learn-claude-code/web/src/data/annotations/s07.json

{
  "version": "s07",
  "decisions": [
    {
      "id": "file-based-persistence",
      "title": "Tasks Stored as JSON Files, Not In-Memory",
      "description": "Tasks are persisted as JSON files in a .tasks/ directory on the filesystem instead of being held in memory. This has three critical benefits: (1) Tasks survive process crashes -- if the agent dies mid-task, the task board is still on disk when it restarts. (2) Multiple agents can read and write to the same task directory, enabling multi-agent coordination without shared memory. (3) Humans can inspect and manually edit task files for debugging. The filesystem becomes the shared database.",
      "alternatives": "In-memory storage (like v2's TodoWrite) is simpler and faster but loses state on crash and doesn't work across multiple agent processes. A proper database (SQLite, Redis) would provide ACID guarantees and better concurrency, but adds a dependency and operational complexity. Files are the zero-dependency persistence layer that works everywhere.",
      "zh": {
        "title": "任务存储为 JSON 文件，而非内存",
        "description": "任务以 JSON 文件形式持久化在 .tasks/ 目录中，而非保存在内存里。这有三个关键好处：(1) 任务在进程崩溃后仍然存在——如果 agent 在任务中途崩溃，重启后任务板仍在磁盘上；(2) 多个 agent 可以读写同一任务目录，无需共享内存即可实现多代理协调；(3) 人类可以查看和手动编辑任务文件来调试。文件系统就是共享数据库。"
      },
      "ja": {
        "title": "タスクをメモリではなく JSON ファイルとして保存",
        "description": "タスクはメモリ内ではなく .tasks/ ディレクトリに JSON ファイルとして永続化されます。3つの重要な利点があります：(1) プロセスのクラッシュ後もタスクが存続する――エージェントがタスク途中でクラッシュしても、再起動時にタスクボードはディスク上に残っています。(2) 複数のエージェントが同じタスクディレクトリを読み書きでき、共有メモリなしにマルチエージェント連携が可能になります。(3) 人間がデバッグのためにタスクファイルを検査・手動編集できます。ファイルシステムが共有データベースになります。"
      }
    },
    {
      "id": "dependency-graph",
      "title": "Tasks Have blocks/blockedBy Dependency Fields",
      "description": "Each task can declare which other tasks it blocks (downstream dependents) and which tasks block it (upstream dependencies). An agent will not start a task that has unresolved blockedBy dependencies. This is essential for multi-agent coordination: when Agent A is writing the database schema and Agent B needs to write queries against it, Agent B's task is blockedBy Agent A's task. Without dependencies, both agents might start simultaneously and Agent B would work against a schema that doesn't exist yet.",
      "alternatives": "Simple priority ordering (high/medium/low) doesn't capture 'task B literally cannot start until task A finishes.' A centralized coordinator that assigns tasks in order would work but creates a single point of failure and bottleneck. Declarative dependencies let each agent independently determine what it can work on by reading the task files.",
      "zh": {
        "title": "任务具有 blocks/blockedBy 依赖字段",
        "description": "每个任务可以声明它阻塞哪些任务（下游依赖）以及它被哪些任务阻塞（上游依赖）。Agent 不会开始有未解决 blockedBy 依赖的任务。这对多代理协调至关重要：当 Agent A 在编写数据库 schema、Agent B 需要写查询时，Agent B 的任务被 Agent A 的任务阻塞。没有依赖关系，两个 agent 可能同时开始，而 Agent B 会针对一个尚不存在的 schema 工作。"
      },
      "ja": {
        "title": "タスクに blocks/blockedBy 依存関係フィールド",
        "description": "各タスクは、自分がブロックするタスク（下流の依存先）と、自分をブロックするタスク（上流の依存元）を宣言できます。エージェントは未解決の blockedBy 依存がある タスクを開始しません。これはマルチエージェント連携に不可欠です：エージェント A がデータベーススキーマを書いていてエージェント B がそれに対するクエリを書く必要がある場合、B のタスクは A のタスクにブロックされます。依存関係がなければ両エージェントが同時に開始し、B はまだ存在しないスキーマに対して作業することになります。"
      }
    },
    {
      "id": "task-default-todo-coexistence",
      "title": "Task as Course Default, Todo Still Useful",
      "description": "TaskManager extends the Todo mental model and becomes the default workflow from s07 onward in this course. This 'default' is a course sequencing choice, not a universal runtime default claim. Both track work items with statuses, but TaskManager adds file persistence (survives crashes), dependency tracking (blocks/blockedBy), ownership fields, and multi-process coordination. Todo remains useful for short, linear, one-shot tracking where heavyweight coordination is unnecessary.",
      "alternatives": "Using only Todo keeps the model minimal but weak for long-running or collaborative work. Using only Task everywhere maximizes consistency but can feel heavy for tiny one-off tasks. Reminder signals are omission-reduction hints, not implicit mode switches; Task/Todo choice should still come from workflow intent and available tools.",
      "zh": {
        "title": "Task 为课程主线，Todo 仍有适用场景",
        "description": "TaskManager 延续了 Todo 的心智模型，并在本课程 s07 之后成为默认主线。两者都管理带状态的任务项，但 TaskManager 增加了文件持久化（崩溃后可恢复）、依赖追踪（blocks/blockedBy）、owner 字段与多进程协作能力。Todo 仍适合短、线性、一次性的轻量跟踪。"
      },
      "ja": {
        "title": "Task を主線にしつつ Todo も併存",
        "description": "TaskManager は Todo のメンタルモデルを拡張し、本コースでは s07 以降のデフォルトになる。どちらもステータス付き作業項目を扱うが、TaskManager にはファイル永続化（クラッシュ耐性）、依存関係追跡（blocks/blockedBy）、owner、マルチプロセス協調がある。Todo は短く直線的な単発作業では引き続き有効。"
      }
    },
    {
      "id": "task-write-discipline",
      "title": "Durability Needs Write Discipline",
      "description": "File persistence reduces context loss, but it does not remove concurrent-write risks by itself. Before writing task state, reload the JSON, validate expected status/dependency fields, and then save atomically. This prevents one agent from silently overwriting another agent's transition.",
      "alternatives": "Blind overwrite writes are simpler but can corrupt coordination state under parallel execution. A database with optimistic locking would enforce stronger safety, but the course keeps file-based state for zero-dependency teaching.",
      "zh": {
        "title": "持久化仍需要写入纪律",
        "description": "文件持久化能降低上下文丢失，但不会自动消除并发写入风险。写任务状态前应先重读 JSON、校验 `status/blockedBy` 是否符合预期，再原子写回，避免不同 agent 悄悄覆盖彼此状态。"
      },
      "ja": {
        "title": "耐久性には書き込み規律が必要",
        "description": "ファイル永続化だけでは並行書き込み競合は防げない。更新前に JSON を再読込し、`status/blockedBy` を検証して原子的に保存することで、他エージェントの遷移上書きを防ぐ。"
      }
    },
    {
      "id": "reminder-advisory-not-switch",
      "title": "Reminder Is Advisory, Not a Mode Switch",
      "description": "Reminder signals should be treated as omission-reduction hints, not as control-plane switches. Choosing Task vs Todo should come from workflow intent and currently available tools, while reminders only nudge usage when tracking appears stale.",
      "alternatives": "Treating reminders as implicit mode selectors looks convenient, but it hides decision boundaries and makes behavior harder to reason about during long sessions.",
      "zh": {
        "title": "Reminder 是提示，不是模式开关",
        "description": "Reminder 信号用于降低遗漏，不应当被当作控制面的模式切换器。Task/Todo 的选择应由工作流意图与可用工具决定，提醒只在追踪滞后时提供轻量提示。"
      },
      "ja": {
        "title": "Reminder は助言でありモード切替ではない",
        "description": "Reminder は取りこぼしを減らすための助言であり、制御面のモード切替として扱わない。Task/Todo の選択はワークフロー意図と利用可能ツールで決め、Reminder は追跡が滞ったときに軽く促す。"
      }
    },
    {
      "id": "todo-task-fast-matrix",
      "title": "Todo/Task Fast Decision Matrix",
      "description": "Use Todo for short one-session linear checklists. Use Task for cross-session work, dependencies, or teammate coordination. If uncertain, start with Task because downscoping is cheaper than migrating state mid-run.",
      "alternatives": "Always using Todo keeps the model minimal but breaks durability and collaboration. Always using Task maximizes consistency but may feel heavy for tiny one-shot notes.",
      "zh": {
        "title": "Todo/Task 快速判定矩阵",
        "description": "短时单会话线性清单用 Todo；跨会话、依赖、多人协作用 Task；拿不准时先用 Task，因为后续降级比半途迁移状态更便宜。"
      },
      "ja": {
        "title": "Todo/Task クイック判定マトリクス",
        "description": "短い単一セッションの直線タスクは Todo、セッション跨ぎや依存・協調がある作業は Task。迷うなら Task 開始が安全で、後で簡略化する方が途中移行より低コスト。"
      }
    }
  ]
}