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知识库管理、摄取、同步和跨多个存储层（本地文件、MCP内存、向量存储、Git仓库）的检索。当用户想要保存、组织、同步、去重或搜索其知识系统时使用。
Instinct-based learning system that observes sessions via hooks, creates atomic instincts with confidence scoring, and evolves them into skills/commands/agents. v2.1 adds project-scoped instincts to prevent cross-project contamination.
Orchestrate building a brand-new feature end to end — research, plan, TDD implementation, review, and gated commit — by delegating each phase to the matching ECC agent. Use when adding a capability that does not exist yet.
Orchestrate bootstrapping a working MVP from a design or spec document — ingest the doc, plan thin vertical slices, scaffold the first end-to-end slice, then TDD-implement, review, and gated commit. Use to turn an SDD/PRD into a running starting point.
Orchestrate altering an existing, working feature to new desired behavior — update its tests to the new spec, change the implementation to match, review, and gated commit. Use when behavior is not broken but should be different.
Orchestrate fixing a bug — reproduce it as a failing regression test, fix to green, review, and gated commit — by delegating each phase to the matching ECC agent. Use when existing behavior is broken or wrong.
Shared orchestration engine for the orch-* skill family. Defines the gated Research-Plan-TDD-Review-Commit pipeline, the size classifier, the agent map, and the two human gates that the orch-* operation skills delegate to. Not usually invoked directly.
| name | knowledge-ops |
| description | 知识库管理、摄取、同步和跨多个存储层（本地文件、MCP内存、向量存储、Git仓库）的检索。当用户想要保存、组织、同步、去重或搜索其知识系统时使用。 |
| origin | ECC |
管理一个多层知识系统，用于跨多个存储库进行知识的摄取、组织、同步和检索。
推荐使用实时工作区模型：
~/.claude/projects/*/memory/当需要捕获新知识时：
这是什么类型的知识？
检查此知识是否已存在：
写入适当的层级：
更新任何相关的索引或摘要文件。
定期将会话历史同步到知识库：
将重要的工作区配置和脚本镜像到知识库：
当信息影响活跃执行时：
将来自多个来源的知识汇集到一处：
# 短期：当前会话上下文
使用 TodoWrite 进行会话内任务追踪
# 中期：项目记忆文件
写入 ~/.claude/projects/*/memory/ 以实现跨会话回溯
# 长期：GitHub / Linear / 知识库
将活跃执行事实置于 GitHub + Linear
将持久化综合上下文置于知识库仓库
# 语义层：MCP 知识图谱
使用 mcp__memory__create_entities 创建永久结构化数据
使用 mcp__memory__create_relations 进行关系映射
使用 mcp__memory__add_observations 添加关于已知实体的新事实
使用 mcp__memory__search_nodes 查找已有知识
在完成任何知识操作之前：