text-to-cad is a collection of agent workflows for creating, examining, finding, preparing, and transferring CAD, engineering, manufacturing, and robot-description files. It is for agents working with mechanical design, fabrication, simulation, and robotics projects. Catalogue skills, instructions, and a plugin implement these workflows.
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 earthtojake/text-to-cad --skill sdfgit clone --depth 1 https://github.com/earthtojake/text-to-cadWrote 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/earthtojake/text-to-cad/sdf)<a href="https://agentmods.dev/skills/earthtojake/text-to-cad/sdf"><img src="https://agentmods.dev/badge/skills/earthtojake/text-to-cad/sdf/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/earthtojake/text-to-cad/sdf"><img src="https://agentmods.dev/badge/skills/earthtojake/text-to-cad/sdf.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk pass
- 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 | $0.00088 | $0.01873 |
| Opus 5 | $0.00044 | $0.00937 |
| Sonnet 5 | $0.00018 | $0.00375 |
| Haiku 4.5 | $0.00009 | $0.00187 |
Grade A, and why
sdf 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 5d 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 — 146 lines — stays where its author put it; the contents beside it link to each section on GitHub.
SDF
Provenance: maintained in earthtojake/text-to-cad. Use the installed local skill files as the runtime source of truth; the repository link is only for provenance and release review.
Use this skill when the deliverable is an SDFormat document. SDFormat describes simulator and world behavior: models, worlds, frames, poses, links, joints, inertials, visuals, collisions, sensors, lights, physics, plugins, includes, and simulator metadata.
This skill is for SDFormat, not signed-distance-field geometry.
The .sdf file is the source of truth: author and edit the XML directly. There is no gen_sdf() contract.
Setup
This skill's commands are thin entrypoints over the cadgen distribution, which
carries the Python build runtime and the JavaScript it executes. Install it once:
python -m pip install -r requirements.txt
Rendering additionally needs a browser, which pip cannot supply:
python -m playwright install chromium
Core rules
- Author
.sdfXML directly and validate every created or modified file withcadgen sdf validatebefore reporting completion. - Identify the target consumer before editing: Gazebo/libsdformat version, another simulator, visualization-only tooling, model package, or world handoff.
- Decide document kind: model-level SDF, world-level SDF, or model-in-world. Prefer model-level SDF for reusable robot/object exports.
- Use SI units unless the target explicitly requires otherwise: meters, kilograms, seconds, radians.
- Prefer
version="1.12"for new outputs unless the target consumer constrains the version. - Establish the design ledger before writing poses, frames, joint axes, mesh scales, inertials, sensors, or plugins, and keep it as a comment block at the top of the
.sdf. Usereferences/design-ledger.mdandreferences/llm-guardrails.md. - Write
relative_to/expressed_inexplicitly on every nontrivial pose and axis. Implicit frame defaults are the top SDF failure mode. Seereferences/frame-semantics.md. - Do not infer spatial transforms from visual impression alone. Derive poses, axes, scale, mass, inertia, and frame names from upstream source data, drawings, simulator documentation, measured values, or explicit assumptions. Never freehand computed numbers — use formulas or a throwaway helper script (inertia tensors, unit conversions).
- When the robot already has a URDF, derive the SDF from it instead of re-authoring geometry; see
references/interoperability.md. - Regenerate upstream geometry, mesh, robot-description, render, topology, or package assets with their owning workflows before editing SDF that references them.
- After authoring, run available checks: bundled validation, optional
gz sdf --check, simulator load, joint motion, and plugin/sensor startup. - Report assumptions, skipped checks, unresolved resource paths, and target-specific compatibility risks.
What ships with it
11 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.
- agents/openai.yaml 273 B
- LICENSE 1.0 KB
- references/design-ledger.md 4.1 KB
- references/examples.md 4.3 KB
- references/frame-semantics.md 3.6 KB
- references/interoperability.md 3.5 KB
- references/llm-guardrails.md 4.4 KB
- references/sdf-workflow.md 4.1 KB
- references/smoke-tests.md 3.0 KB
- references/validation.md 7.1 KB
- requirements.txt 24 B
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.
- 5d ago Changed · +18 lines 2ba9eaed38b3
- 10d ago First seen · 128 lines · 88 tokens per session scan A 51f3c1b4de5a
sdf is a skill published in the GitHub repository earthtojake/text-to-cad (15,283 stars, last pushed today), licensed MIT. It adds 88 tokens to every session and 1,873 once invoked, about $0.0004 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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