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-new-task/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-new-task)<a href="https://agentmods.dev/skills/dartsim/dart/dart-new-task"><img src="https://agentmods.dev/badge/skills/dartsim/dart/dart-new-task.svg" alt="Measured on agentmods" 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 | $0.00026 | $0.01077 |
| Opus 5 | $0.00013 | $0.00539 |
| Sonnet 5 | $0.00005 | $0.00215 |
| Haiku 4.5 | $0.00003 | $0.00108 |
Grade A, and why
dart-new-task 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 today.
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 — 98 lines — stays where its author put it; the contents beside it link to each section on GitHub.
dart-new-task
Use this skill in Codex to run the DART dart-new-task workflow. The editable
workflow source lives in .claude/commands/; this file is its generated adapter
in the shared .agents/skills/ catalog.
Invocation
- Claude Code:
/dart-new-task <arguments> - Codex:
$dart-new-task <arguments>
Treat the text after the skill name as $ARGUMENTS. When the workflow
references $1, $2, etc., map those to the positional values supplied by the
user.
Command Body
Start a new task in DART: $ARGUMENTS
Required Reading
Read these files first: @AGENTS.md @docs/ai/principles.md @docs/README.md
Then load owners when the task needs them:
- Multi-phase/session work:
docs/dev_tasks/README.mdbefore creating or resuming the project home. - Branching or contribution:
docs/onboarding/contributing.mdbefore setup. - C++/Python/build changes:
docs/onboarding/building.mdanddocs/onboarding/code-style.mdbefore implementation. - Docs edits:
docs/AGENTS.mdbefore editing. - Acceptance and testing: the task's gate set in
docs/ai/verification.mdbefore implementation; load detailed test guidance for the affected surface.
Workflow
- Understand the task - Parse: goal, constraints, type (feature|bugfix|refactor|docs)
- Assess scope - Multi-phase or multi-session? Create
docs/dev_tasks/<task>/(seedocs/dev_tasks/README.mdfor criteria). Team-scale work (multiple parallel lanes needing orchestrated worker agents) switches todart-ultraworkinstead. For multi-session, design-heavy, public API, solver/paper, release, or cross-module work, fill the dev-task specification intake before editing: value, scope, assumptions, traceability, non-goals, acceptance evidence, gates, and open decisions. If consequential ambiguity would change public API, release compatibility, numerical correctness, benchmark claims, or roadmap scope, record an owner-localDecision neededblock instead of silently choosing. - Setup - Choose the target branch before creating a topic branch:
- features/docs/non-bugfix refactors: branch from
origin/main - bug fixes that apply to the current release line: branch from the active
DART 6 LTS
origin/release-6.*branch first, then cherry-pick or reapply tomain
- features/docs/non-bugfix refactors: branch from
- Implement - Keep commits focused, follow code style
- Task lifecycle - For an intermediate commit or PR, preserve and update
the active task folder. In the completing change, follow
docs/dev_tasks/README.md: complete feasible work, promote durable artifacts, and remove the folder before final validation and commit. Preserve the owner's approval requirement for retiring unfinished work. - Verify - Run
pixi run lintbefore committing, then the gate set for this task type fromdocs/ai/verification.md. If the claim depends on 3D structure or behavior, route throughdart-verify-sim: text oracle first, then assessed claim-tied visual evidence, or record why it is not applicable. - PR - After explicit maintainer/user approval,
git push -u origin HEADthengh pr create --draft --base <target-branch> --milestone "<milestone>"(DART 7.0formain, branch-matching DART 6.x release milestone for the active DART 6 LTS branch); follow.github/PULL_REQUEST_TEMPLATE.md
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.
- today Changed · -1 lines e09649994d49
- 2d ago Changed · +5 lines 402ce339efab
- 4d ago Changed · -14 lines c700d81c19b1
- 6d ago First seen · 108 lines · 26 tokens per session scan A 7a7a0c4ec4d3
dart-new-task is a skill published in the GitHub repository dartsim/dart (1,202 stars, last pushed today), licensed BSD-2-Clause. It adds 26 tokens to every session and 1,077 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.
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.
atmos-config
Atmos root configuration: atmos.yaml discovery, precedence, deep merging, basepath, imports, minimal bootstrap, and routing to narrower Atmos skills.
workthreads
SpecStory Workthreads - a weekly work-thread rollup across a team's repos from SpecStory coding histories (any agent - Claude Code, Codex, Cursor, Gemini, and more). It groups the window's sessions into threads of work per project and labels each new / open / recently closed, so a lead sees what shipped, what is still…
story-readiness
Validate that a story file is implementation-ready. Checks for embedded GDD requirements, ADR references, engine notes, clear acceptance criteria, and no open design questions. Produces READY / NEEDS WORK / BLOCKED verdict with specific gaps. Use when user says 'is this story ready', 'can I start on this story', 'is…
autotask-creator
Rules for automation CRUD from the group-chat commander. The commander does not call mutation tools and does not edit cloud/autotasks files directly. It emits one or more top-level ... containers in its final text; the bus parses and applies them after the turn.
monorepo-management
Master monorepo management with Turborepo, Nx, and pnpm workspaces to build efficient, scalable multi-package repositories with optimized builds and dependency management. Use when setting up monorepos, optimizing builds, or managing shared dependencies.