dart-contribute — collision-detection dart-contribute, community, collision-detection, ide skills, computer-animation, constraint-dynamics, dartpy, dynamics, gazebo, inverse-kinematics, Claude Code

v1.0.0
GitHub

About this Skill

Ideal for Robotics and Animation Agents requiring advanced physics engine capabilities with C++20 and Python bindings. DART contribution workflow - branching, PRs, code review, dual-PR for bugfixes

# Core Topics

collision-detection computer-animation constraint-dynamics dartpy dynamics gazebo
dartsim dartsim
[1.1k]
[296]
Updated: 2/22/2026

Killer-Skills Review

Decision support comes first. Repository text comes second.

Reference-Only Page Review Score: 7/11

This page remains useful for operators, but Killer-Skills treats it as reference material instead of a primary organic landing page.

Original recommendation layer Concrete use-case guidance Explicit limitations and caution Locale and body language aligned
Review Score
7/11
Quality Score
49
Canonical Locale
en
Detected Body Locale
en

Ideal for Robotics and Animation Agents requiring advanced physics engine capabilities with C++20 and Python bindings. DART contribution workflow - branching, PRs, code review, dual-PR for bugfixes

Core Value

Empowers agents to simulate complex robotics and animation scenarios using a C++20 physics engine, leveraging collision detection, constraints, and Python bindings for seamless integration with DART, gazebo, and urdf.

Ideal Agent Persona

Ideal for Robotics and Animation Agents requiring advanced physics engine capabilities with C++20 and Python bindings.

↓ Capabilities Granted for dart-contribute

Developing realistic robotics simulations with collision detection and constraints
Creating detailed animation sequences with precise physics engine control
Integrating DART with gazebo and urdf for comprehensive robotics and animation development

! Prerequisites & Limits

  • Requires C++20 compatibility
  • Limited to DART, gazebo, and urdf ecosystems
  • Python bindings required for non-C++ interactions

Why this page is reference-only

  • - The underlying skill quality score is below the review floor.

Source Boundary

The section below is imported from the upstream repository and should be treated as secondary evidence. Use the Killer-Skills review above as the primary layer for fit, risk, and installation decisions.

After The Review

Decide The Next Action Before You Keep Reading Repository Material

Killer-Skills should not stop at opening repository instructions. It should help you decide whether to install this skill, when to cross-check against trusted collections, and when to move into workflow rollout.

Install Path

Start With Installation And Validation

If this skill is worth continuing with, the next step is to confirm the install command, CLI write path, and environment validation.
Trusted Recheck

Cross-Check Against Trusted Picks

If you are still comparing multiple skills or vendors, go back to the trusted collection before amplifying repository noise.
Workflow

Move To Workflow Collections For Team Rollout

When the goal shifts from a single skill to team handoff, approvals, and repeatable execution, move into workflow collections.
Labs Demo

Browser Sandbox Environment

⚡️ Ready to unleash?

Experience this Agent in a zero-setup browser environment powered by WebContainers. No installation required.

Boot Container Sandbox

FAQ & Installation Steps

These questions and steps mirror the structured data on this page for better search understanding.

? Frequently Asked Questions

What is dart-contribute?

Ideal for Robotics and Animation Agents requiring advanced physics engine capabilities with C++20 and Python bindings. DART contribution workflow - branching, PRs, code review, dual-PR for bugfixes

How do I install dart-contribute?

Run the command: npx killer-skills add dartsim/dart. It works with Cursor, Windsurf, VS Code, Claude Code, and 19+ other IDEs.

What are the use cases for dart-contribute?

Key use cases include: Developing realistic robotics simulations with collision detection and constraints, Creating detailed animation sequences with precise physics engine control, Integrating DART with gazebo and urdf for comprehensive robotics and animation development.

Which IDEs are compatible with dart-contribute?

This skill is compatible with Cursor, Windsurf, VS Code, Trae, Claude Code, OpenClaw, Aider, Codex, OpenCode, Goose, Cline, Roo Code, Kiro, Augment Code, Continue, GitHub Copilot, Sourcegraph Cody, and Amazon Q Developer. Use the Killer-Skills CLI for universal one-command installation.

Are there any limitations for dart-contribute?

Requires C++20 compatibility. Limited to DART, gazebo, and urdf ecosystems. Python bindings required for non-C++ interactions.

↓ How To Install

  1. 1. Open your terminal

    Open the terminal or command line in your project directory.

  2. 2. Run the install command

    Run: npx killer-skills add dartsim/dart. The CLI will automatically detect your IDE or AI agent and configure the skill.

  3. 3. Start using the skill

    The skill is now active. Your AI agent can use dart-contribute immediately in the current project.

! Reference-Only Mode

This page remains useful for installation and reference, but Killer-Skills no longer treats it as a primary indexable landing page. Read the review above before relying on the upstream repository instructions.

Upstream Repository Material

The section below is imported from the upstream repository and should be treated as secondary evidence. Use the Killer-Skills review above as the primary layer for fit, risk, and installation decisions.

Upstream Source

dart-contribute

Install dart-contribute, an AI agent skill for AI agent workflows and automation. Works with Claude Code, Cursor, and Windsurf with one-command setup.

SKILL.md
Readonly
Upstream Repository Material
The section below is imported from the upstream repository and should be treated as secondary evidence. Use the Killer-Skills review above as the primary layer for fit, risk, and installation decisions.
Supporting Evidence
<!-- AUTO-GENERATED FILE - DO NOT EDIT MANUALLY --> <!-- Source: .claude/skills/dart-contribute/SKILL.md --> <!-- Sync script: scripts/sync_ai_commands.py --> <!-- Run `pixi run sync-ai-commands` to update -->

DART Contribution Workflow

Load this skill when contributing code to DART.

Full Documentation

For complete guide: docs/onboarding/contributing.md

For code style: docs/onboarding/code-style.md

Branch Naming

  • feature/<topic> - New features
  • fix/<topic> - Bug fixes
  • refactor/<topic> - Refactoring
  • docs/<topic> - Documentation

PR Workflow

bash
1# Create branch
2git checkout -b <type>/<topic> origin/main
3
4# Make changes, then
5pixi run lint
6pixi run test-all
7
8# Push and create PR
9git push -u origin HEAD
10gh pr create --draft --milestone "DART 7.0"

Rule of thumb: run pixi run lint before committing so auto-fixes are included.

Use .github/PULL_REQUEST_TEMPLATE.md and ensure the PR description covers Summary, Motivation, Changes, Testing, Breaking Changes, and Related Issues.

Milestones (Required)

Always set a milestone when creating PRs:

Target BranchMilestone
mainDART 7.0 (or next major)
release-6.16DART 6.16.x (current patch)
bash
1# Set milestone on existing PR
2gh pr edit <PR#> --milestone "DART 7.0"
3
4# List available milestones
5gh api repos/dartsim/dart/milestones --jq '.[] | .title'

CRITICAL: Bug Fix Dual-PR

Bug fixes require PRs to BOTH branches:

  1. release-6.16 - Current release
  2. main - Next release

Steps:

  1. Fix on release-6.16 first
  2. Cherry-pick to main
  3. Create separate PRs for each

CHANGELOG (After PR Created)

After creating a PR, check if CHANGELOG.md needs updating:

Change TypeUpdate CHANGELOG?
Bug fixes✅ Yes
New features✅ Yes
Breaking changes✅ Yes (in Breaking Changes section)
Documentation improvements✅ Yes (in Tooling and Docs)
CI/tooling changes✅ Yes (in Tooling and Docs)
Refactoring (no behavior change)⚠️ Maybe (if significant)
Dependency bumps⚠️ Maybe (if user-facing)
Typo fixes❌ No

Format: - Description. ([#PR](https://github.com/dartsim/dart/pull/PR))

bash
1# Example entry in CHANGELOG.md under appropriate section:
2- Added AI-native documentation with AGENTS.md and module-specific guides. ([#2446](https://github.com/dartsim/dart/pull/2446))

Code Review

  • Address all feedback
  • Keep changes minimal
  • Update tests if behavior changed
  • Run full validation before pushing fixes

CI Loop

bash
1gh run watch <RUN_ID> --interval 30

Fix failures until green.

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