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 znlgis/opengis-skills --skill design-drawing-svg-mdgit clone --depth 1 https://github.com/znlgis/opengis-skillsWrote 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/znlgis/opengis-skills/design-drawing-svg-md)<a href="https://agentmods.dev/skills/znlgis/opengis-skills/design-drawing-svg-md"><img src="https://agentmods.dev/badge/skills/znlgis/opengis-skills/design-drawing-svg-md/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/znlgis/opengis-skills/design-drawing-svg-md"><img src="https://agentmods.dev/badge/skills/znlgis/opengis-skills/design-drawing-svg-md.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00061 | $0.05711 |
| Opus 5 | $0.00030 | $0.02856 |
| Sonnet 5 | $0.00012 | $0.01142 |
| Haiku 4.5 | $0.00006 | $0.00571 |
Grade A, and why
design-drawing-svg-md 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 7d 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.
How it starts
The opening of the file, as written. The whole thing — 260 lines — stays where its author put it; the contents beside it link to each section on GitHub.
技能定位: 设计图 SVG+MD 双载体记录方法论——把"会画不懂"的矢量 PDF 工程图,转化为大模型能准确理解、指认与复刻的交付物。
方法来源: 一套钢结构施工图数字化执行方案的固化与泛化;文中数字为示例值或多图实测值,执行时以实际图纸实测为准。
适用输入: 矢量线画 + 无文字层的 PDF 工程图(彩色分层或单色均可)。
脚本资产: 本仓库
scripts/目录附带可直接复跑的泛化脚本——共用库 scripts/common.py、入口配置 scripts/config.example.json、十一阶段脚本01_extract.py…09_verify_deliverables.py(执行顺序与门禁见 reference/pipeline.md)。
概述
MD 是"大模型阅读主线",SVG 是"高精度几何档案 + 按需切片源",两者用统一 ID 体系互联,用校验闭环保证一致。
何时使用
- 需要让大模型/Agent 理解一份工程图纸(几何、尺寸、语义、工艺、管理信息)
- 源图为 PDF,且是矢量线画、无文字层(尺寸数字只是 glyph 轮廓路径,直接渲染"会画不会读")
- 需要对图纸做问答、复刻重绘、改图、核量、生成 BOM 等下游任务
- 图纸会换版(R00→R01),需要可 diff、可追溯的数字化档案
何时不使用
- 源图已有文字层且无需精确几何 → 直接 PDF 文本提取即可
- 只需一张渲染图给人看,无下游智能任务 → 不必建双载体
- 栅格扫描件 → 本技能不覆盖矢量化(OCR/矢量化另案处理)
适用对象
A0 钢结构施工图(无文字层的矢量线画)为典型用例;任何"矢量线画 + 无文字层"的 PDF 工程图均可套用。
核心概念
双载体定位
原图 PDF(矢量线画 / 无文字层 / 彩色分层)
│ 提取(fitz.get_drawings + 分层:OCG 语义优先 + 颜色兜底)
▼
MD(魂·阅读主线) ◄── ID 互联(view/dim/balloon/prim-id + crosswalk) ──► SVG(骨·几何档案)
语义/参数/值/工艺/BOM 原生坐标/图层/视图分组/文本
│ │
└──────── 校验闭环(MD 重绘 ⇄ SVG 叠合 ⇄ 原图)──────────────────────┘
└──────── 消费(MD 全文分块 + SVG 按视图切片)────────────────────────┘
三条设计原则
- 单一事实源:每类信息只在一处为"真",另一处只引用不复制(分工矩阵见下),避免双份漂移。
- ID 互联而非坐标复制:MD 保留局部 mm 参数坐标(可编辑),SVG 保留页面 pt 原生坐标(精确),换算关系写入 crosswalk。
- token 可行:MB 级 SVG 不整份进上下文;MD 为索引,SVG 按
data-view切片按需取。
为什么不只用单一载体
| 载体 | 优势 | 短板 |
|---|---|---|
| 仅 SVG | 像素级可复刻 | 对模型是坐标流——"会画不懂"(无文字层时尺寸数字只是轮廓路径) |
| 仅 MD | 结构语义可读、可编辑 | "看懂画不准"(细节图元易被省略、无法精确指认) |
理解准确性的四个分量
大模型"准确理解" = 几何精度 × 语义完整 × 可指认 × token 可行,缺一不可:
| 分量 | 含义 | 落点 |
|---|---|---|
| 几何精度 | 每条线的位置/类型/参数可复现 | SVG 原生坐标 + MD 参数图元互校 |
| 语义完整 | 每根线"是什么"、每个视图"看的是什么"、工艺与管理要求 | MD 语义层 + SVG data-* 属性 |
| 可指认 | 文档里每句话能定位到原图确切位置 | ID + crosswalk + 布局表 |
| token 可行 | 装得进上下文 | MD 分块读、SVG 按视图切片读 |
What ships with it
17 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.
- reference/md-spec.md 8.1 KB
- reference/pipeline.md 19 KB
- reference/svg-spec.md 9.4 KB
- scripts/01_extract.py 8.2 KB runs code
- scripts/02_cluster_views.py 17 KB runs code
- scripts/03_render_regions.py 21 KB runs code
- scripts/03b_text_recover.py 23 KB runs code
- scripts/03c_glyph_solve.py 35 KB runs code
- scripts/03d_vision_read.py 34 KB runs code
- scripts/04_build_md.py 30 KB runs code
- scripts/05_crosswalk.py 28 KB runs code
- scripts/06_enhance_svg.py 16 KB runs code
- scripts/07_validate.py 14 KB runs code
- scripts/08_qa.py 18 KB runs code
- scripts/09_verify_deliverables.py 91 KB runs code
- scripts/common.py 41 KB runs code
- scripts/config.example.json 1.6 KB
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.
- 7d ago Changed · +35 lines 7cdc967be5d6
- 9d ago First seen · 225 lines · 61 tokens per session scan A df7805d80d5b
design-drawing-svg-md is a skill published in the GitHub repository znlgis/opengis-skills (61 stars, last pushed yesterday), licensed MIT. It adds 61 tokens to every session and 5,711 once invoked, about $0.0003 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 2026-09-03.
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