「technical」の検索結果

Playwriting for banqiang-system Chinese opera (板腔体：京剧、豫剧、越剧、秦腔、评剧、沪剧、淮剧、川剧弹戏), where sung passages are paired seven- or ten-character lines varied by metre (板式) rather than filled into fixed tune patterns. Covers genre (唱工戏／做工戏／武戏), the main line, technical structure and 排场, how 行当 and a named star decide the writing, 程式, lyric craft (唱词：上下句、重点句、垛句、辙口), 宾白 and the sung/spoken seam, duets, what the writer marks on the page (Peking-opera vs Yue-opera style), the interface with actors and musicians, restoring old plays, and three contemporary routes including 现代戏. Sources; 范钧宏、翁偶虹、刘吉典、樊尚林、张庚郭汉城、罗怀臻、陆军, plus full scripts (锁麟囊／沙家浜／白蛇传／朝阳沟／潘金莲). Use when writing or revising 唱词, choosing 板式, writing for a performer or role-type, adapting a traditional play, writing a 现代戏, judging a project's genre, marking 锣鼓, or drawing the boundary before general dramaturgy skills apply. Not for 元杂剧/传奇/昆曲, which are the qupai system; see sw-chinese-opera-qupai.

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AI DevKit · Use when the user asks to brainstorm, ideate, generate ideas, expand options, challenge ideas, pressure-test ideas, compare concepts, narrow choices, name something, plan content angles, explore strategy, evaluate product ideas, technical approaches, experiments, or decisions.

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AI DevKit · Analyze and simplify existing implementations to reduce complexity, improve maintainability, and enhance scalability. Use when users ask to simplify code, reduce complexity, refactor for readability, clean up implementations, improve maintainability, reduce technical debt, or make code easier to understand.

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Chinese AI/tech writing de-AI editor for posts, X/Twitter threads, technical essays, product notes, model reviews, and public-writing drafts. Use when the user asks to 去AI味, 改得像本人, 写推特post, 精修中文AI技术文章, or complains about AI-flavored shells such as 不是A而是B, 真正/其实/本质上, 更重要的是, 冒号讲义腔, 空泛总结, 顺滑但没作者判断的稿子.

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Audit, question, suggest, or fact-preservingly revise a press release, blog post, contributed article, or expert explainer so AI answer systems can more easily retrieve, understand, quote, and cite its useful information. Use when someone asks for AI visibility, AI search, answer-engine, AEO, GEO, AI Overview, or ChatGPT citation optimization of supplied writing; when they want an evidence-aware pre-publication audit; or when another Newsjack workflow needs a prose-level AI-discoverability pass. Do not use as a technical SEO audit, rank tracker, publishing system, or promise of rankings, mentions, citations, traffic, or coverage.

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Manages work transitions between team members or agents by creating structured handoff documents, summarizing project status, documenting key decisions, blockers, and open questions, and generating onboarding briefs. Use when someone needs to hand off, hand over, or transition a project; pass work to another person or agent; brief a colleague taking over; prepare a shift change summary; or onboard someone mid-task. Produces ready-to-use handoff documents covering current status, next steps, known issues, technical context, and communication templates for both planned and unplanned transfers.

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Author and validate durable data and ML feasibility studies using the Feasibility Study Interchange Profile, constrained YAML authority, UUID URN identity, lifecycle lineage, and evidence traceability. Use when assessing whether available data and technical evidence support a proposed outcome.

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Ultra-compressed response style that reduces output token count while preserving technical accuracy, with intensity levels and auto-clarity safety rules

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Create or assess an evidence-grounded, falsifiable outcome hypothesis: a testable prediction of what measurable business result will change, for whom, by when, and how leading and lagging indicators will prove or disprove it. Use when framing measurable outcomes, turning an MVP, POC, feature, or technical initiative into a beneficiary result, defining targets and indicators, or judging whether evidence is strong enough to invest. Also applies to business outcome hypotheses, value hypotheses, and outcome statements.

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Run /architect when choosing between approaches, designing a feature or page, picking a tech stack, or when /develop says a decision is owed, anytime a load bearing technical decision is unmade. Asks deep questions, recommends an answer, and writes a build spec to docs/specs/. Owns all spec files.

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Verifies factual claims in documents using web search and official sources, then proposes corrections with user confirmation. Use when the user asks to fact-check, verify information, validate claims, check accuracy, or update outdated information in documents. Supports AI model specs, technical documentation, statistics, and general factual statements.

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Use when asked 帮我写开题报告, 开题答辩怎么准备, 文献综述怎么写, 技术路线图, 研究内容和创新点, or write a thesis proposal for a Chinese university. Produces a 开题报告 in the section order Chinese universities use (选题背景与意义, 国内外研究现状, 研究内容与目标, 研究方法与技术路线, 创新点, 研究基础, 进度安排, 预期成果, 参考文献), a literature review plan, a technical route diagram in text, and the questions the 开题答辩 panel is likely to ask.

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Use when asked 帮我准备大厂技术面试, 八股文怎么背, 模拟一面二面, 系统设计面试题, 项目深挖怎么答, 手撕算法, or run a mock technical interview for a Chinese internet company. Produces a preparation plan for the interview rounds Chinese tech companies run (笔试, 技术一面二面, 交叉面, HR 面), a 八股 question bank by stack with answer points, a system design walkthrough, a project deep-dive script, and a mock round asked one question at a time with follow-ups (追问) and scores.

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Plan an e-commerce category / collection page that ranks and merchandises well. Use when asked to design a category page, a PLP (product listing page), a collection page, or to improve category SEO and merchandising. Produces a brief — search intent & keywords, intro copy, merchandising/sort logic, filters & facets, internal links, and SEO/technical notes — so the page converts browsers and earns organic traffic.

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Diagram a system or technical architecture — services, data stores, and how they connect. Use when asked to draw an architecture, show how components fit together, map a system/data flow, or visualize services and dependencies. Produces a ready-to-render Mermaid diagram with grouped subgraphs (renders live, exportable as PNG/SVG) plus a component legend and notes.

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Designs software architecture and selects appropriate patterns for projects. Use when designing systems, choosing architecture patterns, structuring projects, making technical decisions, or when asked about microservices, monoliths, or architectural approaches.

日本語の概要は準備中です。原文の説明を表示しています。

Help users design and execute a modern SEO strategy that balances technical site health with programmatic content scaling and AI-driven discovery.

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Help users accelerate their product development cycles by implementing high-intensity rituals, ruthless scoping, and technical guardrails that allow teams to ship faster without sacrificing quality.

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Help users build a sustainable engineering culture by measuring health through frameworks like Core 4, managing technical debt as leverage, and optimizing workflows with AI tools.

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Help users navigate complex product decisions by weighing competing priorities and calculating long-term value. This skill covers build-vs-buy logic, technical debt evaluation, and communicating tradeoffs to senior leadership.

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Use when receiving code review feedback before implementing suggestions, especially when feedback is unclear, risky, disputed, or technically questionable.

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Restructure existing code while preserving observable behavior. Use for targeted technical debt or hotspot work with characterization tests.

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Explain a technical spec or proposed change in plain language: what problem it solves, how the solution works, and every schema change.

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Audits a website codebase and makes code changes so AI engines (ChatGPT, Claude, Perplexity, Google AI Overviews) can better discover, parse, quote, and cite the site. Covers structured data, content structure, technical signals, and freshness.

日本語の概要は準備中です。原文の説明を表示しています。