「allocation」の検索結果

AI กลยุทธ์ Ads — Google Ads, Meta (Facebook/IG), TikTok Ads — campaign structure, audience, creative brief, budget allocation, bid strategy สำหรับตลาดไทย

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Generates performance-focused guidance for Google Cloud workloads based on the design principles and recommendations in the Performance Optimization pillar of the Google Cloud Well-Architected Framework (WAF). Use this skill to evaluate a workload, identify performance requirements, and provide actionable recommendations for resource allocation, modular design, and elasticity.

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Use when writing, reviewing, or deploying Solidity smart contracts — token contracts, signature-gated claim systems, merkle-gated staking vaults, allocation modules, role-based proxies, or factory patterns. Triggers on edits to `*.sol` files, `hardhat.config.*`, `foundry.toml`, deploy scripts, or mentions of "smart contract", "Solidity", "Web3", "EVM", "Hardhat", "Foundry", "ERC20/721/1155", "merkle", "staking", or "on-chain". For security audits and adversarial review see security-engineering.

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Paid acquisition strategy, budget allocation, and avoiding common advertising mistakes across platforms

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Drafts Brownfields Agreements for contaminated-property transactions under CERCLA, EPA brownfields programs, and state voluntary cleanup programs. Structures BFPP liability protections, All Appropriate Inquiries documentation, remediation obligations, institutional controls, cost allocation, and long-term stewardship covenants. Use when drafting brownfields purchase agreements, prospective purchaser agreements, voluntary cleanup MOAs, or environmental covenant frameworks.

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Drafts a U.S. CRE personal property Bill of Sale transferring equipment, fixtures, FF&E, inventory, and other tangible assets. Handles inclusion/exclusion schedules, price allocation, tax responsibility, and risk of loss. Trigger when the user needs a bill of sale, asset schedule, equipment transfer document, or personal property conveyance tied to a CRE closing.

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Drafts a U.S. ocean Bill of Lading (B/L) functioning as receipt, contract of carriage, and document of title under COGSA or Hague-Visby. Covers negotiable and straight B/Ls, cargo description, freight allocation, and core carriage clauses. Use when drafting or reviewing a bill of lading, master/house B/L, ocean shipment documentation, or title transfer. Trigger keywords: bill of lading, B/L, ocean carriage, COGSA, Hague-Visby, negotiable, straight, master bill, house bill.

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Drafts a U.S. Asset Purchase Agreement for deals where a buyer acquires specified business assets while avoiding unwanted liabilities. Enforces itemized asset/liability schedules, purchase price mechanics with working capital true-ups, IRS Form 8594 tax allocation, seller and buyer reps and warranties with disclosure schedules, pre- and post-closing covenants, closing conditions and deliveries, and indemnification with basket/cap limits. Use when drafting an asset purchase agreement, APA, asset acquisition, purchase and sale of assets, asset deal, or excluded liabilities agreement.

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Generates structured U.S. aviation-law summaries by synthesizing FAA, DOT, and TSA rules, treaties, and precedent into actionable legal analysis. Use when briefing on air traffic rights, aircraft operations, airworthiness, carrier liability, or incident/compliance exposure. Trigger: aviation law, FAA, DOT, TSA, 14 CFR, Part 121/125/135, Montreal Convention, Warsaw Convention, ICAO, route authority, code-sharing, slot allocation, accident liability.

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Drafts a mathematically balanced ALTA Settlement Statement for U.S. real estate closings, allocating debits and credits between buyer and seller with prorations, payoffs, lender fees, title charges, and transfer taxes. Enforces balance verification (seller credits minus debits equals cash to seller; buyer debits minus credits equals cash from buyer) and cross-references title commitment, loan documents, and purchase agreement. Use when preparing closing financials, settlement statements, HUD-equivalent documents, or real estate closing allocations.

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Template for pre-reasoning → action → post-verification model allocation

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Implement randomization methods for RCTs. Use when user mentions: random assignment, treatment allocation, stratification, blocking, permutation randomization, cluster randomization, randomization balance, misfit handling, re-randomization.

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Estimates the minimum biological replicates (or cells/events) for a target power at a target FDR in genomics experiments using ssizeRNA, PROPER, powsimR for scRNA-seq, and pilot-data dispersion estimation from DESeq2/edgeR. Covers the biological-versus-technical replication distinction (technical replicates do not add degrees of freedom for biological inference), replicate-number-versus-sequencing-depth budgeting, scRNA-seq sample-versus-cell allocation under a pseudobulk model, and the critique that "n=3" is a publication convention rather than a power calculation. Use when budgeting a sequencing experiment, writing the sample-size justification in a grant, estimating replicates from pilot data, allocating a fixed budget between samples and depth, or planning scRNA-seq cohort size. For clinical-trial sample size see clinical-biostatistics/power-and-sample-size; for the power-given-n direction see experimental-design/power-analysis.

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Expert guide for Backend.AI distributed computing platform. Automatically activates when users ask about: - Backend.AI architecture, components (Manager, Agent, Storage Proxy, Webserver, App Proxy) - Features (session scheduling, Sokovan orchestrator, multi-tenancy, resource allocation) - APIs (REST, GraphQL), authentication, RBAC authorization - Container runtime (kernels, jail sandbox, hook library, virtual folders) - Accelerator support (CUDA, ROCm, TPU, NPU, Graphcore IPU) - Client SDKs (Python, Java, JavaScript, PHP) - Setup, requirements (Python 3.13+, Docker, PostgreSQL, Redis, etcd) - How WebUI connects to/interacts with Backend.AI backend - Plugin interfaces, development setup, infrastructure Use when user mentions "Backend.AI", "backend.ai", "Sokovan", component names, or asks about the backend platform this WebUI connects to. allowed-tools: WebFetch, Read

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Calculate the Maryland Aggregate Pathology Index (MAPI) on a deceased donor procurement kidney biopsy to predict graft survival and decide single vs dual vs discard allocation. Trigger when a clinician asks "what's the MAPI score", "interpret donor kidney biopsy", "should I use this marginal kidney", "MAPI cutoff for transplant", "procurement biopsy scoring", or has histology results from a deceased donor kidney and needs an objective grading.

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An infographic skill for AI agents — works inside Claude Code, Codex, Hermes, OpenClaw, Cursor, and any agent host that loads skills. Create professional infographics as self-contained HTML files with PNG exports. Use when the user asks to create, design, generate, build, or make an infographic, data visualization, visual explainer, chart poster, cheatsheet, or pocket guide. Trigger phrases include "make this visual", "turn this into a graphic", "visualize this data", "infographic for X", "cheatsheet for X", or when the user provides structured data (tokenomics allocations, ecosystem/partner lists, timelines, comparisons, step-by-step processes) AND asks for a visual output. Covers tokenomics, ecosystem overviews, game overviews, cheatsheets, airdrop guides, comparisons, and process flows. Do NOT trigger for plain text answers, markdown tables, bulleted summaries, questions asking for advice or explanations about a topic (even when the topic is tokenomics, ecosystem, vesting, etc.), inline chat diagrams, or data processing with no visual output requested. The signal is "asks for a visual", not "mentions a keyword".

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Use when CPU usage is high, memory grows unboundedly, goroutines leak, mutex contention shows in traces, or escape analysis suggests excess heap allocation. Triggers: net/http/pprof endpoint exposure, go tool pprof analysis, flamegraph generation, allocs vs inuse_space heap profiles, runtime/trace event timeline, mutex profiling, block profiling, goroutine dumps, GC pressure measurement. NOT for non-Go languages, distributed tracing (use OpenTelemetry skill), or production telemetry pipelines.

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Detect and analyze heap spray attacks in memory dumps using Volatility3 plugins to identify NOP sled patterns, shellcode landing zones, and suspicious large allocations in process virtual address space.

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Configure and distribute creator fees to multiple shareholders using the PumpFees program with BPS-based share allocation, admin management, and cross-program fee consolidation for graduated tokens.

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Comprehensive, measurement-driven performance optimization for latency, throughput, memory/GC, and tail behavior. Use when the user asks to optimize/speed up, reduce latency (p95/p99), increase throughput/QPS, lower CPU/memory/allocations/GC pauses, profile hot paths, or run a benchmarked perf pass (including JSONL/query-heavy code). Requires before/after measurement on a runnable workload (or an explicit `UNMEASURED` plan) plus a correctness gate.

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Knowledge base from the FAA Human Factors Design Standard (HF-STD-001B, 2016) — the FAA's consolidated human-factors / human-systems-integration design criteria for systems it manages, operates, or maintains. Use for requirement-level design rules on: general human-factors design principles; automation and function allocation; designing equipment for maintenance; displays, controls, and visual indicators; alarms, audio, and voice communications; the computer-human interface (information presentation, coding, interaction styles, windows, dialogue); keyboards, input devices, and workstation/workplace ergonomics; system security, personnel safety, environment, anthropometry, and user documentation; plus intended-use and tailoring guidance. It is a quantified, source-attributed synthesis (heavily citing MIL-STD-1472G, MIL-HDBK-759C, DOD-HFDG-ATCCS, NUREG-0700, NASA-STD-3000, ANSI, OSHA, ISO 9241). Complements nasa-hsi as a parallel HSI tradition from the civil-aviation domain. Scope limits: it is design criteria, NOT an HSI lifecycle/process model (use nasa-hsi, nasa-npr-7123, or dau-se-guidebook for process); it does NOT reproduce the third-party standards it cites; it is FAA-acquisition-oriented (ATC, towers, TRACONs, airway facilities), not a general consumer-UX guide; and it is thin on modern touchscreen/mobile, web, and AI-driven interface patterns and on quantitative human-reliability analysis.

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Knowledge base from the FAA Requirements Engineering Management Handbook (DOT/FAA/AR-08/32). Use for writing requirements for real-time, embedded control systems — the avionics/medical slant — via the Handbook's eleven recommended practices: system overview and boundary (monitored/controlled variables), operational concepts (use cases), environmental assumptions, change-tolerant functional architecture (dependency diagrams), safety-driven architecture revision (FHA/PSSA/fault tree), system modes, detailed behavior and performance requirements (ideal value + tolerance + latency), the four-variable model bridge to software requirements (MON/CON/NAT/REQ, IN'/REQ'/OUT', DO-178B mapping), subsystem allocation, and rationale. Carries the Isolette Thermostat and Flight Control System worked examples. Slanted toward control systems with sensors and actuators; thin on information-system / enterprise / agile requirements, on requirements-management tooling, and on the formal-methods internals of SCR/RSML/SpecTRM (it names them, does not re-teach them). Does not reproduce the IEEE/DO-178B/ARP standards it cites.

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Knowledge base from MIL-HDBK-338B (Electronic Reliability Design Handbook). Use for electronic reliability engineering: R/M/A theory, reliability specification/allocation/prediction, parts management and derating, reliable circuit and fault-tolerant design, environmental and human performance reliability, FMEA/FMECA/FTA/sneak circuit analysis, design reviews and testability, FRACAS, reliability demonstration and growth testing, and systems-level R&M parameters. Covers selected Part 2 design-guidance topics only; skips large annex/part-stress tables. Guidance handbook — not a contractual requirement text. Does not replace MIL-HDBK-217 prediction libraries, service-specific reliability regs, or safety standards (see mil-std-882).

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Knowledge base from NASA Human Systems Integration (HSI) Practitioner's Guide (NASA/SP-2015-3709). Use for HSI process implementation, lifecycle phase activities, function allocation, ConOps development, HSI Plan writing, HSI metrics (MOE/MOP/TPM/KPP), HITL testing strategy, HSI team organisation, scaling/tailoring for program size, and V&V planning. Does not cover the specific human engineering design standards (NASA-STD-3001 content) or detailed HFE methods beyond what the guide itself provides.

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。