cad-sdf-skill

cad-sdf-skill is a skill for OpenCode from darellchua2/opencode-config-template. It costs 40 tokens per session (1,404 once invoked), scanned A, original, Apache-2.0.

A guide for generating and validating SDFormat files, which describe robot models and simulated worlds for Gazebo.

In plain words
What is it for?
Use it to create reusable robot or object models, simulation worlds, and Python source that generates SDFormat.
Why use it?
It helps produce simulator documents with correct models, joints, sensors, physics, and related settings.

Skill for OpenCode

Written for OpenCode: installed under .opencode/. Also seen: mentions OpenCode.

Install

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.

agentmods
npx agentmods add skills/darellchua2/opencode-config-template/cad-sdf-skill
Any agent
npx skills add darellchua2/opencode-config-template --skill cad-sdf-skill
Clone the repo
git clone --depth 1 https://github.com/darellchua2/opencode-config-template

Made for: OpenCode.

Wrote 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.

agentmods badge for cad-sdf-skill

README.md
[![agentmods](https://agentmods.dev/badge/skills/darellchua2/opencode-config-template/cad-sdf-skill.svg)](https://agentmods.dev/skills/darellchua2/opencode-config-template/cad-sdf-skill)
Your own site
<a href="https://agentmods.dev/skills/darellchua2/opencode-config-template/cad-sdf-skill"><img src="https://agentmods.dev/badge/skills/darellchua2/opencode-config-template/cad-sdf-skill.svg" alt="Measured on agentmods" height="20"></a>
Per session 40 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,404 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00040 $0.01404
Opus 5 $0.00020 $0.00702
Sonnet 5 $0.00008 $0.00281
Haiku 4.5 $0.00004 $0.00140

Measured 3d ago against content hash a5352263ded1, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-06, from the pricing page.

Security

Grade A, and why

cad-sdf-skill 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 3d ago.

The scan reads SKILL.md. This mod also ships 10 executable files (scripts/packages/cadpy_metadata/src/cadpy_metadata/__init__.py, scripts/packages/cadpy_metadata/src/cadpy_metadata/generator.py, scripts/sdf/__init__.py, …), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

opencode_app/.opencode/skills/cad-sdf-skill/SKILL.md · 111 lines

How it starts

The opening of the file, as written. The whole thing — 111 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 or a Python gen_sdf() source. 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.

Core rules

  1. Treat the Python file defining gen_sdf() as source of truth. Treat configured .sdf files as generated artifacts unless the user explicitly asks for direct XML editing.
  2. Identify the target consumer before editing: Gazebo/libsdformat version, another simulator, visualization-only tooling, model package, or world handoff.
  3. Decide document kind: model-level SDF, world-level SDF, or model-in-world. Prefer model-level SDF for reusable robot/object exports.
  4. Use SI units unless the target explicitly requires otherwise: meters, kilograms, seconds, radians.
  5. Prefer version="1.12" for new outputs unless the target consumer constrains the version.
  6. Establish the design ledger before writing poses, frames, joint axes, mesh scales, inertials, sensors, or plugins. Use references/design-ledger.md and references/llm-guardrails.md.
  7. 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.
  8. Prefer helper functions and named constants over large XML string literals. Hidden numbers are a common SDF failure mode.
  9. Generate only explicit targets with scripts/sdf or the repository's existing SDF launcher. Do not run directory-wide generation.
  10. Regenerate upstream geometry, mesh, robot-description, render, topology, or package assets with their owning workflows before regenerating SDF that references them.
  11. After generation, run available checks: bundled validation, optional gz sdf --check, simulator load, joint motion, and plugin/sensor startup.
  12. Report assumptions, skipped checks, unresolved resource paths, and target-specific compatibility risks.

Read the full file on GitHub · 111 lines

Changes

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.

  1. 3d ago First seen · 111 lines · 40 tokens per session scan A a5352263ded1

Subscribe to this mod's changes

cad-sdf-skill is a skill published in the GitHub repository darellchua2/opencode-config-template (6 stars, last pushed today), licensed Apache-2.0. It adds 40 tokens to every session and 1,404 once invoked, about $0.0002 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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