review-skill

review-skill is a skill for Claude Code from Dora0512/interview-trainer. It costs 45 tokens per session (1,147 once invoked), scanned A, original, MIT.

A one-command interview study card that gathers explanations, diagrams, project examples, résumé links, STAR stories, and follow-up questions for a selected topic.

In plain words
What is it for?
Use it to review a numbered topic or named skill and produce a single review card in the user's language.
Why use it?
It saves you from searching through separate study files when preparing to discuss a technical skill in an interview.

Skill for Claude Code

Written for Claude Code: user-invocable in frontmatter.

Part of the interview-trainer plugin — 9 skills shipped together

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.

agentmods
npx agentmods add skills/dora0512/interview-trainer/review-skill
Any agent
npx skills add Dora0512/interview-trainer --skill review-skill
Clone the repo
git clone --depth 1 https://github.com/Dora0512/interview-trainer

Made for: Claude Code.

Or install interview-trainer, the plugin that ships this one along with the rest of its 9 skills.

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 review-skill

README.md
[![agentmods](https://agentmods.dev/badge/skills/dora0512/interview-trainer/review-skill.svg)](https://agentmods.dev/skills/dora0512/interview-trainer/review-skill)
Your own site
<a href="https://agentmods.dev/skills/dora0512/interview-trainer/review-skill"><img src="https://agentmods.dev/badge/skills/dora0512/interview-trainer/review-skill.svg" alt="Measured on agentmods" height="20"></a>
Per session 45 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,147 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00045 $0.01147
Opus 5 $0.00023 $0.00574
Sonnet 5 $0.00009 $0.00229
Haiku 4.5 $0.00005 $0.00115

Measured 5d ago against content hash 43b2671a1f1b, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-05, from the pricing page.

Security

Grade A, and why

review-skill 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.

skills/review-skill/SKILL.md · 94 lines

How it starts

The opening of the file, as written. The whole thing — 94 lines — stays where its author put it; the contents beside it link to each section on GitHub.

复习技能点 Skill / One-Shot Review Card

当用户要复习某个面试技能点时,自动拉齐所有关联内容,生成一站式复习卡片。

语言规则:指令用中文写,但用用户的语言输出复习卡片。

使用方式

/review-skill <技能编号或名称>

例如:/review-skill 技能3/review-skill <话题名>/review-skill 协程

工作区路径

内容 路径
技能定义 + 简历关联 knowledge-base/topics.md
用户画像(简历卖点 + 量化数据锁定) profile.md
STAR 故事库 knowledge-base/star-stories.md
Mermaid 图库 knowledge-base/diagrams.md
深度追问清单 knowledge-base/deep-dive-questions.md
深度技能指南(如有) knowledge-base/guides/*.md
类比银行 knowledge-base/analogy-bank.md
真实面试记录 data/records/**/*.md
能力画像 data/capability-profile.md

执行步骤

  1. 定位技能点:从 knowledge-base/topics.md 找对应技能完整内容(掌握内容/能回答问题/达标判定/项目实践/简历关联)。
  2. 拉简历原文:从 profile.md 指向的简历读「简历关联」对应条目原文。
  3. 拉 STAR 故事:从 star-stories.md 读关联故事全文(S→T→A→R→追问准备)。
  4. 拉 Mermaid 图:从 diagrams.md 读关联图代码,直接嵌入。
  5. 拉深度追问:从 deep-dive-questions.md 找该技能对应追问列表。
  6. 拉技能深度指南(如有):从 knowledge-base/guides/*.md 提取关键章节。
  7. 拉真实面试失分点(如有):从 data/records/**/*.md 搜该技能相关记录,提取 哪些公司哪轮考过/当时水平/追问/答错点/发挥评估 ⚠️❌ 条目;从能力画像「真实面试验证记录」提取历史水平。

输出格式:一站式复习卡片

# 复习卡片:技能 X — [技能名称]

## 一句话类比
> [从 analogy-bank.md 取对应类比]

## 核心原理(含图)
[原理要点 + 嵌入 diagrams.md 的 Mermaid 图]

## 简历原文
> [简历对应段落完整引用] 量化数据:[profile.md 锁定的数字]

## STAR 故事
[完整 STAR 故事]

## 项目实战代码
> 模块:`<模块路径>` 核心类:`<类名>` 关键设计:[模式名称]

## 面试模拟
### 面试官可能问的问题
[从 deep-dive-questions.md 列 3-5 个追问]
### 每题参考回答结构
[类比开场 → 背景 → 原理 → 工程方案 → 数据结果 → 权衡]

## 真实面试复盘
> 你在真实面试中被考到该技能的表现记录:
| 公司 | 轮次 | 日期 | 达到水平 | 面试官追问 | 你的失分点 |
|------|------|------|---------|-----------|-----------|
**重点补强**:(基于真实失分点,给最需补强的 1-2 个知识点)
> 该技能未被真实面试考过时,显示"暂无真实面试记录,建议 `/interview mock` 模拟验证"。

## 自测清单
□ 能用类比解释核心概念(30秒)
□ 能画出关键流程图(1分钟)
□ 能讲出项目实战案例 + 量化数据(2分钟)
□ 能应对 3 个以上追问
□ 简历数字能脱口而出
□ 真实面试失分点已补强(如有)

关键规则

  1. 类比必须有:从 analogy-bank.md 取,没有则新建并标注
  2. 量化数字锁定:与 profile.md 锁定数据一致
  3. Mermaid 图必须嵌入:是代码块,不是链接
  4. 追问至少 3 个
  5. 自测清单必须有
  6. 真实面试复盘必须有:被考过则展示失分点和补强建议

Read the full file on GitHub · 94 lines

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. 5d ago First seen · 94 lines · 45 tokens per session scan A 43b2671a1f1b

Subscribe to this mod's changes

review-skill is a skill published in the GitHub repository Dora0512/interview-trainer (10 stars, last pushed 1mo ago), licensed MIT. It adds 45 tokens to every session and 1,147 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.

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