Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add TatsukiMeng/ai-native-engineering --skill excalidraw-normalizergit clone --depth 1 https://github.com/TatsukiMeng/ai-native-engineeringWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/tatsukimeng/ai-native-engineering/excalidraw-normalizer)<a href="https://agentmods.dev/skills/tatsukimeng/ai-native-engineering/excalidraw-normalizer"><img src="https://agentmods.dev/badge/skills/tatsukimeng/ai-native-engineering/excalidraw-normalizer/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/tatsukimeng/ai-native-engineering/excalidraw-normalizer"><img src="https://agentmods.dev/badge/skills/tatsukimeng/ai-native-engineering/excalidraw-normalizer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00090 | $0.00592 |
| Opus 5 | $0.00045 | $0.00296 |
| Sonnet 5 | $0.00018 | $0.00118 |
| Haiku 4.5 | $0.00009 | $0.00059 |
Grade A, and why
excalidraw-normalizer scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
Excalidraw 规范化
概览
用这个 skill 把 Excalidraw 场景从“看起来差不多”推进到“可维护、可发布”。
默认目标：
- 节点标签跟随节点移动
- 节点移动时连接关系不脱落
- 几何布局符合简单、可复用的模式
- 透明导出在夜间模式下可用
- 仅靠 JSON 不足以把连线排好时，交给编辑器做一次规范化重算
工作流
- 先处理结构，不先抠视觉修饰。
- 先把标签和连接关系绑好，再优化布局。
- 用简单几何模型重排，例如 star、ring、grid、lane、hierarchy。
- 如果连线质量依赖锚点选择，手写的 connector
points只能视为临时结果。 - 当线段还需要编辑器的重算能力时，做一次 Excalidraw editor pass。
- 布局稳定后，再用仓库内渲染器导出。
规则
- 节点内部文字优先使用
containerId。 - 连接优先使用带
startBinding和endBinding的arrow。 - 保持
boundElements与连接图形同步。 - 优先拆成多个小图，不要堆成一张过载大图。
- 文档资产默认导出透明背景。
- 透明导出时避免深色细线，优先更亮的蓝、紫、青，并适当加粗。
- 如果拖动节点后图会散，就不能把它当成完成品。
参考
- 需要完整检查清单和布局模式时，读 references/normalization.md。
- 图的结构已经对了，但连线路径还是不好看时，读 references/editor-pass.md。
- 仓库内渲染器在 docs/scripts/excalidraw/render_excalidraw.py，命令入口在
docs/package.json的render:diagram:setup和render:diagram。
What ships with it
3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 9d ago First seen · 44 lines · 90 tokens per session scan A 0d7588b9e40b
excalidraw-normalizer is a skill published in the GitHub repository TatsukiMeng/ai-native-engineering (58 stars, last pushed 4mo ago), licensed MIT. It adds 90 tokens to every session and 592 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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