Agent skill

Diagram Generator

by zhaoxuya520 in zhaoxuya520/reverse-skill

Turns text, notes, code, schemas or tables into diagram source in Mermaid, Graphviz DOT, PlantUML or SVG, and renders files when you ask for an image or PDF.

MITAuto-check: warningsDevelopment

Install Diagram Generator

The automated check flagged lines worth reading first. See the safety section below.

skills CLI
$ npx skills add zhaoxuya520/reverse-skill --skill diagram-generator -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install zhaoxuya520/reverse-skill diagram-generator --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/zhaoxuya520/reverse-skill.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/diagram-generator .claude/skills/diagram-generator && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
diagram-generator
GitHub stars
41k
Used in
1 other repo
Token cost
~2.3k tokens
SKILL.md length
888 words
Files
6 (incl. scripts, references)
Skills in repo
19
Repo updated
First seen
Licence
MIT

At a glance

Turns text, notes, code, schemas or tables into diagram source in Mermaid, Graphviz DOT, PlantUML or SVG, and renders files when you ask for an image or PDF.

  • Works in 4 steps: NOW:确认当前任务是否命中本 skill 的适用范围 → NOW:读取 ../tool-index.md,校验工具可用性和实际路径 → NEXT:缺工具时调用 bootstrap,不要猜路径 → …
  • Drawing a flowchart or sequence diagram from a description
  • SKILL.md covers ACTION REQUIRED(读完后立刻执行), Purpose, Default workflow and Diagram language decision table, plus 8 more sections
  • Runs Python scripts from its folder; calls python and npm; reaches graphviz.org and plantuml.com

What it does

Editable, text-based diagrams are produced from messy or structured input: flowcharts, swimlanes, sequence, state, ER and class diagrams, C4-style architecture, dependency graphs, Gantt charts, mind maps, user journeys, org charts and similar. The agent works through a fixed sequence of identifying intent and audience, picking a diagram family, normalizing entities and relationships, writing concise source, validating it and returning it with a short note on assumptions.

A decision table picks the language. Mermaid is the default and covers flowcharts, sequence, state, ER, class, Gantt, mind map, journey and git graph diagrams, Graphviz DOT is preferred for dense dependency graphs, and PlantUML for UML-heavy work. Direct SVG is used when markup is more reliable. The agent is told not to over-ask and to label any assumptions it makes.

Files are rendered only when you want an image or PDF, using scripts/render_diagram.py, and a second script creates sample diagrams. A reference file lists diagram patterns, and the opening of the file points to a shared tool index for checking available tools and bootstrapping missing ones.

When your agent uses it

  • Drawing a flowchart or sequence diagram from a description
  • Visualizing a database schema as an ER diagram
  • Laying out a dense dependency graph
  • Rendering diagram source to an image or PDF file

Example prompts

  • “Draw a sequence diagram of the login flow described in these notes.”
  • “Turn this SQL schema into an ER diagram I can paste into Markdown.”
  • “Make a Gantt chart for the launch plan below and render it as a PNG.”

Requirements

  • Python, to run scripts/render_diagram.py for file output

Workflow steps

4 steps, taken from the first numbered list in SKILL.md.

  1. NOW:确认当前任务是否命中本 skill 的适用范围
  2. NOW:读取 ../tool-index.md,校验工具可用性和实际路径
  3. NEXT:缺工具时调用 bootstrap,不要猜路径
  4. ACT:进入"工作流"第一步并执行,不要停在确认状态

What it can do on your machine

Read from SKILL.md and the folder at commit cab634b. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 2 files in scripts/ (Python), which the agent can run.

    Shell commands in SKILL.md call:

    • python
    • npm

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Hosts in commands or code, which the agent is likely to contact:

    • graphviz.org
    • plantuml.com

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Diagram Generator loads about 2.3k tokens when it runs, and up to ~3.4k if it reads all its reference files. Until then it costs about 145 tokens; SKILL.md has 888 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~145
When it runs · the whole SKILL.md, loaded when a task matches
~2.3k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~3.4k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check: warnings

The automated check found patterns that need a careful read before installing.

  • WarningTells the agent its actions are pre-authorized / not to stop for confirmationSKILL.md:13
    4. `ACT`:进入"工作流"第一步并执行,不要停在确认状态

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from zhaoxuya520/reverse-skill at commit cab634b, republished under its MIT licence (© zhaoxuya520). 888 words, ~2,251 tokens.

Download SKILL.mdSave it as .claude/skills/diagram-generator/SKILL.md (or your agent's skills folder). This skill also uses 5 other files; get the full folder from GitHub.
name
diagram-generator
description
generate, refine, validate, and render diagrams from natural language, notes, code snippets, schemas, tables, or existing diagram source. use for flowcharts, swimlanes, sequence diagrams, state diagrams, er diagrams, class diagrams, architecture/c4-style diagrams, dependency graphs, gantt charts, mind maps, user journeys, sankey-style flows, org charts, network graphs, and other visual models. supports mermaid by default, graphviz dot for complex graph layout, plantuml for uml-heavy engineering diagrams, and svg output when direct markup is more reliable.

Diagram Generator

ACTION REQUIRED(读完后立刻执行)

  1. NOW:确认当前任务是否命中本 skill 的适用范围
  2. NOW:读取 ../tool-index.md,校验工具可用性和实际路径
  3. NEXT:缺工具时调用 bootstrap,不要猜路径
  4. ACT:进入"工作流"第一步并执行,不要停在确认状态

Purpose

Create clear, editable diagrams from messy or structured inputs. Prefer text-based diagram source first so the result can be reviewed, versioned, and refined. Render to files only when the user asks for an image/PDF or when a downloadable artifact would materially help.

Default workflow

  1. Identify the user's intent, audience, and source material.
  2. Choose the diagram family and language using the decision table below.
  3. Normalize entities, relationships, labels, states, branches, and time/order information before writing diagram code.
  4. Generate concise, readable diagram source.
  5. Validate the syntax mentally and, when creating files, run scripts/render_diagram.py.
  6. Return the diagram source plus a short note about assumptions. When files are generated, include links to the output files.

Do not over-ask for clarification. If the request is underspecified, make reasonable assumptions and label them briefly.

Diagram language decision table

Use Mermaid unless another language is clearly better.

User wantsPreferWhy
process flow, decision tree, simple swimlaneMermaid flowchartreadable and easy to paste into Markdown
sequence of system/user interactionsMermaid sequenceDiagram or PlantUML sequenceMermaid for docs; PlantUML for UML formality
lifecycle, state machine, transitionsMermaid stateDiagram-v2 or PlantUML statecompact transition syntax
database schema, entities, relationshipsMermaid erDiagramportable ER notation
class/interface/object modelMermaid classDiagram or PlantUML classMermaid for docs; PlantUML for detailed UML
project scheduleMermaid ganttconcise timeline syntax
hierarchy, ideas, notesMermaid mindmapgood default for idea maps
customer/product journeyMermaid journeybuilt-in journey notation
git historyMermaid gitGraphbuilt-in git notation
dependency graph, package graph, large networkGraphviz DOTbetter layout engines for dense graphs
architecture with layers, clusters, boundariesMermaid flowchart with subgraphs, Graphviz clusters, or PlantUML C4-stylechoose based on requested fidelity
weighted flow/sankey-like relationshipMermaid sankey-beta when supported, otherwise SVG or GraphvizMermaid support may vary by renderer
custom visual where source languages fit poorlySVGprecise control over layout and styling

Output policy

  • Always provide editable source unless the user explicitly asks only for an image.
  • Default to a single best diagram. Offer alternatives only when genuinely useful.
  • Prefer stable, simple syntax over fancy features that may not render in older Mermaid/PlantUML versions.
  • Use short labels. Split long text into notes outside the diagram when needed.
  • Avoid ambiguous node IDs. Use ASCII IDs and human-readable labels.
  • Preserve user terminology, but standardize capitalization within a diagram.
  • For technical diagrams, include boundaries such as client, service, database, queue, external API, and operator/user when they are implied.
  • For business-process diagrams, distinguish happy path, decision points, failures, retries, and manual steps when present.
  • For diagrams created from uncertain text, include an Assumptions section after the code.

Mermaid generation rules

Consult references/diagram-patterns.md for compact templates.

General Mermaid rules:

  • Start with the correct diagram directive, for example flowchart TD, sequenceDiagram, erDiagram, gantt, mindmap, or journey.
  • For flowcharts, use flowchart TD unless the user asks for left-to-right; use flowchart LR for architecture and pipelines.
  • Use subgraphs for swimlanes or architecture layers. Name subgraphs with readable labels.
  • Keep node IDs stable and ASCII-only, for example ingest_service[Ingest Service].
  • Quote labels that contain punctuation likely to confuse the parser.
  • Use decision diamonds for branching: decision{Condition?}.
  • Use consistent edge labels: -- yes -->, -- no -->, -. async .->, or == critical ==> only when meaningful.
  • In sequence diagrams, declare participants before messages. Use actor for humans and participant for systems.
  • Use alt/else/end, opt/end, loop/end, and par/and/end blocks for conditional, optional, repeated, and parallel flows.
Show full SKILL.md (315 more words)Show less

Graphviz DOT generation rules

Use Graphviz for large, dense, or layout-sensitive relationship diagrams.

  • Prefer digraph G for directed relationships and graph G for undirected networks.
  • Set layout-friendly graph attributes at the top: rankdir=LR, nodesep, ranksep, and splines=true when helpful.
  • Use subgraph cluster_name for boundaries and subsystems.
  • Use plain labels and restrained styling.
  • Use edge labels only when they add meaning.
  • For many nodes, group by domain with clusters and avoid crossing-heavy all-to-all edges.

PlantUML generation rules

Use PlantUML when the user asks for UML or needs formal UML notation.

  • Wrap diagrams with @startuml and @enduml.
  • Use actor, participant, database, queue, collections, or component stereotypes when useful.
  • Use package, rectangle, or node for architecture boundaries.
  • For class diagrams, include only important fields/methods unless the user asks for exhaustive detail.
  • For activity diagrams, use clear start/end markers and explicit branch labels.

SVG generation rules

Use SVG only when text diagram languages cannot express the requested visual reliably.

  • Keep SVG simple, accessible, and editable.
  • Include <title> and meaningful text labels.
  • Prefer rectangles, lines, arrows, and groups over complex paths.
  • Do not embed external fonts or remote images.

Rendering files

When the user asks for PNG/SVG/PDF, create a source file and run:

bash
python "<SKILL_ROOT>/diagram-generator/scripts/render_diagram.py" input.mmd --format svg --out output.svg
python "<SKILL_ROOT>/diagram-generator/scripts/render_diagram.py" input.dot --format png --out output.png
python "<SKILL_ROOT>/diagram-generator/scripts/render_diagram.py" input.puml --format svg --out output.svg

<SKILL_ROOT> 是本包 skills/ 目录的实际路径,AI 应自动检测。

The renderer is intentionally dependency-tolerant. It tries common local tools and reports actionable installation hints if a renderer is unavailable. Do not claim an image was rendered unless the script completed successfully and the output file exists.

Validation checklist

Before finalizing:

  • The diagram type matches the user's task.
  • The source is syntactically plausible for the chosen language.
  • Labels are short enough to fit.
  • Edges and message order reflect the input accurately.
  • Assumptions are called out when the input was incomplete.
  • For generated files, the output exists and opens or has nonzero size.

Common response template

Use this structure for most diagram answers:

markdown
下面是可编辑的 [language] 版本:

```[language]
[source]

Assumptions:

  • [only if needed]

Rendered file: [link] [only if generated]


For English user requests, respond in English. For Chinese user requests, respond in Chinese unless they ask otherwise.

---

## 按需自举(On-Demand Bootstrap)

### 自动化能力边界

| 工具 | 可自动安装 | 安装方式 | 说明 |
|------|-----------|---------|------|
| Mermaid CLI (mmdc) | ✓ | npm install -g @mermaid-js/mermaid-cli | 渲染 Mermaid 为 PNG/SVG |
| Graphviz (dot) | ✗ | 手动安装 | https://graphviz.org/download/ |
| PlantUML | ✗ | 需要 Java + plantuml.jar | https://plantuml.com/download |
| Python (render script) | ✓ | 已在 bootstrap 中 | `scripts/render_diagram.py` 依赖 |

### 说明

本 skill 主要输出文本格式的图表源码(Mermaid/DOT/PlantUML),不一定需要本地渲染工具。只有当用户明确要求生成 PNG/SVG/PDF 文件时才需要对应的渲染器。

如果渲染器不可用,`scripts/render_diagram.py` 会输出安装提示而不是报错。

---

## 路由上下文

**上游入口**: `skills/SKILL.md`(总控)、`routing.md`
**触发条件**: 用户说"画图"、"流程图"、"架构图"、"攻击路径图"、"时序图"、"Mermaid"、"Graphviz"、"PlantUML"
**下游出口**:
- 生成的图表可嵌入 `docs-generator/` 的报告中
- 攻击路径图可配合 `pentest-tools/` 的渗透报告

**同级关联模块**: `docs-generator/`(报告中嵌入图表)


## 任务完成自检(声称完成前 MUST 通过)

- [ ] 我是否执行了工作流中的每一步(而不是只阅读)?
- [ ] 我是否基于 `tool-index` 使用了真实工具路径?
- [ ] 我是否产出了可复现证据(命令/脚本/截图/报告)?
- [ ] 我是否完成并回写了 RULES 要求的 Checklist 项?

© zhaoxuya520, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 5 other files (scripts, references) in skills/diagram-generator of zhaoxuya520/reverse-skill.

  • SKILL.md
  • README.md
  • agents/openai.yaml
  • references/diagram-patterns.md
  • scripts/create_sample_diagrams.py
  • scripts/render_diagram.py

Open the folder on GitHubat commit cab634b

Used in 1 other repository

We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in zhaoxuya520/reverse-skill, which our catalogue first saw on October 7, 2026.

Compare with similar skills

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Architecture Diagramkonraddzbik/architecture-diagram-skill115—~5.7kAutomated safety check: PassMIT
Chatbot Mvp Distillationpdsuwwz/chatgpt-vue3-light-mvp579—~722Automated safety check: PassMIT
Chatbot Mvp Distillation Zhpdsuwwz/chatgpt-vue3-light-mvp579—~414Automated safety check: PassMIT
Markdown Mermaid WritingK-Dense-AI/scientific-agent-skills48k1 repos~4.2kAutomated safety check: NotesApache-2.0

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Works with

Questions about Diagram Generator

What does Diagram Generator do?

Turns text, notes, code, schemas or tables into diagram source in Mermaid, Graphviz DOT, PlantUML or SVG, and renders files when you ask for an image or PDF. Editable, text-based diagrams are produced from messy or structured input: flowcharts, swimlanes, sequence, state, ER and class diagrams, C4-style architecture, dependency graphs, Gantt charts, mind maps, user journeys, org charts and similar. The agent works through a fixed sequence of identifying intent and audience, picking a diagram family, normalizing entities and relationships, writing concise source, validating it and returning it with a short note on assumptions.

When should I use Diagram Generator?

Diagram Generator fits situations like: drawing a flowchart or sequence diagram from a description; visualizing a database schema as an ER diagram; laying out a dense dependency graph; rendering diagram source to an image or PDF file.

How do I install Diagram Generator in Claude Code?

Run `npx skills add zhaoxuya520/reverse-skill --skill diagram-generator -a claude-code`. Or copy the skill folder (skills/diagram-generator in zhaoxuya520/reverse-skill) into .claude/skills/diagram-generator in your project. Claude Code loads it when a task matches its description.

How do I install Diagram Generator in Codex?

Run `npx skills add zhaoxuya520/reverse-skill --skill diagram-generator -a codex`. Or copy the skill folder (skills/diagram-generator in zhaoxuya520/reverse-skill) into .agents/skills/diagram-generator in your project. Codex loads it when a task matches its description.

Can I use Diagram Generator in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add zhaoxuya520/reverse-skill --skill diagram-generator -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/diagram-generator, .gemini/skills/diagram-generator, .github/skills/diagram-generator and .opencode/skills/diagram-generator in your project.

What does Diagram Generator need to run?

Going by SKILL.md and its folder, Diagram Generator needs Python for the scripts in its folder and the command-line tools its instructions call (python and npm). Our summary lists: Python, to run scripts/render_diagram.py for file output.

Does Diagram Generator access the network?

SKILL.md names 2 domains. In commands or code: graphviz.org and plantuml.com; the agent is likely to contact these when it follows the instructions. This is read from the text; nothing was executed.

Is Diagram Generator safe to install?

Our automated static check of SKILL.md flagged 1 warning(s): tells the agent its actions are pre-authorized / not to stop for confirmation. Read the flagged lines before installing; the check is not a guarantee either way. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Diagram Generator use?

Diagram Generator is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Diagram Generator use?

About 2.3k tokens (SKILL.md is roughly 9k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 1.2k tokens, read only when the agent opens those files.

What are the alternatives to Diagram Generator?

Skills that share tags, products or a category with Diagram Generator: Pretty Mermaid Renderer (imxv/Pretty-mermaid-skills, 1.5k stars), Architecture Diagram (konraddzbik/architecture-diagram-skill, 115 stars), Chatbot Mvp Distillation (pdsuwwz/chatgpt-vue3-light-mvp, 579 stars) and Chatbot Mvp Distillation Zh (pdsuwwz/chatgpt-vue3-light-mvp, 579 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Diagram Generator?

zhaoxuya520 (a GitHub user) maintains it in zhaoxuya520/reverse-skill, which has 40,590 GitHub stars. The repository holds 19 skills in this directory. The repository was last updated on September 22, 2026.

Source: zhaoxuya520/reverse-skill on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.