Interview Bank
328 questions total; 1 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#skills1#cost14#evaluation14#reliability12#agent-skills11#architecture11#observability10#error-handling9#security9#api-design6#coding-agent6#debugging5
235 more tagsShow fewer tags
#idempotency5#streaming5#structured-output5#chunking4#deployment4#distributed-systems4#rag4#system-prompt4#tool-calling4#client3#embeddings3#failure-modes3#ingestion3#mcp3#message-bus3#operations3#progressive-disclosure3#ranking3#timeline3#agent-loop2#agentic-rag2#agents-sdk2#caching2#citations2#code-review2#communication2#concurrency2#consistency2#context2#context-engineering2#context-rot2#cost-control2#data-modeling2#grounding2#hybrid-search2#langgraph2#latency2#model-migration2#model-routing2#multi-agent2#ordering2#pipeline-design2#prompt-basics2#prompt-engineering2#protocol2#rate-limiting2#react2#redis-streams2#responses-api2#retrieval2#retrieval-quality2#routing2#runtime2#sse2#state-management2#statelessness2#subagents2#system-design2#tool-design2#tooling2#tracing2#trade-offs2#transport2#vector-database2#versioning2#workflow2#abstention1#access-control1#agent-design1#agent-quality1#altitude1#approvals1#async1#async-task1#atomicity1#attention-budget1#auth1#av-sync1#behavioral1#bm251#candidate-selection1#capacity-planning1#chain-of-thought1#checkpointing1#ci1#citation-verification1#claude-code1#cli-design1#cloud1#compaction1#compression1#content-hash1#context-compression1#context-window1#contextual-retrieval1#cost-optimization1#cross-model1#dag1#data-quality1#database1#decision-making1#decomposition1#degradation1#deliberate-practice1#design1#diagnostics1#dimensions1#distribution1#docker1#documentation1#engineering-judgement1#engineering-tradeoffs1#eval1#event-driven1#fallback1#fan-out1#ffmpeg1#forking1#four-elements1#framework-design1#framework-selection1#golden-set1#hallucination1#handoffs1#headless1#hnsw1#hybrid1#hyde1#image-generation1#incremental-recompute1#incremental-sync1#index-maintenance1#index-routing1#indexing1#information-retrieval1#instruction-hierarchy1#intent-routing1#interrupt-merge1#interview-prep1#invalidation1#isolation1#ivfflat1#just-in-time1#knowledge-organization1#lease1#llm-as-judge1#llm-output-quality1#long-context1#loop-guard1#media-pipeline1#metadata1#metrics1#mobile1#model-selection1#multi-tenancy1#multimodal1#nodejs1#orchestration1#pagination1#parent-child1#pdf-parsing1#performance1#permissions1#persistence1#pgvector1#pipeline-reliability1#portfolio1#prioritization1#production-readiness1#prompt-assembly1#prompt-caching1#prompt-injection1#prompt-limits1#prompt-techniques1#prompt-template1#prompt-versioning1#provider-abstraction1#quality-check1#quantization1#query-transformation1#quiet-hours1#rank-fusion1#reasoning1#recall1#redis1#reflection1#refusal1#reporting1#reproducibility1#rerank1#retrieval-failure1#retrieval-metrics1#retry1#retry-semantics1#retry-strategy1#review1#rollback1#rrf1#sandbox1#sandboxing1#scalability1#scheduling1#schema-design1#scoping1#scripts1#secrets-management1#self-assessment1#self-presentation1#self-reflection1#service-architecture1#session-management1#sessions1#sharding1#skill-authoring1#skill-description1#spec1#state-machine1#stateless1#stopping-criteria1#subtitles1#task-graph1#team-governance1#testing1#tool-budget1#tool-execution1#tool-naming1#tools1#tts1#tuning1#ux1#validation1#vector-index1#verification1#workflow-engine1#xml-tags1
Mastering Claude: From Conversation to Claude Code in 5 Days
D4 Extending Claude Code: Hooks (Deterministic) vs. CLAUDE.md (Advisory), Skills, Subagents, Plugins, Wiring Up an MCP Server, CLI Tools First
What is progressive loading for skills, why does it save context, and how should the description be written?skill 的渐进式加载是怎么回事?为什么能省上下文?description 应该怎么写?
Common in ChinaCommon overseasIntermediate#skills#contextHow to reason about it · think before answering
- This tests the on-demand loading idea and whether you have actually written a skill. The third part separates candidates: a poorly written description makes the skill dead weight.
- Mechanism: at session start only each skill's one-line description from the frontmatter is resident; the body loads when the model judges the task relevant or the user types /name. Body length therefore barely affects daily cost, so it can hold long procedures, examples, and caveats.
- Contrast with CLAUDE.md: loaded in full every session, a fixed cost; a procedure used twice a week wastes the window the rest of the time. Moving such content into skills is how CLAUDE.md keeps shrinking after pruning.
- Writing the description: state what it does plus the phrases a user would say, about a hundred words; too broad triggers on unrelated tasks, too narrow never triggers. Add disable-model-invocation: true for side-effecting workflows so only /name invokes them; $ARGUMENTS takes parameters; allowed-tools pre-approves commands.
- Follow-ups: how do you test triggering? Try several natural phrasings and check whether the body loaded. Skill versus subagent: a skill loads a manual into the current context; a subagent opens a separate context to do work; they compose.
分析过程 · 先想清楚再作答
- 这题考的是「按需加载」这个设计思想,以及你有没有真写过 skill。第三问是区分度:description 写不好,skill 就形同虚设。
- 机制:会话开始时只有每个 skill 的 frontmatter 里那一行 description 常驻上下文;当模型判断当前任务相关、或用户输入 /name 时,正文才被读进来。所以正文长短几乎不影响日常成本,可以放几十步的流程、示例、注意事项。
- 对比 CLAUDE.md:它整份每次加载,是固定成本;一周只用两次的流程放进去等于其余时间白占窗口。把这类内容挪到 skill,是「删到不能再删」之后 CLAUDE.md 还能继续变短的主要手段。
- description 的写法:说清做什么 + 用户会怎么说(触发词),一百来字;太泛会被无关任务误触发,太窄永远触发不到。有副作用的流程(部署、发消息)加 disable-model-invocation: true 只允许手动 /name 触发。$ARGUMENTS 接参数,allowed-tools 预授权命令。
- 可预期的追问:怎么测 skill 有没有被触发?用几个自然语言说法试,看模型是否读了正文;再追问「skill 与 subagent 的区别」——skill 是在当前上下文里加载一份说明书,subagent 是另起一个上下文去做事,两者可以组合。
Key points
- Only the description is resident; the body loads on invocation, so body length barely costs
- CLAUDE.md loads in full each time; moving occasional procedures to skills keeps it short
- Write the description as what it does plus how users phrase it, about a hundred words
- Side-effecting workflows get disable-model-invocation; $ARGUMENTS carries parameters
答题要点
- 只有 description 常驻,正文在被触发时才加载;正文长短几乎不影响日常成本
- CLAUDE.md 整份每次加载;偶尔用的流程挪进 skill 是让它继续变短的手段
- description 写「做什么 + 用户会怎么说」,一百来字,不泛不窄
- 副作用流程加 disable-model-invocation;$ARGUMENTS 接参数