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-fix-ci)<a href="https://agentmods.dev/commands/dartsim/dart/dart-fix-ci"><img src="https://agentmods.dev/badge/commands/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/commands/dartsim/dart/dart-fix-ci"><img src="https://agentmods.dev/badge/commands/dartsim/dart/dart-fix-ci.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 | $0.00006 | $0.00398 |
| Opus 5.5 | $0.00002 | $0.00159 |
| Sonnet 5.5 | $0.00001 | $0.00080 |
| Haiku 4.5 | $0.00001 | $0.00040 |
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 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
Fix CI failure: $ARGUMENTS
Required Reading
@AGENTS.md @docs/onboarding/ci-cd.md @docs/ai/verification.md
Workflow
When the failing claim depends on model/scene structure, simulation, dynamics,
collision/contact/constraints, or GUI/Filament output, use dart-verify-sim to pair
the focused reproduction with assessed, claim-tied visual evidence. Document a
visual exception when graphics support is unavailable or not applicable.
- 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.
- Reproduce locally with the smallest relevant command:
- formatting:
pixi run lint - tests:
pixi run test,pixi run test-py, or another existing focusedpixi run ...test task - coverage: add targeted tests for uncovered changed lines
- formatting:
- Fix the root cause with minimal scope.
- 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 the PR is green.
Output
- Root cause
- Fix or rerun action
- Commands run
- Current CI status
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 6ef3c1ff8542
- 23d ago Changed · -18 lines · -4 tokens per session cc1b49e04c01
- 1mo ago Changed · +2 lines 82d14c8132ee
- 1mo ago Changed · -1 lines f3df06805348
- 1mo ago First seen · 67 lines · 10 tokens per session scan A a6e6db26f500
dart-fix-ci is a command published in the GitHub repository dartsim/dart (1,217 stars, last pushed yesterday), licensed BSD-2-Clause. It adds 6 tokens to every session and 398 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 2026-09-01.
Other commands, from other repositories
ci-debug
Diagnose a failing CI run against an 11-pattern playbook. Classifies the failure, cites the relevant memory entry, proposes the exact fix command — but NEVER applies without explicit user approval. Use when a specific PR check or GitHub Actions run failed and you want a diagnosis instead of speculation. Don't use for…
metrics
Apply the CLI runtime and safety contract before executing a command. Runtime --help is authoritative.
traces
Apply the CLI runtime and safety contract before executing a command. Runtime --help is authoritative.
add-debug-wait
Add a wait step to a CI workflow for debugging test failures.
pr-quality-gate-reliability
You are reviewing a pull request for production survivability: how the change behaves when its dependencies misbehave, time out, or fail.
fix-ci
Find failing PR checks, inspect logs or check links, and apply focused fixes. Routing depends on failure type (build/test/security). Usage: /fix-ci [branch|PR].