Use when Spark engineering knowledge must be placed, deduplicated, migrated, or validated across AGENTS, Notes, Roles, Skills, and Workflows.
中文简介正在准备中。当前显示原文说明。
Use when a Spark implementation needs an evidence-based review for correctness, ownership, compatibility, failure handling, maintainability, and unnecessary complexity.
中文简介正在准备中。当前显示原文说明。
查看安装方法安装前可以查看交给 AI 代理的指令内容。
Review the actual diff and reachable behavior. Treat unnecessary complexity as an engineering defect when it creates permanent surface area, duplicated semantics, state, lifecycle, or failure modes without a corresponding invariant.
Use spark-change-scope first when the owner and acceptance boundary are not
already explicit. Use spark-find-simplifications when a finding needs an
equivalence-preserving removal plan.
limit before downstream filtering or skipping; prove that the limit is applied on the dimension whose fairness or completeness is claimed.Report these when the diff provides concrete evidence:
NOT_IMPLEMENTED methods, or compatibility machinery added only for possible future work;Do not report formatting or personal style preferences. A small helper is useful when it owns a real invariant, and validation belongs at an untrusted boundary. Missing future functionality is not a defect; surface area added today solely for that future may be. Added state, lifecycle, synchronization, or public surface is not merely style.
Do not accept tests that assert prompt wording unless exact representation is
the contract. Stop with needs-decision when correctness or ownership depends
on an unresolved product choice.
Return findings, verifiedBehaviors, residualRisks, and verdict. Each
finding includes severity, category, evidence, impact, deletionTest,
and repairDirection. Category is correctness | security | ownership | compatibility | complexity.
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Use when Spark engineering knowledge must be placed, deduplicated, migrated, or validated across AGENTS, Notes, Roles, Skills, and Workflows.
中文简介正在准备中。当前显示原文说明。
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.
中文简介正在准备中。当前显示原文说明。
Use when a Spark change needs its authoritative owner, affected boundaries, risks, acceptance criteria, and smallest verifiable slice established before implementation or review.
中文简介正在准备中。当前显示原文说明。
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.
中文简介正在准备中。当前显示原文说明。
Use when a working Spark implementation should be simplified without changing its observed behavior, ownership, compatibility, or public contract.
中文简介正在准备中。当前显示原文说明。
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.
中文简介正在准备中。当前显示原文说明。