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 agentmods add skills/darellchua2/opencode-config-template/cad-urdf-skillnpx skills add darellchua2/opencode-config-template --skill cad-urdf-skillgit clone --depth 1 https://github.com/darellchua2/opencode-config-templateWrote 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/darellchua2/opencode-config-template/cad-urdf-skill)<a href="https://agentmods.dev/skills/darellchua2/opencode-config-template/cad-urdf-skill"><img src="https://agentmods.dev/badge/skills/darellchua2/opencode-config-template/cad-urdf-skill.svg" alt="Measured on agentmods" 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 | $0.00056 | $0.01162 |
| Opus 5 | $0.00028 | $0.00581 |
| Sonnet 5 | $0.00011 | $0.00232 |
| Haiku 4.5 | $0.00006 | $0.00116 |
Grade A, and why
cad-urdf-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 2d 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 — 73 lines — stays where its author put it; the contents beside it link to each section on GitHub.
URDF
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 for URDF robot-description outputs. Treat URDF work as constrained kinematic modeling, not just XML writing. The main correctness risks are frame placement, joint-axis semantics, unit consistency, mesh scale, inertial data, and generated-artifact drift.
Core Rules
- Treat the Python source that defines
gen_urdf()as the source of truth. Treat configured.urdffiles as generated artifacts. - Generate only explicit URDF targets. Do not regenerate unrelated CAD, mesh, render, SRDF, SDF, or simulator artifacts from this skill.
- The
scripts/urdfgenerator validates generated URDFs by default. Do not use or document a separatevalidatecommand. - Before writing or changing URDF XML, establish the robot's frame, joint, geometry, unit, and assumption ledger. See
references/design-ledger.md. - Use URDF frame semantics exactly. Joint origins, link frames, joint axes, and visual/collision/inertial origins use different reference frames. See
references/frame-semantics.md. - Do not infer spatial transforms, mesh units, handedness, axes, or joint signs from vague prose. Use CAD transforms, dimensioned drawings, measured values, existing source data, or explicit documented assumptions.
- Prefer simple, auditable generator code over clever XML construction. Keep constants named by physical meaning, not by arbitrary numbers.
- For physical links, model
inertial,visual, andcollisionseparately when the target consumer needs them. Frame-only links may intentionally omit mass and geometry.
CAD Viewer Handoff
After completing URDF work that creates or modifies a .urdf, you must ALWAYS hand the explicit file path to the cad-viewer-skill (load via skill tool) when that skill is installed. the cad-viewer-skill (load via skill tool) must start CAD Viewer if it is not already running and return link(s) to the relevant created or updated file(s); if the cad-viewer-skill (load via skill tool) is unavailable or startup fails, report that instead of silently omitting the handoff.
What ships with it
16 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.
- LICENSE 1.0 KB
- references/design-ledger.md 4.9 KB
- references/frame-semantics.md 3.5 KB
- references/gen-urdf.md 2.4 KB
- references/generator-contract.md 4.6 KB
- references/urdf-workflow.md 7.0 KB
- references/validation.md 6.1 KB
- requirements.txt 45 B
- scripts/packages/cadpy_metadata/pyproject.toml 407 B
- scripts/packages/cadpy_metadata/src/cadpy_metadata/__init__.py 416 B runs code
- scripts/packages/cadpy_metadata/src/cadpy_metadata/generator.py 7.9 KB runs code
- scripts/packages/cadpy_metadata/src/cadpy_metadata/py.typed 1 B
- scripts/urdf/__init__.py 46 B runs code
- scripts/urdf/__main__.py 363 B runs code
- scripts/urdf/cli.py 9.6 KB runs code
- scripts/urdf/source.py 24 KB runs code
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.
- 2d ago First seen · 73 lines · 56 tokens per session scan A cf2fbb67ba42
cad-urdf-skill is a skill published in the GitHub repository darellchua2/opencode-config-template (6 stars, last pushed 5d ago), licensed Apache-2.0. It adds 56 tokens to every session and 1,162 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.
Other skills, from other repositories
integrated-browser
Use this when working on the VS Code integrated browser ("browserView") to understand its architecture and mental model. Covers the embedded Chromium browser, its editor tab, navigation, overlay/layout, sessions, and agent browser tools under src/vs/platform/browserView and src/vs/workbench/contrib/browserView.
gke-compute-classes
Configures, optimizes, and troubleshoots GKE ComputeClasses. Use when configuring Spot VMs with on-demand fallback, targeting specific accelerators (GPUs/TPUs) or machine families, restricting ComputeClass access, or debugging pending pods related to node pool auto-creation. Do not use for cluster-level Node Auto…
jetson-diagnostic
Read-only Jetson health snapshot for identity, memory, GPU, thermal, power, storage, services, and top processes.
offensive-z-wave
Z-Wave attack methodology — sniffing with Z-Force / EZ-Wave / RTL-SDR + ZniffMobile, S0 (legacy) network-key derivation flaw and key reuse, S2 (modern) ECDH commissioning analysis, replay/injection on unauthenticated nodes, default-key brute-force on test deployments, and home-automation hub pivots. Use when targeting…
project-snmp-profiles-authoring
Use when editing Netdata SNMP profile YAMLs, topology SNMP profiles, ddsnmp profile parsing, or profile-format documentation. Requires checking source MIB field accessibility, especially MAX-ACCESS not-accessible INDEX objects, before adding or changing profile symbols.
hyperpod-version-checker
Check and compare software component versions on SageMaker HyperPod cluster nodes - NVIDIA drivers, CUDA toolkit, cuDNN, NCCL, EFA, AWS OFI NCCL, GDRCopy, MPI, Neuron SDK (Trainium/Inferentia), Python, and PyTorch. Use when checking component versions, verifying CUDA/driver compatibility, detecting version mismatches…