4.4천건 · 관련도순
Design and implement a feature engineering pipeline for a ML problem. Use when asked to "engineer features for this model", "what features should we build", or "design feature transformations".
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Apply source-aware mechanical-engineering judgment to research, analysis, coding, writing, teaching, research identity, and release work. Use for thermal-fluid systems, heat transfer, fluid mechanics, thermodynamics, HVAC, energy systems, turbomachinery, piping, multiphase flow, experiments, correlations, CFD, reduced-order models, AI/ML, uncertainty, engineering datasets, literature reviews, citations, manuscripts, reviewer revisions, Overleaf packages, figures, proposals, research software, reproducibility, public releases, engineering teaching materials, or a research-project logo and visual identity.
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Use when a task needs the judgment of an Energy Engineer working on building and industrial energy efficiency — running an ASHRAE Level 1/2/3 energy audit, calculating envelope heat loss/gain with the degree-day method, comparing HVAC equipment on SEER/EER/IEER/COP rather than nameplate alone, designing an IPMVP measurement and verification (M&V) plan, or ranking energy conservation measures (ECMs) by savings-to-investment ratio for a capital plan. Distinct from a wind-energy-engineer or solar/PV engineer (own generation-asset design and yield) and from an electrical-engineer (owns utility-scale power delivery and protection) — this role owns the demand side: how much energy a building or process actually needs, and which retrofit reduces that number with numbers that hold up after the fact.
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Use when the user asks to query Volcengine CloudTrail audit logs, investigate login or resource operations, or manage CloudTrail trails and backfill delivery tasks. Trigger on 操作审计, 审计日志, CloudTrail, cloud_trail, trail, 跟踪, 历史补投, or backfill in a Volcengine context. Audit queries are read-only; trail and backfill mutations require an explicit preview and confirmation.
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使用 ve docs search/fetch 检索火山引擎官方文档并获取全文。Use when 用户咨询火山引擎产品的概念、用法、计费规则、部署步骤、最佳实践或服务条款，或提供 www.volcengine.com/docs/、docs.volcengine.com/docs/ 链接需要阅读正文时。
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Use when the user wants to transact on any Volcengine commercial product — purchase/provision it, ask what it costs, or unsubscribe from it. Covers three actions: buy (purchase, subscribe, provision, open, place an order; Chinese "开通 / 购买 / 下单 / 买 / 售卖 / 订购"), price (how much does it cost, quote, billing rules, estimated spend; Chinese "多少钱 / 价格 / 报价 / 费用 / 怎么收费 / 如何计费 / 预估费用"), and unsubscribe (cancel a subscription, refund a prepaid instance; Chinese "退订 / 退款 / 取消订阅"). Trigger even when the user does not mention "sale" but expresses a clear purchase, pricing, or cancellation intent toward a Volcengine product. Only handles these three transaction actions; anything outside them is out of scope.
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Presentation/Core/Engine split control plane — the canonical entry point for any work decomposing the Yuzu server into three binaries (presentation · core · engine) per ADR-0031-presentation-core-engine-decomposition / ADR-0032 (the admission interlock) / ADR-0033 (access-control spine). Use when the user says "/split", "/pce-split", "/decomposition", asks to plan or implement a split workstream (WS-A*, WS-B*, WS-X*), asks "what's our gap to the presentation/core split" or "is it safe to extract presentation/the engine yet", asks to audit split readiness, or starts work touching the seam (handlers calling stores directly, the INV-31-4 contract test, the Drogon port, `server/presentation` or `server/engine`, the `uce` DB grants, component service identity, or the ADR-0032 admission/grant/audit substrate — `use_case_run_id`, the release log, the capability-declaration registry).
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Fix a specific bug or problem in a {{engine_name}} project. Supports two modes — immediate fix or plan-first. Without arguments executes existing .unikit/code/FIX_PLAN.md. Checks {{engine_name}} compilation, suggests test coverage, and creates self-improvement patches. Use when user says "fix bug", "debug this", "something is broken", "fix the tests", "fix the errors in the tests", "read the errors in the {{engine_name}} console logs and fix the problems", or pastes an error message or {{engine_name}} console log. Also trigger when user shares a NullReferenceException, MissingReferenceException, compilation error, or any {{engine_name}}-specific error.
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Patterns for vibe coding that produce production-quality output instead of garbage. Covers prompt engineering for AI coding, verification without reading every line, accept/reject/refine decision framework, architectural guardrails, context management (CLAUDE.md, .cursor/rules), TDD-driven vibe coding, screenshot-driven development, diff review discipline, and the anti-patterns that destroy quality. Activate on: "vibe coding", "AI coding quality", "Claude Code workflow", "AI-assisted development", "how to use AI for coding", "coding with AI", "agentic engineering workflow", "AI code quality", "vibe code without garbage", "production quality AI code", "CLAUDE.md setup", "cursorrules setup", "pre-commit hooks for AI", "TDD with AI", "test-driven vibe coding". NOT for: multi-person collaborative coding sessions (use cooperative-vibe-coding), building AI/LLM applications (use ai-engineer), prompt engineering for non-coding LLM use cases (use prompt-engineer).
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Introduce people to AI, agentic AI, and AI skills with appropriate pedagogy for any audience. Covers LLM analogies, progressive complexity paths, aha-moment demos, audience-tailored explanations, workshop design, and overcoming emotional barriers to AI adoption. Activate on 'explain AI', 'introduce AI', 'AI workshop', 'AI demo', 'teach AI', 'AI literacy', 'onboard to AI', 'AI evangelism', 'explain agentic', 'explain skills to', 'AI training session', 'AI onboarding'. NOT for teaching ML engineering (use ai-engineer), not for building AI features (use ai-engineer), not for prompt engineering (use prompt-engineer), not for building training data pipelines.
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Expert-level climate engineering covering carbon capture and storage, direct air capture, solar geoengineering, enhanced weathering, and carbon accounting.
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23 engineering agent skills and plugins for Claude Code, Codex, Gemini CLI, Cursor, OpenClaw, and 6 more tools. Architecture, frontend, backend, QA, DevOps, security, AI/ML, data engineering, Playwright, Stripe, AWS, MS365. 30+ Python tools (stdlib-only).
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Introduce people to AI, agentic AI, and AI skills with appropriate pedagogy for any audience. Covers LLM analogies, progressive complexity paths, aha-moment demos, audience-tailored explanations, workshop design, and overcoming emotional barriers to AI adoption. Activate on 'explain AI', 'introduce AI', 'AI workshop', 'AI demo', 'teach AI', 'AI literacy', 'onboard to AI', 'AI evangelism', 'explain agentic', 'explain skills to', 'AI training session', 'AI onboarding'. NOT for teaching ML engineering (use ai-engineer), not for building AI features (use ai-engineer), not for prompt engineering (use prompt-engineer), not for building training data pipelines.
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Agent fallback for CEngineServer_UnloadSpawnGroup (auto-generated, category: vfunc). Locate CEngineServer::UnloadSpawnGroup in the CS2 server module via IDA Pro MCP and emit a fresh, minimal-unique artifact. The deterministic preprocessor could not resolve this symbol on the current gamever - your job is the re-sign. Trigger: CEngineServer_UnloadSpawnGroup, CEngineServer::UnloadSpawnGroup
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개발 스킬의 첫 사용에 앞서 작업 관리 위치, 분류 라벨, 용어집과 설계 결정 기록의 위치를 확인합니다. 사용자 검토를 거쳐 저장소 공통 설정 문서를 정리합니다.
AI 에이전트가 맡는 개발의 완료 조건을 정하고 검증 가능한 작업으로 나눕니다. 구현 전후 평가를 비교하고 난도에 맞는 모델 선택과 비용·시간 기록을 정리합니다.
SearXNG로 여러 검색 엔진의 결과를 모으고 엔진, 분류, 기간으로 좁혀 제목과 링크, 짧은 발췌문을 얻습니다. 공개 인스턴스는 API 키 없이 사용합니다.
Git 변경 이력에서 개발 성과, 작업 시간대, 테스트 코드 비율과 변경이 집중된 파일을 분석하고 개인과 팀의 개선점 및 기간별 추이를 정리합니다.
OpenDesign 내부 구조를 예로 삼아 기술 발표용 HTML 슬라이드를 만듭니다. 구성, 근거 자료, 발표자 노트를 정리해 엔지니어 대상 설명 자료로 완성합니다.
기사와 보고서를 남녀 두 진행자의 자연스러운 대화로 바꾸고 음성 합성으로 팟캐스트를 만듭니다. 영어와 중국어를 지원하며 MP3와 대화 원고를 출력합니다.
Search software, data, and engineering jobs across countries through freehire.me. Filter by skills, seniority, location, posting age, and remote work, and retrieve full descriptions to assess opportunities or inspect a specific posting.
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Audit how a brand appears in AI search answers and identify improvements to its content and website access. Review citation patterns, clear answer structure, supporting evidence, and whether AI systems can retrieve key information.
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Plan AI application work across six areas: prompt evaluation, context allocation, retrieval-based answer generation, agent security, evaluation pipelines, and product strategy. This overview explains the approaches; the individual workflow packages, test cases, and CI templates are not included.
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Create incident response runbooks with ordered recovery steps, severity levels, escalation contacts, and status update templates. Help on-call engineers follow clear procedures during outages, verify recovery, and keep stakeholders informed.
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