interview-prep
Mock interview coach for AI engineering roles, built on the interview bank of AI Engineering from Scratch. Asks one question or one incident scenario, stops, and waits for the learner's own answer. Then it grades the answer against the bank, asks follow-ups one at a time, sends each gap to the lessons and manual sections that teach it, and keeps an append-only record in INTERVIEW-LEARNING.md. Trigger phrases: "interview prep", "mock interview", "ask me an interview question", "practise for my AI engineering interview", "run an incident scenario", "debugging round", "system design round", "inference engineer loop", "review my interview gaps", "how ready am I for the interview"
- License 许可
- MIT
- 最近更新
- 2026-11-10
- Stars
- ★ 7.8w
- Forks
- 1.4w
01 前言 Front Matter
- name
- bmad-review-adversarial-general
- description
- Execute review-adversarial-general
02 资源文件 7
- 参考文档agents/openai.yaml247 B
- 参考文档references/grading.md3.8 KB
- 参考文档references/loops.md3.1 KB
- 参考文档references/routing.md3.0 KB
- 参考文档references/scenario-mode.md3.6 KB
- 参考文档references/state-file.md3.1 KB
- 参考文档references/testing.md2.4 KB
03 SKILL.md 正文
review-adversarial-general
Read the entire task file at: {project-root}/_bmad/core/tasks/review-adversarial-general.xml
Follow all instructions in the task file exactly as written.
04 同仓库更多 Skills
write-manual
Writes a long technical manual that explains one subject at one pinned version, from its purpose to each request and response. Every listing comes from an offline capture, every claim traces to a ranked source, and an audit must report TOTAL 0. Use it for "write a manual", "write a 101 manual for <subject>", "manual.json", "add a manual section", "build a capture kit", "audit the manual", or "pin a spec version and document it".
start-learning
One-time onboarding for the AI Engineering from Scratch curriculum (542 lessons, 20 phases). Interviews the learner, runs the placement quiz, and writes LEARNING.md, a persistent study plan the learn skill drives. Trigger phrases: "start learning", "set up the course", "begin the curriculum", "onboard me", "create my learning plan"
motion-figure
Builds figures that move or respond to the reader, in three tiers: SMIL animations and slider widgets inside lessons, interactive mechanism figures that show the named parts of a real system with a computed verdict, and ordered dither bands in the course palette. Triggers: "animated figure", "add a slider widget", "interactive figure", "show how this system works", "make this diagram move", "dither masthead", "mechanism figure", "figure fence".
mcpa-certification
AI-native tutor and onboarding workflow for the MCPA (Model Context Protocol Associate) certification in AI Engineering from Scratch. Use when a learner wants to prepare for the MCPA, resume their certification path, learn the next lesson interactively, run and verify practical labs, take the diagnostic or a full mock, or remediate weak exam domains from GitHub with Claude Code, Codex, ChatGPT, Cursor, or another agent.
lesson-screen
Opens a lesson screen in the browser next to the terminal while a course tutor teaches. It shows the lesson's registered figures, code traces with real values, and clickable predictions. It also builds a figure for the lesson on the fly with the course figure skills and any figure skill the host has installed: a blueprint, a mechanism, an isometric machine, or a 3D model. Clicks return to the tutor as events. Trigger phrases: "open the lesson screen", "show me this visually", "show this in 3D", "draw the architecture", "visualize this lesson", "build a figure for this lesson", "lesson screen".
learn
Interactive lesson tutor for the AI Engineering from Scratch curriculum. Reads LEARNING.md, fetches the next lesson, teaches it section by section in the terminal, quizzes at the end, and records progress. Works cloned or entirely over raw.githubusercontent.com — no setup required. Trigger phrases: "next lesson", "teach me", "continue the course", "let's learn", "resume learning"