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.
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 dartsim/dart --skill dart-mechanical-refactorgit 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-mechanical-refactor)<a href="https://agentmods.dev/skills/dartsim/dart/dart-mechanical-refactor"><img src="https://agentmods.dev/badge/skills/dartsim/dart/dart-mechanical-refactor/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-mechanical-refactor"><img src="https://agentmods.dev/badge/skills/dartsim/dart/dart-mechanical-refactor.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- 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 | $0.00020 | $0.00507 |
| Opus 5.5 | $0.00008 | $0.00203 |
| Sonnet 5.5 | $0.00004 | $0.00101 |
| Haiku 4.5 | $0.00002 | $0.00051 |
Grade A, and why
dart-mechanical-refactor 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 10d 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.
What it actually says
dart-mechanical-refactor
Use this skill to run the DART dart-mechanical-refactor workflow. The editable workflow
source lives in .claude/commands/; this generated skill is its entrypoint for
Codex and Muse.
Invocation
- Claude Code:
/dart-mechanical-refactor <arguments> - Codex:
$dart-mechanical-refactor <arguments> - Muse:
/dart-mechanical-refactor <arguments>
Treat the text after the skill name, or the user's request when the skill is
loaded on demand, as $ARGUMENTS. When the workflow references $1, $2,
etc., map those to the positional values supplied by the user.
Command Body
Perform mechanical refactor: $ARGUMENTS
Required Reading
@AGENTS.md @CONTRIBUTING.md @docs/onboarding/code-style.md
Workflow
- Define the exact transformation and scope before editing.
- Create a topic branch from the target branch, for example
git switch --no-track -c refactor/<topic> origin/main. - Prefer scriptable or automated edits when the transformation is repetitive.
- Keep behavior unchanged; do not mix in feature work or cleanup outside scope.
- If reorganizing files, update CMake, pixi tasks, generated indexes, and docs.
- Run focused checks first, then broader checks according to risk:
pixi run lintpixi run buildpixi run testpixi run test-allwhen feasiblepixi run -e gazebo test-gzwhen package, collision, constraint, or downstream Gazebo/gz-physics compatibility could be affected
- Ask for explicit maintainer/user approval before pushing or opening a PR. After approval, open a PR with a clear scope statement and no behavior-change claim unless tested.
Output
- Transformation summary
- Files or areas changed
- Verification run
- Any residual risk
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.
- 10d ago Changed · +1 lines 605868d6db13
- 13d ago Changed 0a9b7c84b644
- 18d ago Changed 7715fc9ede64
- 24d ago Changed · +2 lines 519ded52da2d
- 1mo ago Changed 303e4c3d13d5
- 1mo ago Changed · -1 lines ab7c127292a7
- 1mo ago First seen · 59 lines · 20 tokens per session scan A e739e50122c0
dart-mechanical-refactor is a skill published in the GitHub repository dartsim/dart (1,217 stars, last pushed today), licensed BSD-2-Clause. It adds 20 tokens to every session and 507 once invoked, about $0.0001 per session on Opus 5.5. 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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