dart: Command for Claude Code

.claude/commands/dart-resume.md

dart-resume is a command for Claude Code from dartsim/dart. It costs 6 tokens per session (1,487 once invoked), scanned A, original, BSD-2-Clause.

A command for continuing unfinished work from a previous coding session.

In plain words
What is it for?
Rebuilding a plan, inspecting the repository, verifying results, and finishing or clearly blocking a development task.
Why use it?
It helps recover the full task when work was interrupted instead of stopping after checking a single part of it.

Command for Claude Code

Written for Claude Code: argument-hint in frontmatter. Also seen: agent in frontmatter; mentions subagents; mentions AGENTS.md.

This is dartsim/dart's own configuration. It tells Claude Code how to work on dart itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything dart configures →

About the project

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.

dartsim/dart · 1,202 stars · on GitHub · dart.readthedocs.io

Reuse

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.

Copy the file
curl -O https://raw.githubusercontent.com/dartsim/dart/main/.claude/commands/dart-resume.md
Clone the repo
git clone --depth 1 https://github.com/dartsim/dart

Made for: Claude Code.

Wrote 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.

agentmods badge for dart-resume

README.md
[![agentmods](https://agentmods.dev/badge/commands/dartsim/dart/dart-resume.svg)](https://agentmods.dev/commands/dartsim/dart/dart-resume)
Your own site
<a href="https://agentmods.dev/commands/dartsim/dart/dart-resume"><img src="https://agentmods.dev/badge/commands/dartsim/dart/dart-resume.svg" alt="Measured on agentmods" height="20"></a>
Per session 6 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,487 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00006 $0.01487
Opus 5 $0.00003 $0.00744
Sonnet 5 $0.00001 $0.00297
Haiku 4.5 $0.00001 $0.00149

Measured yesterday against content hash 9746c13458b5, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

dart-resume 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 yesterday.

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.

.claude/commands/dart-resume.md · 147 lines

How it starts

The opening of the file, as written. The whole thing — 147 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Resume unfinished work: $ARGUMENTS

Objective

dart-resume is a completion-oriented task manager, not a status lookup or a single-slice helper by default. Resume the named or reconstructed work, build or refresh the execution plan, track progress in the repo-owned task surface, split independent work into verifiable packets, use subagents/sub-sessions only when the user explicitly requested delegation and the current AI surface permits it, verify every result, and keep going until the whole task is complete or a real blocker or approval boundary remains.

Decisions must be evidence-based. Before choosing between meaningful options, first improve or define the verification/debugging method so it can catch false positives and false negatives. Use repository inspection, focused tests, benchmarks, A/B comparisons, GUI or visual evidence, logs, and external resource searches as needed to decide from evidence instead of preference.

For a docs/dev_tasks/<task> target, full completion means all feasible task work is finished, durable decisions and deferred work are promoted, and the temporary dev-task folder is removed in the completing change. Do not stop after one successful slice unless the user explicitly requested a limited mode.

Argument Handling

Use $ARGUMENTS to identify the target, explicit scope limits, and execution modifiers. Interpret arguments in this order:

  1. Explicit scope-limited mode: if arguments include status, audit-only, plan-only, slice, or next-slice, honor that limit and state it in the plan. Without one of these limiters, do not downscope the session to a single slice.
  2. Execution modifiers: if arguments include no-subagents, run serially but keep the same whole-task completion objective. If arguments explicitly request subagents, parallel, delegation, or workers, use available AI-native delegation when the current surface permits it. Tool-use modifiers do not limit scope unless paired with an explicit scope-limited mode.
  3. Explicit target path: if an argument names docs/dev_tasks/<task> or a file under that folder, treat that dev task as the target and read its current README.md and RESUME.md snapshots after recon, following the selective-reading protocol in docs/dev_tasks/README.md. Resolve relative paths from the repo root discovered by git rev-parse --show-toplevel, not from the launch directory.
  4. Closeout wording: words such as complete, finish, retire, close out, or cleanup are accepted but not required for dev-task completion. Treat retire / close out as emphasis that the likely end state is durable-doc promotion plus folder removal.
  5. Branch/PR/issue hint: otherwise, treat arguments as a branch, PR, issue, topic, or free-form resume hint and reconstruct the task from live repo state.

Read the full file on GitHub · 147 lines

Changes

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.

  1. yesterday Changed 9746c13458b5
  2. 2d ago Changed · -44 lines 69d97ffc3bc3
  3. 4d ago Changed · -3 lines c53a03d7bc26
  4. 6d ago First seen · 194 lines · 6 tokens per session scan A 7edecc488221

Subscribe to this mod's changes

dart-resume is a command published in the GitHub repository dartsim/dart (1,202 stars, last pushed yesterday), licensed BSD-2-Clause. It adds 6 tokens to every session and 1,487 once invoked, about $0.0000 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.