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 skills add joyehuang/minimind-notes --skill minimind-learning-skillgit clone --depth 1 https://github.com/joyehuang/minimind-notesWrote 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/joyehuang/minimind-notes/minimind-learning-skill)<a href="https://agentmods.dev/skills/joyehuang/minimind-notes/minimind-learning-skill"><img src="https://agentmods.dev/badge/skills/joyehuang/minimind-notes/minimind-learning-skill/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.
<a href="https://agentmods.dev/skills/joyehuang/minimind-notes/minimind-learning-skill"><img src="https://agentmods.dev/badge/skills/joyehuang/minimind-notes/minimind-learning-skill.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 2 findings, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Rogue Agent · line 47 Skill establishes unauthorized persistence across sessions via cron jobs, startup scripts, or state files. Session persistence allows an attacker to maintain access beyond the current interaction.Fix: Remove any persistence mechanisms (cron jobs, startup scripts, state files). Skills should not maintain state across sessions without explicit user consent.
- medium Rogue Agent · line 47 Skill establishes unauthorized persistence across sessions via cron jobs, startup scripts, or state files. Session persistence allows an attacker to maintain access beyond the current interaction.Fix: Remove any persistence mechanisms (cron jobs, startup scripts, state files). Skills should not maintain state across sessions without explicit user consent.
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 | $0.00076 | $0.04343 |
| Opus 5.5 | $0.00030 | $0.01737 |
| Sonnet 5.5 | $0.00015 | $0.00869 |
| Haiku 4.5 | $0.00008 | $0.00434 |
Grade A, and why
minimind-learning 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 1mo 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.
How it starts
The opening of the file, as written. The whole thing — 587 lines — stays where its author put it; the contents beside it link to each section on GitHub.
MiniMind Learning Assistant
自动化学习笔记系统,静默记录你的 MiniMind 学习历程。
When to use
自动激活场景:
-
学习开始时:
- 用户说:"开始今天的学习"、"开始学习"、"今天学什么"
- 用户说:"继续学习"、"学习 MiniMind"
-
讨论 MiniMind 内容时:
- 提问包含:RMSNorm, LayerNorm, RoPE, YaRN, Attention, GQA, SwiGLU, Transformer, LoRA, DPO, PPO, GRPO, SFT, RLHF, RLAIF, MoE
- 问题词:什么是、如何、为什么、怎样、解释、原理
- 遇到问题:报错、错误、失败、Bug
-
显式记录请求:
- 用户说:"记录一下"、"保存笔记"、"写入笔记"
How to use
1. 初始化检查
首次激活时,确保笔记结构存在:
# 检测 Git 仓库根目录
git rev-parse --show-toplevel
# 验证是 MiniMind 仓库(存在以下文件)
# - model/model_minimind.py
# - trainer/train_pretrain.py
# - README.md (包含 "MiniMind")
# 创建笔记目录(如不存在)
mkdir -p docs/learning_materials
# 从模板初始化文件(如不存在)
# - docs/notes.md
# - docs/learning_log.md
# - docs/knowledge_base.md
# - docs/learning_materials/README.md
模板位置:~/.claude/skills/minimind-learning/templates/
2. 学习引导模式
当用户说"开始学习"时,主动引导:
👋 欢迎开始今天的 MiniMind 学习!
你想学习哪个模块?
**基础组件**:
1. 归一化技术 - RMSNorm, LayerNorm
2. 位置编码 - RoPE, YaRN
3. 注意力机制 - Attention, GQA
4. 前馈网络 - FeedForward, SwiGLU
**训练技术**:
5. 预训练 - Pretraining
6. 监督微调 - SFT
7. 参数高效微调 - LoRA
8. 强化学习 - DPO, PPO, GRPO
直接告诉我编号或主题名称,我会为你讲解!
(学习过程中我会自动记录笔记到 `docs/` 目录)
3. 触发检测
每次用户消息后,检查是否满足以下任一条件:
Tier 1: 即时触发(立即更新笔记)
# MiniMind 术语(50+)
TERMS = [
# 架构
"RMSNorm", "LayerNorm", "BatchNorm", "GroupNorm",
"RoPE", "YaRN", "ALiBi", "位置编码",
"Attention", "注意力", "GQA", "MQA", "FlashAttention",
"FeedForward", "前馈", "SwiGLU", "GELU", "GLU",
"Transformer", "TransformerBlock",
# 训练
"pretrain", "预训练", "pretraining",
"SFT", "监督微调", "fine-tuning", "微调",
"LoRA", "lora", "LoRA-r", "LoRA-alpha",
"DPO", "PPO", "GRPO", "SPO",
"RLHF", "RLAIF", "强化学习",
"distillation", "蒸馏", "知识蒸馏",
# 模型
"MiniMind", "MiniMind-Dense", "MiniMind-MoE",
"MoE", "混合专家", "expert routing",
"MiniMind-Reason", "R1",
]
# 问题词
QUESTION_WORDS = ["什么是", "如何", "为什么", "怎样", "解释", "原理", "作用"]
# 问题指示
PROBLEM_MARKERS = ["报错", "错误", "失败", "Bug", "不工作", "问题"]
# 检查
if any(term in user_message for term in TERMS):
trigger_tier_1()
elif any(word in user_message for word in QUESTION_WORDS):
trigger_tier_1()
elif any(marker in user_message for marker in PROBLEM_MARKERS):
trigger_tier_1()
What ships with it
10 files 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.
- .gitignore 243 B
- .minimind-learning.json.example 356 B
- LICENSE 1.0 KB
- scripts/init-for-learning.bat 3.1 KB runs code
- scripts/init-for-learning.sh 3.0 KB runs code
- scripts/validate_notes.py 8.9 KB runs code
- templates/knowledge_base.md.template 7.5 KB
- templates/learning_log.md.template 1.1 KB
- templates/learning_materials_readme.md.template 5.1 KB
- templates/notes.md.template 4.3 KB
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.
- 1mo ago First seen · 587 lines · 76 tokens per session scan A 8acecdd0bffb
minimind-learning is a skill published in the GitHub repository joyehuang/minimind-notes (222 stars, last pushed 4mo ago), licensed Apache-2.0. It adds 76 tokens to every session and 4,343 once invoked, about $0.0003 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 2026-08-30.
Other skills, from other repositories
ai-engineering-curriculum
Use when structured AI engineering curriculum — 382 skills + 99 prompts across 20 phases covering ML, deep learning, LLMs, agents, and production systems. Use when learning AI, building AI skills,.
andrej-karpathy
Agente que simula Andrej Karpathy — ex-Director of AI da Tesla, co-fundador da OpenAI, fundador da Eureka Labs, e o maior educador de deep learning do mundo.
andrej-karpathy
Agente que simula Andrej Karpathy — ex-Director of AI da Tesla, co-fundador da OpenAI, fundador da Eureka Labs, e o maior educador de deep learning do mundo.
andrej-karpathy
Agente que simula Andrej Karpathy — ex-Director of AI da Tesla, co-fundador da OpenAI, fundador da Eureka Labs, e o maior educador de deep learning do mundo.
outlines
Outlines: structured JSON/regex/Pydantic LLM generation.
instructor
Structured LLM outputs validated with Pydantic.