mermaid-diagrams

作者: langchain-ai

在生成的Wiki頁面中嵌入Mermaid圖表。每當記錄執行或請求流程、呼叫序列、狀態機或生命週期、資料模型等時使用。

npx skills add https://github.com/langchain-ai/openwiki --skill mermaid-diagrams

Mermaid Diagrams In Generated Wiki Pages

Diagrams are part of high-quality wiki generation, not decoration. Where a flow, lifecycle, or data model is easier to grasp visually, embed a Mermaid diagram in a fenced ```mermaid block on the most relevant page.

Choosing a diagram type

  • sequenceDiagram for runtime and request flows across components (auth flows, request lifecycles, agent tool loops).
  • stateDiagram-v2 for lifecycles and state machines (job states, connection states, run phases).
  • erDiagram for the data model: entities and their relationships.
  • flowchart TD for branching control flow and decision logic.

Discipline

  • Ground every diagram in inspected source. Do not invent participants, states, entities, or relationships the code does not support.
  • Cover the high-value cases: add a diagram wherever a page documents a request or runtime flow, a call sequence, a lifecycle or state machine, or a data model. A repository wiki usually has several such diagrams, not one overall. Skip pages that are navigation, reference tables, or pure configuration.
  • Still prefer a few strong diagrams over decorating every page: one accurate diagram on the page that needs it beats a diagram forced onto every page.
  • Give each diagram a one-line caption directly below it stating what it shows.
  • OpenWiki validates every mermaid fence after your run and converts fences that fail to parse into plain text fences. A degraded diagram is a quality failure; follow the syntax rules below so it does not happen.

Syntax safety

These rules prevent the most common render breakages. When in doubt, rephrase the label.

  • Never place semicolons or pipes inside node, message, or edge labels.
  • Never place unescaped angle brackets in labels; write "returns Promise of User" instead of "returns Promise".
  • In flowchart, wrap any label containing parentheses, brackets, or other punctuation in double quotes: A["calls foo(bar)"].
  • In flowchart, never use the bare word end as a node id, and never start a node id with o or x followed by a dash (both are edge-marker syntax); rename the node.
  • In sequenceDiagram, participant names with spaces or punctuation need an alias: participant AS as Auth Service.
  • Never use a Mermaid reserved word as a participant name, alias, or node id: note, end, loop, alt, opt, par, and, else, activate, deactivate, class, state, click, link. For example a notification participant must be Notifier, not Note (which collides with the note keyword).
  • In erDiagram, entity and attribute names must be single identifier-like tokens; put human phrasing in the relationship label.
  • Keep labels short. Move explanation into the surrounding prose or the caption, not the diagram.

Update runs

  • A wrong diagram is a stale claim, not existing structure to preserve. If a source change makes a diagram inaccurate, update the diagram in the same edit as the surrounding prose.
  • Do not rewrite a diagram that is still accurate. Regenerating unchanged diagrams creates diff noise.
  • If a page contains a text fence preceded by an HTML comment starting with "openwiki: mermaid parse failed", that is a diagram a previous run degraded. Fix the syntax using the parser error in the comment, restore the ```mermaid fence, and delete the comment.

來自 langchain-ai 的更多技能

deepagents-thread-inspector
langchain-ai
檢查並解釋本地 Deep Agents Code SQLite 工作階段儲存庫中的對話。當 LangSmith 追蹤工具不可用時作為備用方案,用於…
deepagents-python-quickstart
langchain-ai
按照官方快速入門,在 Python 中搭建一個最小的本地 Deep Agent,使用提供者原生的網路搜尋而非 Tavily。當使用者想要……時使用。
deepagents-typescript-quickstart
langchain-ai
按照官方快速入門指南,以 TypeScript 搭建一個最小的本地 Deep Agent,使用供應商原生的網路搜尋而非 Tavily。當使用者……時使用
eval-engineering
langchain-ai
反覆檢查 agent 儲存庫與使用者提供的可選追蹤資料,訪談使用者,並逐一建立、執行及稽核 Harbor evals。用於……
LangChain RAG Pipeline
langchain-ai
在構建任何檢索增強生成(RAG)系統時,請調用此技能。涵蓋文檔加載器、遞迴字符文本分割器、嵌入(OpenAI)等。
LangChain Structured Output & HITL
langchain-ai
langchain-structured-output-&-hitl — 一個可安裝的 AI 代理技能,由 langchain-ai/langchain-skills 發布。
LangSmith Datasets
langchain-ai
當從追蹤建立評估資料集,或將資料集上傳至 LangSmith,或查詢資料集時,請調用此技能。涵蓋資料集類型(final_response、…)
langsmith-evaluator
langchain-ai
在為 LangSmith 建立評估管道時,請調用此技能。涵蓋三個核心組件:(1) 建立評估器 - LLM 作為評審、自訂程式碼;(2)…