dart-next

Use this skill in Codex to run the DART dart-next workflow. The editable workflow source currently lives in .claude/commands/, and this generated Codex skill is a generated Codex adapter entrypoint.

Invocation

• Claude Code/OpenCode: /dart-next <arguments>
• Codex: $dart-next <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

Select and execute the next bounded DART task: $ARGUMENTS

Required Reading

@AGENTS.md @docs/ai/principles.md @docs/ai/north-star.md @docs/ai/workflows.md @docs/ai/verification.md @docs/plans/README.md @docs/plans/dashboard.md @docs/plans/north-star-roadmap.md @docs/dev_tasks/README.md @docs/onboarding/contributing.md @docs/onboarding/ci-cd.md @docs/onboarding/ai-tools.md

Arguments

Interpret $ARGUMENTS as optional constraints:

• mode=select: choose one task and stop with evidence.
• mode=execute: choose one task, make local changes, and verify locally. This is the default when the user asks to do the work.
• mode=pr: execute locally and prepare PR text, then ask for explicit maintainer/user approval before any GitHub, PR, CI, branch, or review-thread mutation, including pushes, PR creation, PR comments, reviewer requests, review re-triggers, thread resolution, ready-for-review transitions, merges, CI reruns, or branch deletion.
• size=tiny|small|medium|large or days=N: fit the chosen task to the requested scope. Default to small, meaning one focused local session.
• focus=<topic>: prefer a focus area without making it the only allowed candidate. Examples: ai-native, easy-start, algorithm, compute, release, ci, docs, python, io, PLAN-020, world_split, dartpy, or a file path.
• area=<dimension>: alias for focus=<dimension>.
• Any issue, PR, branch, milestone, failing check, file path, or user-stated priority overrides the default dashboard order.

If constraints conflict or make the task unsafe to select, stop and ask one clarifying question.

Workflow

1. Inspect local state before choosing work:

   git status --short --branch
   git diff --stat
   

2. Build the candidate set from tracked evidence:
   • explicit user instruction in $ARGUMENTS;
   • current branch, local diff, or active docs/dev_tasks/<task>/ state;
   • docs/plans/dashboard.md, in priority order, especially Horizon: Now;
   • docs/ai/north-star.md gaps and readiness criteria;
   • issue, PR, or CI state named by the user or inferable from the branch.
3. Exclude candidates that are blocked, larger than the requested size, missing enough evidence to start, likely to require unapproved GitHub mutations, or only bootstrap/maintain the dart-next workflow itself unless explicitly focused.
4. Prefer the highest-value remaining candidate in this order:
   • user-specified issue, PR, failing check, or file path;
   • candidates matching focus=<topic> or area=<dimension>;
   • failing CI or review feedback on the current PR;
   • active dev task with a clear next local step;
   • first unblocked Horizon: Now dashboard item fitting the size;
   • issue triage or plan refinement when implementation evidence is missing.
5. State the selected task before editing:
   • candidate and source evidence;
   • rejected higher-priority candidates and why they were not selected;
   • whether the preferred focus matched the selected task, and why if it did not;
   • size assumption and expected stopping point;
   • workflow to follow next;
   • verification gate from docs/ai/verification.md.

Execution Routing

After selection, follow the most specific DART workflow:

If the selected task is multi-session or needs design tracking, create or update docs/dev_tasks/<task>/ according to docs/dev_tasks/README.md.

Local Work Cycle

1. Load task-specific docs from AGENTS.md and the routed workflow.
2. Make the smallest coherent local change that satisfies the selected task.
3. Run the strongest relevant local gate:
   • docs/AI work: gates from docs/ai/verification.md;
   • C++ or Python behavior: pixi run lint, build, and focused tests;
   • CI work: local reproduction when possible plus the fixed check.
4. Review the local diff before declaring completion:

   git diff --stat
   git diff --check
   

5. Optimize or benchmark only when the selected objective is performance sensitive or the plan gate explicitly requires performance evidence.
6. Update durable docs when the task changes project state, public workflow, or roadmap evidence.
7. Run the completion audit from docs/ai/verification.md before finalizing.

PR And Review Management

Use $dart-pr or /dart-pr only after local verification is complete and the user requested PR preparation. Ask for explicit maintainer/user approval before any GitHub, PR, CI, branch, or review-thread mutation, including push, PR creation, PR comment, reviewer request, review re-trigger, review-thread resolution, ready-for-review transition, CI rerun, merge, or branch deletion.

After a PR exists and explicit approval covers PR management, use $dart-manage-pr or /dart-manage-pr for CI, review, and cleanup. For the first Codex review on a draft PR, prefer a top-level @codex review after explicit approval for PR comments; it can run while the PR remains draft. Once Codex is clean and local validation passes on the current head (default pixi run test-all, plus pixi run -e cuda test-all on Linux hosts with a visible NVIDIA CUDA runtime), the draft is ready to mark ready for human review after approval, while merge still waits for required hosted checks.

Output

Report:

• selected task, size, evidence, and routed workflow;
• files changed and verification commands run;
• completion-audit result and any remaining blocker;
• PR readiness status, without performing external mutations unless explicit approval was given.