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.
git 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/commands/dartsim/dart/dart-review-pr)<a href="https://agentmods.dev/commands/dartsim/dart/dart-review-pr"><img src="https://agentmods.dev/badge/commands/dartsim/dart/dart-review-pr/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/commands/dartsim/dart/dart-review-pr"><img src="https://agentmods.dev/badge/commands/dartsim/dart/dart-review-pr.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00007 | $0.00878 |
| Opus 5.5 | $0.00003 | $0.00351 |
| Sonnet 5.5 | $0.00001 | $0.00176 |
| Haiku 4.5 | $0.00001 | $0.00088 |
Grade A, and why
dart-review-pr 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 13d 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 — 93 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Review or respond to PR: $ARGUMENTS
Required Reading
@AGENTS.md @docs/onboarding/code-style.md @docs/onboarding/ai-tools.md (for AI-generated review handling) @docs/ai/verification.md
Workflow
To Review
gh pr view $1 && gh pr diff $1
Check code style, tests, docs, and focused commits. For claims involving 3D
structure or behavior, require the dart-verify-sim text oracle plus assessed
claim-tied Filament/debug-overlay evidence, or a justified replacement; a screenshot
alone is not correctness evidence.
To Address Feedback
gh pr view $1 --comments
Apply minimal fixes locally and verify. Do not push, comment, resolve threads, or re-trigger review without explicit maintainer/user approval for that external mutation.
For published PRs, prefer a new follow-up commit for review fixes so reviewers can inspect what changed since the previous round. Amend or force-push only after explicit maintainer/user approval and only when the user explicitly requests it or when there is a clear reason such as removing sensitive content or repairing broken branch history.
Before every push, first merge the latest base branch into the PR branch (on
every push, not just the first) so each pushed/CI-tested state reflects current
target base branch and conflicts surface early: git fetch origin <base> then
git merge --no-ff origin/<base>, rebuild/retest if the merge touched code, then
push. The local base merge is a routine pre-push step; the push itself still
requires explicit maintainer/user approval. Do not rebase a published PR branch
by default because it invalidates existing CI runs and makes PR review/comment
history harder to follow. Rebase or force-push only when the maintainer
explicitly requests it.
If the push is rejected because the remote PR head moved, fetch and compare the
remote head before retrying. If it already contains an equivalent review fix,
validate that head and follow docs/onboarding/ai-tools.md instead of pushing a
duplicate commit.
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.
- 13d ago Changed b3aafedca6eb
- 17d ago Changed · -6 lines 914588158b03
- 25d ago Changed · +13 lines 44e1f4292b75
- 1mo ago Changed · +15 lines 769447e43ebd
- 1mo ago Changed · +1 lines 21a7baa7a334
- 1mo ago First seen · 70 lines · 7 tokens per session scan A ffc3344265eb
dart-review-pr is a command published in the GitHub repository dartsim/dart (1,217 stars, last pushed yesterday), licensed BSD-2-Clause. It adds 7 tokens to every session and 878 once invoked, about $0.0000 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 2026-09-03.
Other commands, from other repositories
pr
Automated PR code quality review with language-aware analysis and project-specific profiles.
code-improve
Launch autonomous code improvement loop — detects opportunities, applies improvements, creates PRs for review.
refactor-sprint
Parallel refactor sprint — fires refactor-cleaner + code-simplifier + type-design-analyzer + tdd-guide simultaneously. Full cleanup in one pass.
quality-check-command
This command performs comprehensive code quality checks. Use it before commits or when implementation is complete.
clean-oop
Apply SOLID, Clean Code, dependency boundaries, and testability.
gsd-quality
Route to the appropriate quality / review skill based on the user's intent. gsd-code-review-fix was absorbed by gsd-code-review --fix in #2790.