「tradeoff」の検索結果

Designs target system boundaries, contracts and tradeoffs from requirements; does not plan tasks or implement.

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Guide for drafting issue closure and decline responses as an open-source package maintainer. Use when helping compose a reply that says "no" to a feature request, closes an issue as won't-fix, redirects a user to a different package, explains why a design choice is intentional, or otherwise declines or closes a community contribution. Also use when the maintainer needs to explain a deprecation, point out a user misunderstanding, or communicate an effort/scope tradeoff to a contributor.

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Build or review gRPC services and clients in .NET. USE FOR: ASP.NET Core gRPC, protobuf contracts, unary or streaming RPC, gRPC client factory, interceptors, deadlines, cancellation, channel reuse, backend service integration. DO NOT USE FOR: broad browser-facing APIs without gRPC-Web tradeoff review, SignalR realtime hubs, plain REST APIs. INVOKES: dotnet build/test and focused service or client smoke checks when code changes.

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Use when Java design, refactoring, or implementation tradeoffs should be evaluated with Kent Beck's simple design rules, including passes the tests, reveals intention, has no duplication, and has the fewest elements. This should trigger for requests such as Apply simple design rules; Review this design with Beck's rules; Choose between these refactoring options; Keep this Java design simple. Part of Plinth Toolkit

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Adds and tunes a reranker stage for RAG using the retrieve-wide, rerank-narrow pattern. Use when relevant documents appear in the initial top-N but are buried by noise, top-1 precision or MRR is low despite adequate recall, or too many marginal chunks consume context. Covers cross-encoder, API, and local rerankers; N-to-k selection; and latency/cost tradeoffs. Do not use when retrieval recall itself is failing.

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Decision SOP for serving LLMs with vLLM. Covers PagedAttention mental model, quantization/parallelism/batching tradeoffs, OOM triage, and when NOT to use vLLM. Activates when a coder-agent is choosing or tuning an inference engine, debugging vLLM throughput/latency/OOM, or comparing vLLM against TGI/SGLang/TensorRT-LLM/llama.cpp.

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Compress construction schedules using crashing and fast-tracking techniques. Analyze cost-time tradeoffs and find optimal acceleration strategies.

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Research and advise on the best way to approach a software project, including architecture, tech stack, implementation strategy, pricing/operating-cost tradeoffs, benchmark research, and comparisons with similar real-world projects. Use before building, mid-build, or after completion when the user asks for project strategy, optimal approach, research comparables, similar projects, stack selection, vendor/service choice, repo analysis, architecture critique, implementation feedback, or a prioritized improvement plan. Avoid for narrow single-bug debugging or isolated file edits unless the user asks for broader project direction.

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Evaluates and implements age estimation and verification technologies for online services. Covers facial age estimation, digital ID verification, self-declaration with risk assessment, AI-based age estimation, and the accuracy versus privacy tradeoff. Includes ICO guidance and euCONSENT framework. Keywords: age verification, age estimation, facial analysis, digital ID, children, online safety.

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Create Chinese monospaced compass-style PDCA or CAPD problem-solving cards using East-West-South-North-Center layout, full-width and half-width spaces, diagonal Unicode arrows, and strict Chinese character limits. Use when Codex needs to turn a problem, incident, decision tradeoff, root-cause analysis, improvement cycle, or CAPD/PDCA workflow into a square text diagram, Hermes/Discord-ready card, or Chinese 方位九宮圖 with center ◎, north Plan, east Do, south Check, west Action, and four diagonal transition arrows.

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Think and work like an expert Knowledge Representation Researcher. Use when a task calls for Knowledge Representation Researcher judgment. Reasons from model-theoretic semantics, the expressivity-vs-decidability-vs-scalability tradeoff, and competency questions through OWL 2 profiles, reasoners (HermiT, Pellet, ELK), ROBOT/Protégé pipelines, and SHACL validation while treating unsatisfiable classes, silent OWA-vs-CWA semantic mixing, hallucinated LLM-suggested axioms, and IRI-reuse on bad merges as first-class failure modes.

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Think and work like an expert Cognitive Scientist. Use when a task calls for Cognitive Scientist judgment. Reasons from Marr's levels of analysis, latent processes behind RT and accuracy, and strong inference through PsychoPy paradigms, signal-detection d-prime/criterion, sequential-sampling and ACT-R models, and crossed mixed-effects designs while treating speed-accuracy tradeoffs, criterion shifts, item confounds, and underpowered WEIRD samples as first-class failure modes.

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Build and evaluate low-latency spoken, multimodal, and translation experiences with Google Gemini Live API and Gemini Enterprise Agent Platform Live API. Use when a media-production or voice-agent workflow needs real-time audio input/output, barge-in, voice configuration, live transcription, live translation, tool/function calling during a spoken session, WebSocket session design, latency QA, quotas/cost review, or Google/Vertex data-governance tradeoffs.

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Protocol for handling ambiguous decisions and missing/conflicting knowledge during code generation, design, and review. Ensures AI surfaces genuine judgment calls with structured options and stops on hallucination risk instead of silently assuming. Use when a decision has multiple valid approaches, when facts are missing or contradictory, when the user asks 'what should we do here?', 'is this a judgment call?', 'should I ask about this?', 'am I guessing here?', 'what are the tradeoffs?', or when deciding between two reasonable architectural or design options. Also composed by molecules to define how judgment calls and clarification requests are surfaced and resolved.

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Create evidence-aware, interactive visual explainers as self-contained offline HTML. Use when a user asks to explain a concept, repository module, engineering tradeoff, or incident with a diagram, walkthrough, ELI5 treatment, data/request trace, failure view, or teach-back. Do not use for a plain short answer, ordinary prose rewrite, generic website implementation, or unsupported claims presented as facts.

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PM skill for Claude Code, Codex, Cursor, and Windsurf. Diagnoses SaaS metrics, critiques PRDs, plans roadmaps, runs discovery, coaches PM career transitions, pressure-tests AI product decisions, and designs PLG growth strategies. Seven knowledge domains, 12 templates, 40+ frameworks, and an opinionated interaction style that labels assumptions and names tradeoffs.

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This skill should be used when the user asks about "technical decision", "what to use", "A vs B", "comparison analysis", "library selection", "architecture decision", "which one to use", "tradeoffs", "tech selection", "implementation approach", or needs deep analysis for technical decisions. Provides systematic multi-source research and synthesized recommendations.

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This skill should be used when the user says "/council", "council", "deliberate", "multi-perspective decision", "트레이드오프 분석", "위원회 소집", "여러 관점으로 검토", or wants deep multi-perspective deliberation with tradeoff mapping. Combines tribunal (structured adversarial review), agent-council (external LLM opinions), dev-scan (community sentiment), and step-back (meta-level review) into a unified decision-making committee. Uses Agent Teams for real peer-to-peer debate with iterative step-back moderation loop.

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Apply when product, UX, or feature-scope tradeoffs come up. Choose user delight over implementation convenience; ship fewer polished features over more rough ones.

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Expert in decision-making frameworks - systematic approaches to making better decisions under uncertainty. Covers decision criteria, reversibility assessment, stakeholder alignment, and decision documentation. Knows when to decide fast and when to deliberate. Use when "decision framework, how to decide, making a choice, tradeoff, should we, pros and cons, decision matrix, weighing options, " mentioned.

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Prioritize roadmap initiatives with tradeoffs. Use when a senior developer needs help ranking projects.

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Review code for quality, correctness, and fit. Use when the user wants judgment on code that already exists — their own changes, a teammate's patch, a PR, branch, commit, diff, staged changes, or one or more files to look over. Activate on requests like review, look over, sanity check, critique, code review, or 'is this good?' The key signal is that the user wants evaluation of existing code and its tradeoffs, not implementation, debugging, or explanation. This skill works independently, but when plans, specs, task artifacts, or prior discussion exist, use them to understand why the code exists before judging it.

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Answer questions about code, architecture, and technical decisions — no implementation. Trigger on questions asking 'why', 'what does this do', 'what is the purpose of', 'explain', 'what's the difference', 'compare', or 'what are the tradeoffs' — even when referencing specific files, code snippets, or inline code. The key signal is the user wants to UNDERSTAND something, not change it. Do NOT trigger for requests to build, fix, plan, review, research, or add/modify code.

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Chooses managed backend platforms such as Supabase, Convex, and Firebase. Use when comparing database, auth, realtime, and backend-service tradeoffs.

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