「demand」の検索結果

Evaluates new product opportunities through demand, channels and economics before committing to build.

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Diagnoses .NET Framework CLR activation issues using CLR activation logs (CLRLoad logs) produced by mscoree.dll. Use when: the shim picks the wrong runtime, fails to load any runtime, shows unexpected .NET 3.5 Feature-on-Demand (FOD) dialogs, unexpectedly does NOT show FOD dialogs, loads both v2 and v4 into the same process causing failures, or any time someone is wondering "what is happening with .NET Framework activation?"

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Upload video/audio media to BytePlus VOD (Video on Demand) storage, returning the Vid and playback references; supports both local file upload (ApplyUploadInfo + TOS + CommitUploadInfo) and URL pull upload (UploadMediaByUrl); also supports AI-based comprehensive quality restoration on already-uploaded videos (removing compression artifacts, noise, scratches, improving clarity, and configuring Pro-tier color depth). Trigger keywords: upload video, upload media, upload to VOD, URL upload, pull upload, local upload, file upload, UploadMediaByUrl, ApplyUploadInfo, media ingestion, quality restoration, quality enhancement, comprehensive restoration, video denoising, denoise, compression artifact removal, color depth, bit depth, 10-bit, 12-bit, 16-bit.

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Upload video/audio media to BytePlus VOD (Video on Demand) storage, returning the Vid and playback references; supports local file upload (ApplyUploadInfo + TOS + CommitUploadInfo) and URL pull upload (UploadMediaByUrl); also submits frame extraction jobs on ingested media (StartExecution / Operation.Task.Snapshot), including specified time, fixed interval, specified frame, scene-change, sprite image, and output index modes. Trigger keywords: VOD frame extraction, frame extraction, extract frames, video snapshot, thumbnail, screenshot from video, StartExecution Snapshot.

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Upload video/audio media to BytePlus VOD (Video on Demand) storage, returning the Vid and playback references; supports local file upload (ApplyUploadInfo + TOS + CommitUploadInfo) and URL pull upload (UploadMediaByUrl); also submits precision erasure jobs on ingested media (StartExecution / Operation.Task.Erase): Auto OCR only — default subtitle-only erasure, optional full on-screen text, optional EraseOption ClipFilter (skip/selected); NewVid is always true; optional WithEraseInfo. Trigger keywords: precision erasure, precise erase, VOD upload, subtitle removal, OCR subtitles, remove on-screen text, erase text, StartExecution Erase.

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Use MCP servers on-demand via the mcp CLI tool - discover tools, resources, and prompts without polluting context with pre-loaded MCP integrations

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The consumer panel. Spins up a swarm of buyer sub-agents (default 100, --quick for 20) trained on the user's target customer, each with a different income, age, buying behaviour and objection, shows every one the same pitch, and runs the business through 100 buyer scenarios to see who buys, who doesn't, and why. Tallies the answers into buy rates by segment, the reasons people pass in their own words, what would flip a no, and price answers for founder-pricing. Use when the user says "would people buy this", "test it on customers", "run the consumer panel", "simulate buyers", "who is my customer", or "validate demand".

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。

Analyzes Claude Code usage patterns and provides comprehensive recommendations. Runs usage analysis, discovers GitHub community resources, suggests CLAUDE.md improvements, and fetches latest docs on-demand. Use when user wants to optimize their Claude Code workflow, create configurations (agents/skills/commands), or set up project documentation.

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Query the ZINC22 virtual compound library (CartBlanche API, billions of make-on-demand + purchasable molecules). Look up substances by ZINC ID, resolve a SMILES to its ZINC ID (exact match), inspect purchasability/catalogs, and assemble compound sets for docking. Property (MW/logP) filtering is done locally with RDKit. For bioactivity use chembl-database-bioactivity; for approved drugs use drugbank-database-access.

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Provides AWS CloudFormation patterns for DynamoDB tables, GSIs, LSIs, auto-scaling, and streams. Use when creating DynamoDB tables with CloudFormation, configuring primary keys, local/global secondary indexes, capacity modes (on-demand/provisioned), point-in-time recovery, encryption, TTL, and implementing template structure with Parameters, Outputs, Mappings, Conditions, cross-stack references.

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Use the OpenConstructionERP validation engine: rule packs (BOQ quality, DIN 276, NRM, GAEB, MasterFormat, DPGF) that check estimates at import time and on demand. Use when verifying BOQ correctness or writing custom validation rules.

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Implements hub-and-spoke lazy loading to minimize token usage in large skills. Use when building multi-module skills that need conditional on-demand loading.

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Fact lookup: Apple Human Interface Guidelines corpus (greppable markdown). Query on demand for accessibility and ergonomic minimums (hit-target sizes, Dynamic Type), platform terminology, system component capabilities, and App-Review-relevant conventions. Not design direction.

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On-demand senior red-team lead advisor. Call at a decision point or obstacle to get wiki-grounded direction instead of hammering blindly. Dispatches a fresh RTL subagent that reads the engagement state + evidence + wiki and returns ranked directions with an explicit STOP. Use for "redteamlead", "RTL", "I'm stuck", "where do I go", "what next", "which vector", "should I keep hammering this".

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Use when implementing load additional content on user demand.

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Use when implementing show or hide additional text content on demand.

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Forecast inventory needs using demand analysis, safety stock calculations, reorder point optimization, and seasonal adjustment

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Think and work like an expert Human–Computer Interaction Researcher. Use when a task calls for Human–Computer Interaction Researcher judgment. Reasons from situated context, Fitts/GOMS/KLM, and CHI contribution types; runs contextual inquiry through LMM/CLMM analysis with SUS/NASA-TLX triangulation; uses Prolific/OSF and treats demand characteristics, novelty effects, ordinal misuse, and WEIRD samples as first-class failure modes.

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Think and work like an expert Energy Systems Engineer. Use when a task calls for Energy Systems Engineer judgment. Reasons from exergy, load duration curves, capacity factor, and grid boundary constraints through pinch analysis, hourly dispatch models (PLEXOS, HOMER Pro, SAM, PVsyst), spark-spread CHP screening, and IPMVP M&V while treating nameplate-vs-utilization confusion, average-vs-marginal grid emissions, unrealistic arbitrage spreads, and demand-charge ratchet resets as first-class failure modes.

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。

Think and work like an expert Developmental Psychologist. Use when a task calls for Developmental Psychologist judgment. Reasons from developmental trajectories, measurement invariance, and familial-environmental context through age-normed instruments (Bayley, WPPSI/WISC, CBCL, MacArthur-Bates CDI), false-belief and violation-of-expectation paradigms, and lme4/lavaan growth models while treating verbal-demand confounding of theory of mind, informative attrition, adult-normed task misapplication, and parent-versus-direct-assessment divergence as first-class failure modes.

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Think and work like an expert Cardiologist. Use when a task calls for Cardiologist judgment. Reasons from oxygen supply-demand mismatch, forward flow, filling pressures, and pre-test probability through 12-lead ECG, TTE/TEE with ASE grading, cath hemodynamics, CMR, and ACC/AHA/ESC guidelines with risk scores like HEART, GRACE, and CHA2DS2-VASc, while treating context-free troponin elevation, low-flow low-gradient AS discordance, undiagnosed wide-complex tachycardia, and premature diagnostic closure as first-class failure modes.

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Analyze hiring patterns, job market demand, salary signals, and talent competition across LinkedIn and Apollo. Covers job posting analysis, company hiring velocity, role requirement trends, and competitive talent landscape mapping.

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。

Generate content ideas backed by real audience demand data from Reddit questions, YouTube search gaps, Twitter discussions, and web search trends. Identifies proven topics, underserved questions, and content formats that outperform in your niche.

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Build evidence-backed SEO keyword insights and strategy using SandBase-managed search, keyword, site-analysis, and SERP capabilities. Use when asked to discover or prioritize keywords, assess search demand or ranking feasibility, map intent and topics, find competitor gaps, plan organic-search landing pages or content, or analyze a website's SEO opportunities.

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。