dart: Skill for Claude Code

.agents/skills/dart-io/SKILL.md

dart-io is a skill for Claude Code, Codex from dartsim/dart. It costs 24 tokens per session (383 once invoked), scanned A, original, BSD-2-Clause.

A C++ guide for loading robot model files in URDF, SDF, and MJCF formats. These files describe a robot's parts, joints, and physical structure.

In plain words
What is it for?
Use it to parse robot descriptions and load skeletons for robotics or simulation software.
Why use it?
It avoids writing separate loading logic for each supported robot-model format and helps resolve referenced robot packages.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: reads .claude/ paths; installed under .agents/ (shared by several agents); mentions AGENTS.md.

This is dartsim/dart's own configuration. It tells Claude Code and Codex how to work on dart itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything dart configures →

About the project

DART is an open-source C++23 physics engine that simulates the movement and interactions of articulated rigid-body systems for robotics, animation, and machine learning. Researchers and developers use it for kinematics, dynamics, collision handling, constraints, and loading robot models, with C++ and Python interfaces. The catalogue add-ons support workflows built around this engine.

dartsim/dart · 1,202 stars · on GitHub · dart.readthedocs.io

Reuse

Borrowing it

Nothing to install: this file belongs to dartsim/dart. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/dartsim/dart/main/.agents/skills/dart-io/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/dartsim/dart

Made for: Claude Code, Codex.

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 dart-io

README.md
[![agentmods](https://agentmods.dev/badge/skills/dartsim/dart/dart-io.svg)](https://agentmods.dev/skills/dartsim/dart/dart-io)
Your own site
<a href="https://agentmods.dev/skills/dartsim/dart/dart-io"><img src="https://agentmods.dev/badge/skills/dartsim/dart/dart-io.svg" alt="Measured on agentmods" height="20"></a>
Per session 24 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 383 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector warn 7 Sept 2026
SkillSpector: 1 finding, up to medium

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

  • medium Agent Snooping · line 7
    Skill enumerates or reads other installed skills. Access to other skills' SKILL.md files or the skills directory reveals prompt instructions, capabilities, and secrets that should be invisible to peer skills.
    Fix: Remove all code or instructions that list or read other skills' files or directories. Skills should operate independently; cross-skill access is a privilege escalation.
How audits are shown
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 $0.00024 $0.00383
Opus 5 $0.00012 $0.00192
Sonnet 5 $0.00005 $0.00077
Haiku 4.5 $0.00002 $0.00038

Measured 4d ago against content hash 63f9fe78862c, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-07, from the pricing page.

Security

Grade A, and why

dart-io 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 4d 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.

.agents/skills/dart-io/SKILL.md · 54 lines

What it actually says

DART Model Loading (dart::io)

Load this skill when working with robot model files or parsers.

When correctness depends on the loaded model's 3D structure or behavior, also load dart-verify-sim for a text oracle plus claim-tied visual corroboration.

Quick Start

#include <dart/io/read.hpp>

// Format auto-detection
auto skel = dart::io::readSkeleton("dart://sample/urdf/KR5/KR5 sixx R650.urdf");

Full Documentation

For complete I/O guide: docs/onboarding/io-parsing.md

For module-specific details: dart/io/AGENTS.md

Supported Formats

docs/onboarding/io-parsing.md owns the format list (URDF, SDF, MJCF, and opt-in OpenUSD behind DART_BUILD_IO_USD=ON).

Common Patterns

// URDF with package resolution
dart::io::ReadOptions options;
options.addPackageDirectory("my_robot", "/path/to/my_robot");
auto skel = dart::io::readSkeleton("package://my_robot/urdf/robot.urdf", options);

// Force specific format
options.format = dart::io::ModelFormat::Sdf;

Key Files

  • API: dart/io/read.hpp
  • Tests: tests/unit/io/test_read.cpp
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. 4d ago Changed · -4 lines 63f9fe78862c
  2. 6d ago First seen · 58 lines · 24 tokens per session scan A c20580431926

Subscribe to this mod's changes

dart-io is a skill published in the GitHub repository dartsim/dart (1,202 stars, last pushed yesterday), licensed BSD-2-Clause. It adds 24 tokens to every session and 383 once invoked, about $0.0001 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 2026-09-01.

Related

Other skills, from other repositories

evaluating-cosmos-policy

Evaluates NVIDIA Cosmos Policy on LIBERO and RoboCasa simulation environments. Use when setting up cosmos-policy for robot manipulation evaluation, running headless GPU evaluations with EGL rendering, or profiling inference latency on cluster or local GPU machines.

Orchestra-Research/AI-Research-SKILLs · 51 tokens

fine-tuning-serving-openpi

Fine-tune and serve Physical Intelligence OpenPI models (pi0, pi0-fast, pi0.5) using JAX or PyTorch backends for robot policy inference across ALOHA, DROID, and LIBERO environments. Use when adapting pi0 models to custom datasets, converting JAX checkpoints to PyTorch, running policy inference servers, or debugging…

Orchestra-Research/AI-Research-SKILLs · 87 tokens

fine-tuning-openvla-oft

Fine-tunes and evaluates OpenVLA-OFT and OpenVLA-OFT+ policies for robot action generation with continuous action heads, LoRA adaptation, and FiLM conditioning on LIBERO simulation and ALOHA real-world setups. Use when reproducing OpenVLA-OFT paper results, training custom VLA action heads (L1 or diffusion), deploying…

Orchestra-Research/AI-Research-SKILLs · 103 tokens

geometry

Pure-math 3D geometry toolbox — back-project masks and depth to point clouds, DBSCAN-filter noise, fit oriented bounding boxes, derive top-down/front grasp poses, and reconstruct collision worlds from RGB-D frames. Use when a workflow needs perception geometry or planner inputs computed on CPU with no model weights.

graph-robots/open-robot-skills · 64 tokens

molmoact-libero

Run the MolmoAct LIBERO checkpoint (allenai/MolmoAct-7B-D-LIBERO-0812) as a closed-loop VLA policy for the dexterous pick-and-place segment of a task. Drives a Franka Panda in the LIBERO/robosuite OSCPOSE action space from agentview + wrist cameras, served behind a vLLM-style script speaking the openpi websocket…

graph-robots/open-robot-skills · 226 tokens

diansai-2026

A full workflow guide for control-focused electronics competitions, covering the path from understanding the problem to testing and writing the design report.

gugugugg/diansai-2026 · 169 tokens