何时激活
用户希望将信息保存到其知识库 将文档、对话或数据摄取到结构化存储中 跨系统同步知识(本地文件、MCP 记忆、Supabase、Git 仓库) 对现有知识进行去重或整理 用户说“保存到知识库”、“同步知识”、“关于 X 我知道什么”、“摄取这个”、“更新知识库” 任何超出简单记忆回忆的知识管理任务
affaan-m/ECC
Use it for engineering tasks; the detail page covers purpose, installation, and practical steps.
npx skills add https://github.com/affaan-m/ECC --skill "docs/zh-CN/skills/knowledge-ops"Source checked Jul 28, 2026·Refresh due Oct 26, 2026
Limited to facts supported by the pinned source
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。
npx skills add https://github.com/affaan-m/ECC --skill "docs/zh-CN/skills/knowledge-ops"The pinned source contains about 72 English words and 25 usable sections. That evidence supports a source profile, not a complete guide.
72 source words · 25 usable sections
What the source actually contains
Sections are extracted automatically from the pinned SKILL.md and link back to the source.
用户希望将信息保存到其知识库 将文档、对话或数据摄取到结构化存储中 跨系统同步知识(本地文件、MCP 记忆、Supabase、Git 仓库) 对现有知识进行去重或整理 用户说“保存到知识库”、“同步知识”、“关于 X 我知道什么”、“摄取这个”、“更新知识库” 任何超出简单记忆回忆的知识管理任务
来源: GitHub 议题、PR、讨论、发布说明、Linear 议题/项目/文档 用途: 工作的当前操作状态 规则: 如果某事物影响活跃的工程计划、路线图、发布或版本,优先将其放在此处
来源: GitHub 议题、PR、讨论、发布说明、Linear 议题/项目/文档 用途: 工作的当前操作状态 规则: 如果某事物影响活跃的工程计划、路线图、发布或版本,优先将其放在此处
Choose a different workflow
Knowledge base management, ingestion, sync, and retrieval across multiple storage layers (local files, MCP memory, vector stores, Git repos). Use when the user wants to save, organize, sync, deduplicate, or search across their knowledge systems.
A separate implementation from affaan-m/ECC; compare its source, maintenance signals, and permission requirements.
Open source detailUse it for engineering tasks; the detail page covers purpose, installation, and practical steps.
A separate implementation from affaan-m/ECC; compare its source, maintenance signals, and permission requirements.
Open source detailAudit skill SKILL.md files for compliance with the agentskills.io specification and house conventions. Checks frontmatter fields (name, description, compatibility, metadata, argument-hint), metadata sub-fields (author, scope, layer, confirms), and layer/suffix consistency. Use when adding new skills, reviewing skill quality, or ensuring all skills follow the spec. Triggers: "audit skills", "check skill spec", "skill compliance", "are my skills up to spec", "/claude-skill-spec-audit".
A separate implementation from jackchuka/skills; compare its source, maintenance signals, and permission requirements.
Open source detailFAQ
The source record exposes this install command: npx skills add https://github.com/affaan-m/ECC --skill "docs/zh-CN/skills/knowledge-ops". Inspect the command and pinned source before running it.
The pinned source record declares support for: claude code.
Quality breakdown
Based on traceable docs and repository signals; stars are not treated as quality.
Compare before choosing
These links are selected from shared tasks, functions, stacks, platforms, and same-name variants. Compare the source owner, documentation, permissions, and maintenance signals.
Knowledge base management, ingestion, sync, and retrieval across multiple storage layers (local files, MCP memory, vector stores, Git repos). Use when the user wants to save, organize, sync, deduplicate, or search across their knowledge systems.
Use it for engineering tasks; the detail page covers purpose, installation, and practical steps.
Audit skill SKILL.md files for compliance with the agentskills.io specification and house conventions. Checks frontmatter fields (name, description, compatibility, metadata, argument-hint), metadata sub-fields (author, scope, layer, confirms), and layer/suffix consistency. Use when adding new skills, reviewing skill quality, or ensuring all skills follow the spec. Triggers: "audit skills", "check skill spec", "skill compliance", "are my skills up to spec", "/claude-skill-spec-audit".
Patterns and architectures for autonomous Claude Code loops — from simple sequential pipelines to RFC-driven multi-agent DAG systems.
GAN-inspired Generator-Evaluator agent harness for building high-quality applications autonomously. Based on Anthropic's March 2026 harness design paper.
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: