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https://github.com/shareAI-lab/analysis_claude_code.git
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48 lines
3.2 KiB
JSON
48 lines
3.2 KiB
JSON
{
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"version": "s19",
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"decisions": [
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{
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"id": "composition-over-new-loop",
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"title": "The Harness Composes Previous Layers",
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"description": "The integrated harness does not replace the loop with a new architecture. It composes memory, tasks, skills, background work, teams, worktrees, and MCP around the same core model-tool-result cycle.",
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"alternatives": "A new orchestration framework would look more impressive, but it would hide the continuity across the course.",
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"zh": {
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"title": "Harness 组合既有层，而不是换掉循环",
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"description": "集成后的 Harness 没有用新架构替换循环，而是把 memory、task、skill、后台任务、团队、worktree、MCP 组合到同一个模型-工具-结果循环周围。"
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},
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"ja": {
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"title": "Harness は既存レイヤーを統合する",
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"description": "統合された Harness はループを新しい構造で置き換えません。memory、task、skill、バックグラウンド処理、チーム、worktree、MCP を同じ model-tool-result サイクルの周囲に合成します。"
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}
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},
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{
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"id": "single-source-of-runtime-truth",
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"title": "Runtime State Has Named Sources",
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"description": "Context assembly pulls from named sources such as memory, task graph, skills, tool registry, and policy. This keeps a large agent debuggable because each piece of prompt context has an owner.",
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"alternatives": "Dumping everything into one prompt string is shorter, but it becomes impossible to tell which subsystem caused a bad decision.",
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"zh": {
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"title": "运行时状态来自具名来源",
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"description": "上下文组装从 memory、task graph、skills、tool registry、policy 等具名来源读取。大型 agent 因此仍可调试，因为每块 prompt context 都有清晰归属。"
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},
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"ja": {
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"title": "ランタイム状態には名前付きの出所がある",
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"description": "コンテキスト組み立ては memory、task graph、skills、tool registry、policy などの名前付きソースから取得します。各 prompt context に所有者があるため、大きなエージェントでもデバッグ可能です。"
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}
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},
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{
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"id": "recovery-is-first-class",
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"title": "Recovery Is Part of the Main Flow",
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"description": "Compaction, error recovery, and asynchronous result collection are normal loop behavior. The harness handles recovery and resumption through named paths instead of scattered exception branches.",
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"alternatives": "Leaving recovery at the edges makes it harder to see which state is safe to resume.",
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"zh": {
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"title": "恢复能力是一等流程",
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"description": "压缩、错误恢复和异步结果收集都属于正常循环。Harness 通过明确的路径处理恢复与续跑，而不是把逻辑散落在异常分支中。"
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},
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"ja": {
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"title": "リカバリは主要フローの一部",
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"description": "圧縮、エラー回復、非同期結果収集を通常のループ動作として扱います。Harness は回復と再開を名前付きの経路にまとめ、例外分岐へ散らしません。"
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}
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}
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]
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}
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