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 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。
安装前可以查看交给 AI 代理的指令内容。
Verify the requested browser-visible behavior with the repository's Playwright installation. HTTP success and empty error logs are supporting evidence, not proof that client plugins or the requested interaction work.
requestfailed event.networkidle or a fixed delay as readiness for a long-lived event connection.Report relevant errors, status, assertions, and rendered evidence, redacting credentials and private data rather than dumping logs verbatim. Distinguish page load, plugin readiness, and interaction acceptance. An empty error array only means no error was observed in the checked interval.
Browser verification does not change service trust: direct LAN access accepts only loopback or the host's discovered local interface IP literals, and remote peers still require daemon-user authentication.
Return pageStatus, consoleErrors, pageErrors, failedRequests,
bodyEvidence, verdict, and blockingReasons.
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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 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。
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。