe5c3

Subscribe to this mod's changes

learn-today is a command published in the GitHub repository Sean-xhz/ai-learning-platform (2 stars, last pushed 1mo ago), licensed MIT. It adds 35 tokens to every session and 907 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.