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.
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.
curl -O https://raw.githubusercontent.com/dartsim/dart/main/.agents/skills/dart-ci/SKILL.mdgit clone --depth 1 https://github.com/dartsim/dartWrote 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/dartsim/dart/dart-ci)<a href="https://agentmods.dev/skills/dartsim/dart/dart-ci"><img src="https://agentmods.dev/badge/skills/dartsim/dart/dart-ci/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/dartsim/dart/dart-ci"><img src="https://agentmods.dev/badge/skills/dartsim/dart/dart-ci.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
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.
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 | $0.00018 | $0.00563 |
| Opus 5 | $0.00009 | $0.00282 |
| Sonnet 5 | $0.00004 | $0.00113 |
| Haiku 4.5 | $0.00002 | $0.00056 |
Grade A, and why
dart-ci 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.
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 — 55 lines — stays where its author put it; the contents beside it link to each section on GitHub.
DART CI/CD Troubleshooting
Load this skill when debugging CI failures or working with GitHub Actions.
When the failing claim depends on 3D structure or behavior, also load
dart-verify-sim and reproduce it with a text oracle plus assessed visual
evidence, or record why that renderer is unavailable in the failing environment.
Full Documentation
For complete CI/CD guide: docs/onboarding/ci-cd.md
Common Failure Modes
| Failure Type | Solution |
|---|---|
| Formatting fails | pixi run lint; push only after approval |
| Codecov patch fails | Inspect coverage upload/reporting before adding tests |
| FreeBSD RTTI fails | Use type enums + static_cast instead of dynamic_cast |
| macOS ARM64 SEGFAULT | Replace alloca()/VLAs with std::vector<T> |
| RTD build fails | Use defensive .get(key, default) patterns |
| gz-physics fails | Reproduce with pixi run -e gazebo test-gz |
CUDA Runner Policy
The project has a trusted ubuntu-latest-gpu runner for same-repository CUDA
runtime validation, but it must never run untrusted fork-PR code. Consequences:
- Same-repository PRs, protected branch pushes, and manual dispatches use the
GPU runner and run
pixi run --locked -e cuda test-cuda. - Fork PRs use a GitHub-hosted fallback and compile CUDA targets without running GPU-only steps.
- Local CUDA validation is
pixi run -e cuda test-allon Linux hosts with a visible NVIDIA CUDA runtime; local Pixi config auto-detects visible GPU compute capabilities forDART_CUDA_ARCHITECTURES. pixi run check-phase5-cuda-workflowenforces the trusted-event GPU guard and fork-PR hosted fallback inci_cuda.yml.
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.
- 3d ago Changed · -47 lines b59cd4e91559
- 5d ago Changed · +5 lines daa87b62e280
- 7d ago First seen · 97 lines · 18 tokens per session scan A 04b4ae4bfb2d
dart-ci is a skill published in the GitHub repository dartsim/dart (1,204 stars, last pushed 2d ago), licensed BSD-2-Clause. It adds 18 tokens to every session and 563 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.
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