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#workflow-design1#evaluation13#cost11#reliability11#agent-skills7#security6#idempotency5#streaming5#system-design5#prompt-injection4#architecture3#observability3
126 more tagsShow fewer tags
#agent-loop2#api-design2#chunking2#cost-tradeoff2#debugging2#distributed-systems2#error-handling2#hybrid-search2#llm-as-judge2#multi-agent2#multi-hop2#oauth2#operations2#pipeline-design2#prompt-caching2#rag2#recall2#retrospective2#retry2#scheduling2#sse2#tool-permissions2#trade-offs2#access-control1#agentic-rag1#agents-sdk1#analytics1#architecture-review1#behavioral1#budget-control1#caching1#cancellation1#checkpointing1#circuit-breaker1#citation-verification1#client1#client-integration1#coding-agent1#compaction1#compliance1#concurrency1#confused-deputy1#context-engineering1#contextual-retrieval1#copyright1#correctness1#cost-control1#customer-support1#data-quality1#database1#deployment1#distribution1#embedding-migration1#error-propagation1#escalation1#evidence1#faithfulness1#fallback1#feedback-loop1#fencing-token1#filter-pushdown1#filtering1#framework-design1#graph-rag1#guardrails1#handoff1#image-generation1#integration1#iterative-scan1#json-parsing1#labeling1#latency1#latency-budget1#least-privilege1#long-context1#long-session1#long-term-memory1#mcp1#message-bus1#methodology1#model-migration1#multi-tenancy1#notifications1#ocr1#offline-testing1#project-storytelling1#protocol-versions1#quality1#query-rewriting1#rate-limiting1#reconnect1#refusal1#replay1#reproducibility1#rerank1#resume1#retrieval1#risk-assessment1#rollout1#routing1#runtime1#safety1#scaling1#self-introduction1#split-brain1#state-management1#state-persistence1#statelessness1#stdio-transport1#storytelling1#subagent1#subagents1#subscriptions1#test-strategy1#thresholds1#timezone1#token-accounting1#tool-design1#tool-schema1#tools1#trust-boundary1#ux1#verification1#versioning1#workflow-engine1#zero-downtime1
Agent Skills in 7 Days: Turn Experience Into Reusable Capability
D4 Skills With Scripts: Executable Attachments, Dependencies and Sandboxing, Cross-Platform Support, and Breaking Down Document-Handling Skills
What security risks come with bundling scripts in a skill, how would you contain them, and why should document tasks follow plan, validate, then execute?skill 里带脚本会带来哪些安全风险?你会怎么限制它?另外,为什么文档处理这类任务要先规划再校验后执行?
Common in ChinaCommon overseasDeep dive#agent-skills#security#workflow-designHow to reason about it · think before answering
- Two halves; answer both. Security is about boundaries, the three-step flow is about process, and both come down to putting a gate before an irreversible action.
- Cover security in four layers. Source: a third-party skill's scripts are someone else's code, so read the scripts directory before installing, exactly as you would skim a package. Skills invite less scrutiny because they look like documentation.
- Permissions: pre-approve at command granularity, allowing read-only git subcommands rather than arbitrary shell, and remember the field is experimental with uneven support, so do not rely on it alone.
- Input: files and API responses are untrusted. A script that does not execute them is not directly exploitable, but script output enters the model's context, so echoing a large blob of external content effectively speaks it to the model. Actions: gate delete, overwrite and publish behind a dry run or explicit flag, because agents retry.
- For the second half, give the three steps and stress that the value is in the middle one: analysis produces ground truth, validation compares plan against it with self-correctable errors, and only the fill step writes files.
- Name two disciplines: validation never mutates and fill never validates, or the model loses its pause between planning and execution; and intermediate artifacts must be written to disk so the validator can read them.
- Expected follow-up: why not validate while filling? Filesystems have no transactions, and a half-written document is worse than none because it looks complete.
分析过程 · 先想清楚再作答
- 这题有两半,别只答一半。前半考安全边界,后半考流程设计,两者的共同点是「在不可逆的动作之前留一道闸门」。
- 安全这一半按来源、权限、输入、动作四层说。来源:第三方 skill 里的脚本就是别人的代码,装之前要读 scripts 目录,跟装一个包之前看两眼是一回事——skill 更容易被当成文档而放松警惕。
- 权限:预批工具要卡到命令级,写「允许 git 的只读子命令」而不是「允许任意 shell」;而且这个字段还是实验性的,各家支持不一,不要把安全性全押在它上面。
- 输入:脚本处理的外部文件与接口返回是不可信输入。脚本不把它当代码执行就不会被直接利用,但**脚本的输出会进模型上下文**,原样回显一大段外部内容等于把那段话讲给模型听。动作:删除覆盖发布要给预演开关或确认参数,因为 Agent 会重试。
- 第二半给三步流程,并强调价值全在中间那步:分析脚本产出的是真值,模型不该凭记忆猜字段;校验脚本比对计划与真值,错误信息要够模型自己改对;填充脚本才落盘。
- 两条设计纪律要点出来:校验脚本不改数据、填充脚本不做校验,混在一起模型就没法在计划和执行之间停下来;中间产物要落盘成文件,否则校验脚本读不到,你也没法打开看。
- 可预期的追问是「为什么不能边填边校验」。答案是文件系统没有事务,写了一半的文档比完全没写更麻烦——它看起来是完整的。
Key points
- Third-party skill scripts are someone else's code; read the scripts directory before installing.
- Pre-approve tools at command granularity, and do not rely on an experimental field for safety.
- External input is untrusted, and script output enters context, so never echo large external blobs verbatim.
- The value of the three-step flow is the middle step: ground truth, self-correctable errors, then writing.
- Validation never mutates, fill never validates, intermediates go to disk, and never validate while writing.
答题要点
- 第三方 skill 的脚本就是别人的代码,装之前要读一遍 scripts 目录。
- 预批工具按最小权限、卡到命令级;该字段仍是实验性的,不能全押在它上面。
- 外部输入不可信,且脚本输出会进上下文,不要原样回显大段外部内容。
- 三步流程的价值全在中间那步校验:分析出真值、校验给可自纠的错误、执行才落盘。
- 校验不改数据、填充不做校验、中间产物落盘;不要边填边校验,半成品文档看起来是完整的。