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Build and maintain a persistent knowledge base (LLM Wiki) using native backend tools. Supports ingesting PDFs, Markdown, and TXT files, and querying or linting the data. Use this whenever the user wants to add, retrieve, or manage their own local knowledge base and documents.
用 Codex 或 Claude 帮你安装 复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。
基于 SOC 职业分类
Must use first when skill capabilities may help complete a task.
Creates, converts, or modifies Swarm Skills — the multi-role (多角色团队) extension of the Skills standard, optionally with an executable SwarmFlow orchestration script. Use when building or refactoring a multi-agent team, generating workflow (工作流/编排) orchestration code, or upgrading a single-agent skill into a collaborating team. Do NOT use for ordinary single-agent skills — use create-skill instead.
Use when initializing or updating structured in-repository project-maintenance docs; exploring existing code; analyzing a full project or repository; documenting complete source symbol coverage, coverage maps, symbol audit maps, or health for every top-level class, top-level function, and class method; summarizing git history; using project-maintainer as maintenance-aware context during a bug fix, feature change, or refactor; or syncing docs after verified code changes.
进阶版日报生成器，支持多数据源采集、工作分析、趋势对比、周报月报聚合
当用户说「从这个链接/URL生成skill」「把这个网页/教程做成skill」「从这个视频提取步骤」时触发。先用 read_file 读取此 SKILL.md，再按步骤用 bash 调用 scripts/ 下的 Python 脚本完成：爬取网页或下载视频 → 下载图片/抽帧 → 生成标准 Skill Markdown 文件。
使用 gitcode-api 命令行工具访问 GitCode REST API。适用于需要查询仓库、Issue、Pull Request、文件内容、用户、组织、搜索结果，或需要获取 Issue 与 Pull Request 模版的场景。还可用于总结仓库最近 commit / PR / issue、责任人、模块、风险或对外接口影响。
| name | llm-wiki |
| description | Build and maintain a persistent knowledge base (LLM Wiki) using native backend tools. Supports ingesting PDFs, Markdown, and TXT files, and querying or linting the data. Use this whenever the user wants to add, retrieve, or manage their own local knowledge base and documents. |
You are the maintainer of a persistent local LLM Wiki. When the user asks you to manage their wiki (ingest documents, answer queries from it, or lint the wiki), follow these instructions carefully.
The LLM Wiki is based on a structured 3-layer architecture:
sources/): The raw files that are tracked in the wiki. The system relies on a deduplication manifest (manifest.json) so the same file data isn't processed twice.wiki/): The compiled knowledge. You maintain index.md, topic files, and a log.md where all structural changes are recorded.schema/): Configuration mapping (internal).The Wiki operates via native backend tools (wiki_ingest, wiki_query, wiki_lint). The default workspace is the absolute path to ./.llm_wiki within your root workspace. If the user specifies a directory for the wiki (like wiki_lib), you MUST determine the FULL ABSOLUTE PATH to that directory and pass it to the workspace parameter of the tools. This ensures the wiki is correctly created inside a .llm_wiki sub-folder at that exact location.
When a user provides a file (PDF, TXT, MD) or a directory of files to be ingested:
Call your wiki_ingest tool with the source path as source and the target directory as workspace (if provided).
source..llm_wiki/wiki/log.md, and securely add standard Markdown links inside .llm_wiki/wiki/index.md so that the new knowledge is linked from the root page.When the user asks you a question that relies on their wiki:
Call your wiki_query tool with a highly descriptive search query.
workspace path when calling the wiki_lint tool.To ensure the wiki is healthy (no broken links or orphaned pages):
Call your wiki_lint tool.
workspace path when calling the wiki_lint tool..md files in .llm_wiki/wiki/ (using standard file editing tools) to repair broken paths. Ensure all paths are relative.sources/. They are the raw truth. Only edit files in wiki/.index.md after an ingestion.