Use when Spark engineering knowledge must be placed, deduplicated, migrated, or validated across AGENTS, Notes, Roles, Skills, and Workflows.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Use when designing a Spark feature or writing or materially revising a design proposal that needs repository-first research, user input on unresolved key choices, and an owner-aligned implementation plan before code changes.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
설치 방법 보기설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.
Turn a requested capability into an evidence-backed decision and the smallest plan that can prove it.
ask, use ask with those options, recommendation, and tradeoffs. When it does not, return structured needs-decision with the same options, recommendation, and root-question order so the caller can ask. That return completes this planning step; it does not mean a choice has been obtained.Until the key choices are obtained, mark the dependent selection and plan
needs-decision. Treat silence as no choice, not agreement. Do not implement
the dependent behavior while waiting. Editorial corrections and implementation
of existing decisions do not reopen settled choices or require a new proposal.
Put source citations and applicable versions in problemEvidence. Put the
basis of each selection, including reused decisions, explicit user choices,
and delegations, in selection. When verdict is needs-decision, options
holds the viable options and tradeoffs, selection holds the recommendation
and why, and openQuestions holds the root-question order for the caller.
A user choice establishes the design direction, not proposal acceptance or
implementation authority. Return problemEvidence,
options, selection, plan, acceptanceCriteria, risks, outOfScope,
validationCommands, openQuestions, and verdict.
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Use when Spark engineering knowledge must be placed, deduplicated, migrated, or validated across AGENTS, Notes, Roles, Skills, and Workflows.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Use when adding or updating Spark AI provider models or their compact and preflight metrics, especially baidu-oneapi, Grok, Claude, GPT, DeepSeek, OneAPI, context windows, output budgets, prices, thinking maps, or transports.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Use when a Spark change needs its authoritative owner, affected boundaries, risks, acceptance criteria, and smallest verifiable slice established before implementation or review.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Use when a Spark implementation needs an evidence-based review for correctness, ownership, compatibility, failure handling, maintainability, and unnecessary complexity.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Use when a working Spark implementation should be simplified without changing its observed behavior, ownership, compatibility, or public contract.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Use when a running Spark or DSH web service needs real-browser verification — page load, client-plugin boot errors, console errors, failed requests, or onboarding/dialog rendering — with the repository's own Playwright chromium.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.