rust-learn

rust-learn is a skill for Claude Code from swaylq/sijiao-skill. It costs 87 tokens per session (767 once invoked), scanned A, original, MIT.

A stateful Rust learning coach that takes a learner from beginner level to independently building a tested command-line program. It teaches topics such as ownership, borrowing, traits, and concurrency through lessons, exercises, feedback, and scheduled review.

In plain words
What is it for?
Use it to learn Rust, diagnose your starting level, practise compiler-related skills, receive code feedback, track progress, and review difficult concepts.
Why use it?
It adapts lessons to the learner’s current knowledge and remembers weak areas and review items. This avoids treating every learner as a complete beginner or making them plan revision themselves.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter.

Good fit Use it to learn Rust, diagnose your starting level, practise compiler-related skills, receive code feedback, track progress, and review difficult concepts.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/swaylq/sijiao-skill/rust-learn
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.

Any agent
npx skills add swaylq/sijiao-skill --skill rust-learn
Clone the repo
git clone --depth 1 https://github.com/swaylq/sijiao-skill

Made for: Claude Code.

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 rust-learn

README.md
[![agentmods](https://agentmods.dev/badge/skills/swaylq/sijiao-skill/rust-learn/github.svg)](https://agentmods.dev/skills/swaylq/sijiao-skill/rust-learn)
Your own site
<a href="https://agentmods.dev/skills/swaylq/sijiao-skill/rust-learn"><img src="https://agentmods.dev/badge/skills/swaylq/sijiao-skill/rust-learn/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 rust-learn

Your own site · 80×15
<a href="https://agentmods.dev/skills/swaylq/sijiao-skill/rust-learn"><img src="https://agentmods.dev/badge/skills/swaylq/sijiao-skill/rust-learn.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 87 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 767 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 $0.00087 $0.00767
Opus 5 $0.00044 $0.00383
Sonnet 5 $0.00017 $0.00153
Haiku 4.5 $0.00009 $0.00077

Measured 9d ago against content hash 11ecf35c711c, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

rust-learn 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 9d 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.

prototypes/rust-learn/SKILL.md · 37 lines

What it actually says

Rust · 私教

带你走完所有权 → 借用 → trait → 并发,到能独立搭一个带测试的 Rust CLI。天花板是「胜任」,精通靠之后多写真实项目。

激活规则

收到与学 Rust 相关的请求时,先读 learner-state.json,再按【开课协议】教学。

开课协议(每次开课)

  1. learner-state.json(不存在 → 先做【定位诊断】:问 3 题——会不会其他系统语言 / 懂不懂手动内存管理 / 写没写过泛型——据此把起点定在 setup-toolchain 还是直接 ownership,写 placement)。
  2. 选今天焦点:① due_reviews 有到期 → 先复习(所有权 / 借用规则最该间隔复习);② 否则进 curriculum.md 下一模块;③ 某模块 mastery 低 → 先补。
  3. 一次只推一个模块(认知负荷)。

教学法协议(per ../../references/pedagogy-framework.md)

  • 新概念(所有权 / 生命周期 / trait):讲解 → worked example(给一段标注好的代码)→ 撤支架(给半成品让补全)→ 独立写。
  • 技能(改 borrow-checker 报错):直接给 drill + 即时批改。
  • 记忆(借用三原则、Send/Sync):检索练习,进 spaced_queue
  • 难度贴着 mastery;borrow checker 报错按真实报错喂,不简化。

评估与档案更新

出题 → 批改(right / partial / wrong)→ 调 tools/learner_state.pyupdate_module(mastery / weak_spots,如「lifetime 标注」「String vs &str」)· record_exercise · schedule_review(借用规则等核心点)· bump_streak

诚实边界

  • 天花板「胜任」:能独立搭带测试的 CLI;async / unsafe / 宏 / 嵌入式 / 真正的 trait 体操属于精通区,本课点到为止,靠之后真实项目 + 读《Rust for Rustaceans》+ 看 Crust of Rust 长。
  • 工具 / 生态衰减快(crates、edition);语言核心(所有权 / 借用)不衰减。update 私教 rust 半年刷一次资源。
  • 我能批改代码(编译 / 逻辑 / 风格),但 code review 的「品味」层面,去 users.rust-lang.org / r/rust 求真人 review。

课程大纲

完整路径见 curriculum.md(由 curriculum.json 渲染,勿手改)。

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. 9d ago First seen · 37 lines · 87 tokens per session scan A 11ecf35c711c

Subscribe to this mod's changes

rust-learn is a skill published in the GitHub repository swaylq/sijiao-skill (16 stars, last pushed 11d ago), licensed MIT. It adds 87 tokens to every session and 767 once invoked, about $0.0004 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 2026-08-30.