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-fix-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-fix-ci)<a href="https://agentmods.dev/skills/dartsim/dart/dart-fix-ci"><img src="https://agentmods.dev/badge/skills/dartsim/dart/dart-fix-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-fix-ci"><img src="https://agentmods.dev/badge/skills/dartsim/dart/dart-fix-ci.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 | $0.00850 |
| Opus 5 | $0.00010 | $0.00425 |
| Sonnet 5 | $0.00004 | $0.00170 |
| Haiku 4.5 | $0.00002 | $0.00085 |
Grade A, and why
dart-fix-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 — 89 lines — stays where its author put it; the contents beside it link to each section on GitHub.
dart-fix-ci
Use this skill in Codex to run the DART dart-fix-ci 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-fix-ci <arguments> - Codex:
$dart-fix-ci <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
Fix CI failure: $ARGUMENTS
Required Reading
@AGENTS.md @docs/onboarding/ci-cd.md @docs/onboarding/release-management.md
Workflow
For a failure that depends on 3D structure or behavior, use dart-verify-sim
to reproduce the claim with text and assessed visual evidence, or record why
the renderer is unavailable.
- Identify the base branch. Default to
main; usebase=<branch>from$ARGUMENTSor the PR's own base when it is arelease-*branch. For arelease-*base, also readdocs/onboarding/release-management.mdand apply the release caveats called out below. - Identify failing checks:
gh pr checks <PR_NUMBER>orgh run view <RUN_ID>. - Inspect the first real failure:
gh run view <RUN_ID> --log-failed gh run view <RUN_ID> --job <JOB_ID> --log - If a job is still in progress, wait for logs instead of guessing.
- Choose where to fix. Check whether an equivalent fix already exists on
main. If continuing an existing PR, fetch and check out that PR branch instead of creating a new one. For arelease-*base, branch from the release branch and prefer cherry-picking the provenmainfix; keep any new fix release-scoped and minimal. Create a uniquely named branch. If the intended branch exists, inspect and resume it within the requested scope or choose a fresh name; do not reset it:git fetch origin <RELEASE_BRANCH> git switch --no-track -c fix/<unique-topic>-<release-branch> origin/<RELEASE_BRANCH> - Reproduce locally with the smallest relevant command:
- formatting:
pixi run lint - tests:
pixi run test,pixi run test-unit, or another existing focusedpixi run ...test task - coverage: add targeted tests for uncovered changed lines
- formatting:
- Fix the root cause with minimal scope. Explain why the failure was not caught earlier and whether workflow coverage should change.
- If the failure is infrastructure-only, ask for explicit maintainer/user
approval before rerunning the failed job or running:
gh run rerun <RUN_ID> --failed - Ask for explicit maintainer/user approval before pushing, CI re-triggers, or
other GitHub mutations; after approval, push and watch CI until green. For a
release-*base, use the current release milestone and the PR template when creating or updating the release-branch PR.
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 · +2 lines f56608411315
- 6d ago Changed · -1 lines e32a6af0b928
- 8d ago First seen · 88 lines · 20 tokens per session scan A dae9f9552975
dart-fix-ci is a skill published in the GitHub repository dartsim/dart (1,204 stars, last pushed 3d ago), licensed BSD-2-Clause. It adds 20 tokens to every session and 850 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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