dart-ultrawork
GitHub用于启动大型或自主 DART 任务的工作流。通过项目文档和可选决策访谈,协调任务的分解、委派、审查与执行,支持面试、简报及恢复模式,确保多会话团队规模开发的一致性。
触发场景
安装
npx skills add dartsim/dart --skill dart-ultrawork -g -y
SKILL.md
Frontmatter
{
"name": "dart-ultrawork",
"description": "DART Ultrawork: kick off a large or autonomous DART task with project-home docs, an optional decision interview, and orchestrated execution"
}
dart-ultrawork
Use this skill in Codex to run the DART dart-ultrawork 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-ultrawork <arguments> - Codex:
$dart-ultrawork <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
Start a team-scale or autonomous DART task: $ARGUMENTS
Required Reading
@AGENTS.md @docs/ai/principles.md @docs/ai/north-star.md @docs/ai/orchestration.md @docs/ai/sessions.md @docs/ai/verification.md @docs/dev_tasks/README.md @docs/information-architecture.md @docs/plans/dashboard.md @docs/onboarding/contributing.md @docs/onboarding/changelog.md @docs/onboarding/ai-tools.md
Arguments
$ARGUMENTS is a task brief plus optional mode flags:
mode=interview: ask one up-front batch of critical questions.mode=brief: treat provided context as sufficient unless escalation applies.mode=resume: start from the existingdocs/dev_tasks/<task>/project home and run the session-start protocol before changing files.interview=skip: skip maintainer questions only when the brief already answers all consequential decisions.
The brief may be prose or a structured TASK / CONTEXT block. Extract north
star, deliverable, acceptance criteria, constraints, risks, references, paths,
issues/PRs/branches, commands, and first step when present.
Workflow
You are the orchestrator, supervisor, and steerer for the entire task: you
decompose, delegate, review, and keep evidence honest. Workers implement.
Follow the orchestrator/executor contract and packet sizing rules in
docs/ai/orchestration.md. Use dart-new-task instead when the work is a
bounded single-session task and the user did not ask for autonomous project
handling.
- Session start and current reality - Locate the project home. For
DART autonomous projects this is
docs/dev_tasks/<task>/, not a parallel project directory. If it exists, read itsREADME.md,RESUME.md, and any autonomous sidecars such asdecisions.md,verification.md, orprogress-log.md; then verify checkout state, current branch, and any branch/PR evidence named by the docs. If the docs are stale, update the handoff/current-reality note before relying on them. If no project home exists and the task is multi-session, team-scale, design-heavy, risky, or explicitly autonomous, createdocs/dev_tasks/<task>/before implementation. If prior work exists elsewhere, first absorb or summarize it into the project home. - Understand and scout - Restate the north star, final deliverable,
acceptance criteria, quality bar, non-goals, constraints, risks, and target
branch line (DART 7
main, DART 6 LTS, or both). Scout the territory first with named docs/code, read-only searches, adart-analyzepass, or focused reference review; draft a candidate decomposition privately before asking anything. - Interview decisions; self-resolve uncertainties - Ask at most one
up-front batch of critical questions. Escalate before destructive
operations, history rewrites, irreversible migrations, meaningful cost,
security/credential/secret handling, legal or privacy-sensitive decisions,
major product-direction choices not covered by the brief, conflicts with
stated constraints, or any assumption whose wrong answer could cause
significant harm. If input is unavailable, choose the safest reversible path,
document the assumption, and continue only with non-blocked work. Then split
consequential unknowns:
- Maintainer decisions: preference, scope, public API, release,
quality-bar, or roadmap calls that evidence cannot settle. Ask the human
now in one batched interview (focused questions with 2-4 concrete
options each, recommendation first). Do not start large work while a
consequential decision is open. Skip this discretionary interview when
mode=brief; also skip wheninterview=skipand the prompt already answers everything consequential. In both cases, still follow the escalation rules above. - Evidence-resolvable uncertainties: anything a focused A/B test,
benchmark, throwaway spike, reference lookup, or blind-spot review can
settle. Do not ask the human; schedule these as spike/research packets
and record the method and result as evidence (see "Discovering unknowns
before committing" in
docs/ai/orchestration.md).
- Maintainer decisions: preference, scope, public API, release,
quality-bar, or roadmap calls that evidence cannot settle. Ask the human
now in one batched interview (focused questions with 2-4 concrete
options each, recommendation first). Do not start large work while a
consequential decision is open. Skip this discretionary interview when
- Create or refresh the tracking surface - Populate the project home with
value, north star, deliverable, scope, non-goals, assumptions, risks,
acceptance evidence, gates, dependencies, milestone, next actions, and
blockers. Behavior-bearing physics/simulation work needs a high-quality,
self-contained GUI or demos-app artifact unless explicitly out of scope.
Keep
RESUME.mdas the handoff; adddecisions.md,verification.md, andprogress-log.mdsidecars when they improve resumability or evidence. - Set the goal contract - Express done-when as verifiable outcomes
(files, tests, gates, artifacts). When the session supports a goal or
stop-hook mode (for example
/goalin Claude Code), set it to this contract so orchestration cannot stop early or loop forever. Stop once the acceptance criteria are satisfied, verification is recorded, docs are current, known gaps are documented, and unnecessary work has been removed or deferred. Every delegated packet gets its own contract: GOAL (one sentence), DONE WHEN (verifiable), EVIDENCE (what to record), RISKS, and NEXT STEP. - Decompose and route to workers - Cut work packets per
docs/ai/orchestration.md, then route by the current model routing indocs/ai/README.md: implementation packets to Codex executors, iterative build/test lanes to team workers when available, review lanes to an independent session, and critical decisions or stuck failures to the oracle. Without team tooling, execute packets sequentially throughdart-execute-packet. Use parallelism only when the environment supports it and file ownership can stay disjoint. - Run the autonomous work/review cycle - For each meaningful chunk: plan, execute, verify, then run an independent/specialized review lane. Treat review findings as hypotheses: investigate, fix or record no-fix evidence, clean up, re-verify, and re-review. A packet is not done until the current post-fix state has at least two clean review passes recorded.
- Supervise and steer - Monitor progress; unblock, reassign, or re-cut packets on scope mismatch. Workers return Task, Summary, Files changed, Evidence/tests, Risks, and Recommended next step. Use Codex from Claude, Claude from Codex, subagents, or specialist reviewers when available; fall back to role-separated local review only when unavailable. Root-cause failures and fold newly discovered unknowns back into step 3.
- Update docs at each stopping point - Every meaningful cycle updates the
project home:
README.mdfor status/plan/risks,RESUME.mdfor the next fresh-session handoff,decisions.mdif decisions changed,verification.mdif checks ran or gaps were found, andprogress-log.mdfor completed chunks when that sidecar exists. Keep docs current enough for a zero-context session to resume without hidden chat memory. - Version-control and closeout - Keep commits and PRs coherent: separate
feature work, bug fixes, refactors, docs, experiments, and AI-infra changes
when practical; review the diff, remove unrelated changes, make the
changelog decision, and run
pixi run lintbefore commits. Run task-specific gates fromdocs/ai/verification.md, record evidence per packet, and complete the principle audit. A project is complete only when the north star and acceptance criteria are met, verification evidence is recorded, docs are current, known gaps are documented, unnecessary work is removed or deferred, and final state is summarized inRESUME.mdor a durable owner. Promote durable artifacts out ofdocs/dev_tasks/<task>/and remove the folder in the completing PR. GitHub mutations (push, PR, comments, re-triggers) only with explicit maintainer/user approval.
Kickoff Prompt Template
Canonical fresh-session prompt. TASK, context, and Done when are per-task;
reuse the Logistics block verbatim.
TASK: <one-sentence objective>
<Per-task context: constraints, quality bar, must/never rules, and pointers
to the docs, code, branches, or references that define the territory.>
Done when:
- <verifiable outcome: a file, test, gate, benchmark, or artifact>
- <verifiable outcome>
Logistics:
- Run /dart-ultrawork with this task. You are the orchestrator,
supervisor, and steerer: decompose, delegate, review, and keep evidence
honest.
- Interview first: ask the maintainer only the consequential decisions that
evidence cannot settle; resolve everything else yourself and record the
evidence.
- Use docs/dev_tasks/<task>/ as the project home. Keep README.md,
RESUME.md, and any decisions.md / verification.md / progress-log.md
sidecars current enough for a zero-context session to resume.
- Prioritize correctness over speed, but stop once acceptance criteria are
satisfied, verification is recorded, docs are current, and known gaps are
documented. Manage resources responsibly; avoid endless exploration and
low-value polishing.
- Route well-defined implementation packets to Codex executors with GOAL /
DONE WHEN / EVIDENCE. Use team mode only when available and file ownership
can stay disjoint. Keep authoring and review separate. Use the oracle for
critical decisions, hard failures, and research synthesis.
- Set goal mode to Done-when; use Claude `/goal Run /dart-ultrawork with:
<real prompt>` or Codex `/goal $dart-ultrawork <real prompt>`. Treat Claude
goal text beginning `ulw:` or `ultrawok:` as shorthand for the same canonical
`/dart-ultrawork` workflow, not as separate capabilities.
- Read docs/ai/principles.md, docs/ai/north-star.md,
docs/ai/orchestration.md, and docs/ai/sessions.md before starting.
- Review loop: use specialized reviewers when available, investigate findings,
and require two clean passes on the current state before done.
- Verification first: task-specific gates, GUI/demo evidence when relevant,
pixi run lint before commits; GitHub mutations only with approval.
Output
- Interview record, uncertainty-resolution evidence, and project-home path
- Packet list, routing, goal contracts, gates, and review-loop status
- Per-packet evidence, GUI/demo artifacts when relevant, and updated docs
- Principle audit, cleanup status, and approved external mutations
版本历史
- 51b2d25 当前 2026-07-11 18:27


