Use when Spark engineering knowledge must be placed, deduplicated, migrated, or validated across AGENTS, Notes, Roles, Skills, and Workflows.
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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.
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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.
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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.
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Use when a Spark change needs its authoritative owner, affected boundaries, risks, acceptance criteria, and smallest verifiable slice established before implementation or review.
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Use when a Spark implementation needs an evidence-based review for correctness, ownership, compatibility, failure handling, maintainability, and unnecessary complexity.
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Use when a working Spark implementation should be simplified without changing its observed behavior, ownership, compatibility, or public contract.
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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.
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