Interview Bank
328 questions total; 2 shown with current filters.
CourseAllFrom Frontend Engineer to Agent Engineer in 30 DaysPrompt Engineering From Scratch in 5 DaysMastering Claude: From Conversation to Claude Code in 5 DaysMastering Codex and the OpenAI Agents SDK in 5 DaysMCP in 7 Days: Wire Tools Into Any AgentAgent Skills in 7 Days: Turn Experience Into Reusable CapabilityContext Engineering in 5 DaysRAG in 14 Days: From Retrieval to Trustworthy AnswersBuild an AI Short-Drama Production Pipeline With Agents in 14 Days
Tag
All#coding-agent2#architecture8#cost4#multi-agent4#agent-skills3#context3#evaluation3#llm-basics3#pipeline-design3#security3#system-design3#tool-design3
125 more tagsShow fewer tags
#abstention2#agent-loop2#behavioral2#claude-md2#consistency2#context-engineering2#context-window2#distributed-systems2#embeddings2#framework-design2#interview-prep2#interview-process2#mcp2#memory2#observability2#orchestration2#prompt-engineering2#provider-abstraction2#rag2#resume2#scalability2#scheduling2#skills2#sse2#streaming2#structured-output2#tool-calling2#agent-basics1#agent-design1#agent-sdk1#agentic-rag1#agents-md1#api-design1#async-task1#auth1#backoff1#bi-encoder1#build-vs-buy1#career1#chunking1#communication1#concurrency1#configuration1#consistent-hashing1#content-safety1#context-assembly1#context-management1#coreference1#cost-accounting1#cost-analysis1#cross-encoder1#data-quality1#encoding1#failure-analysis1#fairness1#few-shot1#ffmpeg1#fine-tuning1#frontend1#global-market1#golden-set1#hooks1#human-in-the-loop1#hybrid-search1#image-generation1#ingestion1#json-schema1#jwt1#langgraph1#long-context1#long-term-memory1#maintenance1#mcp-basics1#media-pipeline1#mental-model1#message-bus1#messages-api1#migration1#model-routing1#moderation1#modularity1#multi-turn1#normalisation1#openai1#operations1#ordering1#overlap1#primitives1#prioritization1#priority-queue1#proactive-messaging1#product-engineering1#project-storytelling1#prompt1#prompt-basics1#prompt-bloat1#prompt-design1#prompt-injection1#prompt-surface1#prompt-techniques1#prompting1#protocol1#query-rewriting1#rag-basics1#rate-limiting1#redis-streams1#reliability1#responses-api1#retrieval1#routing1#sampling1#schema-validation1#scripts1#server-design1#sharding1#similarity1#skill-design1#stakeholder-communication1#star1#state-machine1#system-prompt1#test-set1#token-budget1#tts1#workflow-engine1
Mastering Codex and the OpenAI Agents SDK in 5 Days
D1 Getting Started With the Codex CLI: Install, AGENTS.md, Approval Modes and the Sandbox, Common Commands
What belongs in a project instruction file for a coding agent (such as Codex's AGENTS.md), what does not, and why is there a size limit?给 coding agent 写的项目说明文件(比如 Codex 的 AGENTS.md)应该写什么、不该写什么?为什么它要有大小上限?
Common in ChinaCommon overseasBasic#coding-agent#context#agents-mdHow to reason about it · think before answering
- This probes whether you treat context as a scarce resource, not whether you know the file format; answering with a project overview signals inexperience.
- Use one test: can the agent discover this by opening files? If yes, leave it out (directory layout, framework); if no, write it down (conventions, no-go areas, environment facts, test commands).
- Add the lookup rules: a global file in the home directory, then project files concatenated from the repo root down to the current directory, so closer files override earlier ones.
- The size cap (32 KiB by default in Codex) forces prioritization: a long manual crowds out the task and dilutes adherence to every rule.
- Expect the follow-up: will the model always obey the file? No, it is prompt text and fades over long sessions; hard limits belong to the sandbox and approvals.
分析过程 · 先想清楚再作答
- 这题考的不是文件格式,而是你对「上下文是有限资源」有没有工程直觉。把它答成「写项目介绍」会被判为没真用过。
- 拆法是一个判断句:这条信息 agent 打开文件自己能不能发现?能发现的不写(目录结构、用了什么框架),发现不了的才写(约定、禁区、环境事实、测试命令)。
- 再补一层查找规则:全局层在用户目录,项目层从根目录到当前目录依次拼接,越靠近当前目录越靠后、越优先,所以子目录可以覆盖根规则。
- 大小上限(Codex 默认 32 KiB)的意义是逼你做取舍:手册太长会挤占任务本身的上下文,还会让模型对每一条规则的遵守度下降。
- 可预期的追问:写在说明文件里的规则模型一定会遵守吗?不一定,它是提示词的一部分,会被长对话稀释;硬约束要靠沙箱与审批,不是靠文字。
Key points
- Write conventions, no-go areas, environment facts and verification commands; skip anything discoverable from the files
- Lookup goes global first, then project files concatenated root-down, with closer files taking precedence
- The size cap forces you to keep only high-value guidance so the task itself keeps its context budget
- Instruction files are advisory; hard limits come from the sandbox and approval policy
答题要点
- 写约定、禁区、环境事实和验证命令;不写 agent 自己打开文件就能发现的内容
- 查找顺序是全局文件在前、项目文件从根到当前目录拼接,越靠近当前目录越优先
- 大小上限逼你只保留高价值信息,避免挤占任务上下文、降低规则遵守度
- 文字规则是建议性的,真正不能越的线交给沙箱与审批
D2 Codex, Level Up: Cloud Tasks, Code Review, MCP Integration, Custom Instructions, IDE Integration
MCP servers and skills both extend a coding agent. When do you reach for each, and what goes in the project instruction file instead?MCP server 和 skill 都是在给 coding agent 加能力,什么时候该用哪一个?项目说明文件又放什么?
Common in ChinaCommon overseasBasic#mcp#skills#coding-agentHow to reason about it · think before answering
- This tests separation of abstraction levels, the tooling-side version of the increasingly common 'function calling vs MCP vs skills' question.
- Ask what is being added: access to an external system (tickets, databases, internal services) is MCP, a protocol-level tool; a multi-step procedure (release checklist, migration flow) is a skill, a prompt-level workflow package; conventions to obey every session belong in the instruction file.
- Contrast triggers: MCP tools are invoked by the model when it needs data; skills are invoked explicitly by name or matched by description; instruction files are loaded unconditionally at session start.
- Conclude: rules in the instruction file, external systems via MCP, procedures as skills; keep each fact in one place to avoid contradictions.
- Expect the follow-up: can a skill use MCP tools? Yes; a skill's steps can call for a tool, the layers are orthogonal, not substitutes.
分析过程 · 先想清楚再作答
- 这题考的是抽象层次的区分,是国内面试开始高频出现的「Function Call / MCP / Skills 三者区别」的工具侧版本。
- 拆法是问「加的是什么」:加的是访问外部系统的能力(查工单、读数据库、调内部服务)就是 MCP,它是协议层的工具;加的是一套多步骤的做法(发版检查、迁移流程)就是 skill,它是提示词层的流程包;每次会话都要遵守的约定就是项目说明文件。
- 再给触发方式的差别:MCP 工具由模型在需要数据时调用;skill 由用户显式点名或由模型按描述匹配;说明文件每次会话开头无条件读入。
- 结论落到一句话:规矩归说明文件、外部系统归 MCP、流程归 skill;同一件事只放一处,避免三处互相矛盾。
- 可预期的追问:skill 里能不能调 MCP 工具?可以,skill 的步骤里可以要求使用某个工具,两者是正交的层次,不是替代关系。
Key points
- MCP adds tools that reach external systems, invoked by the model on demand
- Skills add multi-step procedures, triggered by name or matched by description
- The instruction file holds conventions, no-go areas and environment facts read every session
- The three are orthogonal: rules, external systems, procedures each live in one place; a skill may call for an MCP tool
答题要点
- MCP 加的是访问外部系统的工具,由模型按需调用
- skill 加的是多步骤流程,由用户点名或按描述匹配触发
- 项目说明文件放每次会话都要遵守的约定、禁区与环境事实
- 三者正交:规矩、外部系统、流程各放一处,skill 里可以要求用某个 MCP 工具