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 agentmods add skills/dora0512/interview-trainer/interview-coachnpx skills add Dora0512/interview-trainer --skill interview-coachgit clone --depth 1 https://github.com/Dora0512/interview-trainerWrote 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/dora0512/interview-trainer/interview-coach)<a href="https://agentmods.dev/skills/dora0512/interview-trainer/interview-coach"><img src="https://agentmods.dev/badge/skills/dora0512/interview-trainer/interview-coach.svg" alt="Measured on agentmods" height="20"></a>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 | $0.00033 | $0.00775 |
| Opus 5 | $0.00016 | $0.00387 |
| Sonnet 5 | $0.00007 | $0.00155 |
| Haiku 4.5 | $0.00003 | $0.00077 |
Grade A, and why
interview-coach 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 4d 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.
What it actually says
面试教练 Skill / Interview Coach
当调用此 skill 时，按以下规范生成面试内容。
语言规则：指令用中文写，但用用户的语言生成回答。
使用方式
/interview-coach <面试问题或技术主题>
例如：/interview-coach 冷启动流程、/interview-coach 如何治理 crash 率。
工作区路径
| 内容 | 路径 |
|---|---|
| 用户画像（身份/业务背景/量化数据锁定） | profile.md |
| 类比银行 | knowledge-base/analogy-bank.md |
| 答题规范（Mermaid 语法等） | knowledge-base/answer-norms.md |
| Mermaid 图库 | knowledge-base/diagrams.md |
| STAR 故事库 | knowledge-base/star-stories.md |
| 深度追问清单 | knowledge-base/deep-dive-questions.md |
| 项目知识图谱（如有） | knowledge-base/guides/*.md |
强制回答结构
每个回答必须包含以下 7 个部分：
1. 类比开场（必选）
用一句生活类比引入技术概念，参考 analogy-bank.md。没有现成的则创建一个贴近日常生活的新类比。
2. 背景（必选）
说明这个问题在什么业务场景下出现、为什么重要。结合 profile.md 中的业务背景（公司/规模/用户量）。
3. 原理（必选，含 Mermaid 图）
深入解释原理，必须含至少一张 Mermaid 图。优先从 diagrams.md 引用已验证的图。新建图严格遵循 answer-norms.md 的 Mermaid 语法规范（participant 用英文 ID + as 标签；flowchart 节点用 ["文字"]；连线标签 -- "文字" -->；sequenceDiagram 加 autonumber）。
4. 工程方案（必选，含代码引用）
结合用户真实项目的代码路径和类名（来自 profile.md / star-stories.md / knowledge-base/guides/*.md）：
> **项目实战**
> 模块：`<模块路径>`
> 核心类：<类名>
> 关键设计：[模式名称]
5. 数据结果（L3+ 必选）
给出量化指标，必须与 profile.md 锁定数据一致。
6. 权衡（L3+ 必选）
为什么选这个方案？对比了哪些替代？有什么风险或局限？如果重来会怎么做？
7. 扩展（可选）
延伸到更深层追问准备，链接 deep-dive-questions.md 相关问题。
项目故事引用
涉及项目经验时，优先引用 star-stories.md 中标准化故事，确保 STAR 结构完整。
输出格式
使用 Markdown：Mermaid 代码块、代码块、表格对比、callout（> [!tip] / > [!warning]）。若用户在 Obsidian 中使用，可用 wiki-link 交叉引用。
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.
- 4d ago First seen · 69 lines · 33 tokens per session scan A 47b89937318b
interview-coach is a skill published in the GitHub repository Dora0512/interview-trainer (10 stars, last pushed 1mo ago), licensed MIT. It adds 33 tokens to every session and 775 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.
Other skills, from other repositories
interview-analysis
This skill should be used when the user asks to "/interview-analysis", "analyze my interview", "debrief my interview", "what did I miss in the interview", "review my interview transcript", or pastes a transcript / notes from a just-finished interview. Reads the transcript (pasted, from --from-file, or auto-pulled from…
case-practice
This skill should be used when the user asks for "/case-practice", "/pm-job-search:case-practice", "drill me on product cases", "practice PM case interviews", "MC case drill", or "test my case-interview recognition". Runs drill 1 of the case-practice methodology — a multiple-choice (MC) rapid-recognition drill that…
project-interview-skill
在项目根目录生成导学.md与面经.md；大厂工程向、第一人称口播（每题≥150字完整STAR）、 简历一句话简介、仓库相对路径阅读指引、量化合并文末（待测+如何测）。触发：面经、导学、 interview analyzer、项目分析、面试准备、STAR、简历亮点。.
rolecraft
JD-driven study companion. Paste a job description; get back what to study, what to build, and where else this role exists. Use when the user pastes a job description, says "process this", asks "what would this role take", or wants concepts, tech stacks, companies, projects, or a dashboard summary derived from past…
pm-interview-grill
产品经理（PM）高强度面试拷问与即时教练技能。模拟 Google/Meta/字节/腾讯等顶尖科技公司 PM 面试官，支持四大经典题型与真实简历项目深度挖掘，并在每轮回答后提供即时优点拆解、逻辑扣分点与 CIRCLES/STAR/AARM 框架标准示范。当用户提出“PM面试”、“产品经理面试”、“PM烤问”、“产品经理模拟面试”、“PM烤问我”或需要 PM 面试指导时触发。.
principal-agent
当用户选择职业/组织/合作方式、困惑「为什么大公司磨洋工/小公司拼命」「该不该自己干」时调用。 核心理念: 委托人(主人)会把事做好, 代理人会为自己利益优化; 收益与创造价值绑得越紧, 越像委托人; 别让媒体洗脑你需要代理人。 不适用于: 具体薪酬谈判数字、组织架构设计细节。 Triggers: 激励/代理/主人/打工 vs 创业/利益绑定/principal/agent/incentive.