drawio-skill: Agent skill that turns natural language, code, Terraform/K8s, SQL, OpenAPI, AsyncAPI, Protobuf and GraphQL

by Agents365-ai · MCP Server · ★ 10.6k

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

How to install drawio-skill

git clone https://github.com/Agents365-ai/drawio-skill.git ~/.claude/skills/drawio-skill
git clone https://github.com/Agents365-ai/drawio-skill.git .claude/skills/drawio-skill

Taken from the project's README on GitHub. Check the security audit before running it.

Security audit verdict: SAFE · quality 71/100

Flagged: sudo usage. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →

The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.

agent-skillsarchitecturearchitecture-diagramasyncapibpmnc4-modelclaude-codediagramdiagrams-as-codedrawio

Quick Facts

Stars10,621
Forks729
LanguagePython
CategoryMCP Server
LicenseMIT
Quality Score71/100
Last Updated2026-11-06
Created2026-03-03
Platformsclaude-code, k8s, mcp, python
Est. Tokens~17k

About drawio-skill

drawio-skill — From Text to Professional Diagrams 中文文档 | Online Docs What it does Generates XML files from natural language descriptions Exports diagrams to PNG, SVG, PDF, or JPG using the native draw.io desktop CLI 6 diagram type presets: ERD, UML Class, Sequence, Architecture, ML/Deep Learning, Flowchart — with preset shapes, styles, and layout conventions Animated connectors () for data-flow...

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How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. It is a first-layer scan, not a manual audit — we say so rather than overstate it.

The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.

Sources & who's responsible:

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