ai-engineering-from-scratch/phases/19-capstone-projects/01-terminal-native-coding-agent/quiz.json at main · zhaozhiqiangjianming-ship-it/ai-engineering-from-scratch · GitHub

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{
  "lesson": "01-terminal-native-coding-agent",
  "title": "Capstone 01 — Terminal-Native Coding Agent",
  "questions": [
    {
      "stage": "pre",
      "question": "Which loop shape do 2026 terminal coding agents share?",
      "options": [
        "Plan, act, observe, recover",
        "Encode, decode, sample, stream",
        "Train, evaluate, deploy, monitor",
        "Fetch, embed, rank, synthesize"
      ],
      "correct": 0,
      "explanation": ""
    },
    {
      "stage": "pre",
      "question": "Why does the harness run each task inside an E2B or Daytona sandbox?",
      "options": [
        "To isolate filesystem and tool execution from the host so the worktree can be torn down on completion",
        "To bypass model-provider rate limits",
        "To benchmark token throughput on cold caches",
        "To enable GPU access for the agent loop"
      ],
      "correct": 0,
      "explanation": ""
    },
    {
      "stage": "check",
      "question": "Which built-in hook is the natural place to block destructive shell commands before they execute?",
      "options": [
        "PreToolUse",
        "SessionStart",
        "Stop",
        "PostToolUse"
      ],
      "correct": 0,
      "explanation": ""
    },
    {
      "stage": "check",
      "question": "The capstone caps each tool result at roughly 4k tokens. Which failure mode does that primarily prevent?",
      "options": [
        "Sandbox escape via malicious shell metacharacters",
        "Context poisoning and runaway cost when a tool returns a large dump",
        "Stale plan state across resumed sessions",
        "Model overfitting to tool-call traces"
      ],
      "correct": 1,
      "explanation": ""
    },
    {
      "stage": "check",
      "question": "What does the PreCompact hook do at the 150k-token mark?",
      "options": [
        "Cancels the run and refunds the user budget",
        "Summarizes older turns into a prior-state block so the plan and new observations still fit",
        "Force-pushes the current branch to back up progress",
        "Switches the backing model to a smaller draft model"
      ],
      "correct": 1,
      "explanation": ""
    },
    {
      "stage": "post",
      "question": "Which baseline does the capstone compare its harness against on a 30-issue SWE-bench Pro subset?",
      "options": [
        "OpenCode",
        "mini-swe-agent",
        "Live-SWE-agent",
        "Aider"
      ],
      "correct": 1,
      "explanation": ""
    },
    {
      "stage": "post",
      "question": "Which metric set is the deliverable measuring against?",
      "options": [
        "WER, MOS, and first-audio-out",
        "Perplexity, BLEU, and ROUGE",
        "pass@1, turns-per-task, and dollar-per-task",
        "MRR@10 and nDCG@10"
      ],
      "correct": 2,
      "explanation": ""
    }
  ]
}