「mov」の検索結果

Generates an Apple-compliant account deletion flow with multi-step confirmation UI, optional data export, configurable grace period, Keychain cleanup, and server-side deletion request. Use when user needs account deletion, right-to-delete, or Apple App Review compliance for account removal.

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The sva package contains functions for removing batch effects and other unwanted variation in high-throughput experiment. Specifically, the sva package contains functions for the identifying and building surrogate variables for high-dimensi

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An implementation, which takes input data and makes it available for proper batch effect removal by ComBat or Limma. The implementation appropriately handles missing values by dissecting the input matrix into smaller matrices with sufficient data to feed the ComBat or limma algorithm. The adjusted data is returned to the user as a rebuild matrix. The implementation is meant to make as much data available as possible with minimal data loss.

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Dino normalizes single-cell, mRNA sequencing data to correct for technical variation, particularly sequencing depth, prior to downstream analysis. The approach produces a matrix of corrected expression for which the dependency between sequencing depth and the full distribution of normalized expression; many existing methods aim to remove only the dependency between sequencing depth and the mean of the normalized expression. This is particuarly useful in the context of highly sparse datasets such

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Remove signs of AI-generated writing from text. Use when editing or reviewing text to make it sound more natural and human-written. Based on Wikipedia's comprehensive "Signs of AI writing" guide. Detects and fixes patterns including: inflated symbolism, promotional language, superficial -ing analyses, vague attributions, em dash overuse, rule of three, AI vocabulary words, negative parallelisms, and excessive conjunctive phrases.

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Expert knowledge for Azure AI Vision development including decision making, limits & quotas, configuration, integrations & coding patterns, and deployment. Use when using Image Analysis, Read OCR containers, smart-crop thumbnails, background removal, or video frame analysis, and other Azure AI Vision related development tasks. Not for Azure AI Custom Vision (use azure-custom-vision), Azure AI Video Indexer (use azure-video-indexer), Azure AI Document Intelligence (use azure-document-intelligence), Azure AI Immersive Reader (use azure-immersive-reader).

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Decode any Base transaction into a plain-English story - method, token movements, swaps/approvals, counterparties, and suspicious-approval flags. Keyless via Base RPC + Etherscan v2.

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Price and volume tracker for [REPLACE: TOKEN_SYMBOL] with anomaly alerts above [REPLACE: ALERT_THRESHOLD_PCT]% movement

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Fire when the tracked token does something - new ATH, sharp 1h move, or operator-set target crossed. Silent on normal days.

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Monitor Polymarket and/or Kalshi prediction markets for 24h price moves, volume changes, fresh comments, and high-conviction alerts

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One-pass crypto read - tracked-protocol positions and health plus macro context, with regime take, DeFi verdict, biggest movers, yields, fees, breadth, Fear & Greed, and prediction markets.

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Watch a list of competitor web pages on a cadence - snapshots each page's real signals (pricing, headings, CTAs, new/removed pages, title/description), diffs against the last run, and reports only what actually changed.

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Ambient fleet-health check that surfaces anything worth attention (default), or an on-demand priority brief - the 3 things to focus on, why now, and what moved (var=brief)

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Multichain non-custodial agent wallet via Finance District - check balances, prices, and best DeFi yields, move funds, swap, and make x402 paid API calls across EVM, Solana, Bitcoin, and Sui. Keys never leave a secure enclave (TEE); spend caps are enforced at the wallet. OAuth Connect via the dashboard MCP panel.

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Build prospect lists where the prospect is already one hop from the client, and write the line that says so. Seven members, each with its own source. Current-customer alumni is the priority member - everyone who ever worked at one of the client's customers or case-study companies and has since moved on. Triggers on "warm intro", "who do we know at that account", "they used to work at our customer", "alumni of our case study company", "shared investor angle", "who is in the same city as our rep", "did they visit our site". Outputs warm_intro_line plus a per-member evidence column.

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Trending products and rising categories discovery for Amazon sellers. Analyzes Best Seller Rank patterns, seasonal trends, new release momentum, and emerging niches. Identifies product opportunities before they peak. Use when the user asks about what's trending on Amazon, hot products, rising categories, seasonal opportunities, viral products, what to sell next, emerging niches, or early-mover opportunities. Also trigger for questions like 'what should I sell now?', 'what products are doing well?', 'find me trending niches', or 'what's hot on Amazon?'.

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Amazon FBA and FBM shipping cost calculator and fulfillment optimization. Dimensional weight analysis, storage fee calculation, removal cost estimation, and fulfillment method comparison. Use when the user asks about Amazon shipping costs, FBA fees, fulfillment costs, storage fees, or shipping calculations.

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Amazon keyword position monitoring and SERP analysis. Real-time position tracking, competitor movement alerts, search result changes, and keyword performance optimization. Use when the user asks about keyword monitoring, SERP tracking, position alerts, or search performance analysis.

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Remove vague, corporate, or AI-sounding language and replace it with clear, specific, human wording. Trigger on "improve copy", "sounds generic", "too fluffy".

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Decide whether to add, keep, or remove a dependency. Use before adding any package.

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Find and remove unreachable/unused code safely. Use during cleanup or before a refactor.

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Systematically remove one harness component at a time and measure impact, killing scaffolding that no longer earns its complexity.

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Applies Geoffrey Moore's chasm-crossing strategy for B2B tech products moving from visionary early adopters to pragmatist mainstream. Use when a product has early traction but stalls before mainstream adoption, when planning a beachhead/niche strategy, when designing whole-product offerings, when positioning against established competitors, or when scaling from innovator usage to industry standard. Triggers include 'stuck between early adopters and mainstream', 'we need a beachhead', 'pragmatist customers won't buy', 'how do we go from 10 to 1000 customers'. NOT for PLG/freemium SaaS (Slack, Notion, Cursor), pure consumer apps, two-sided marketplaces, or AI-native products with bottoms-up viral adoption - their dynamics break the visionary-to-pragmatist sequence.

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Use when the user wants to generate a cinematic still image on Higgsfield, asks about shot framing, camera angle, or composition for image prompts, needs a specific shot type (close-up, wide shot, cowboy shot, etc.), or is working with [img] reference-based image generation. Covers distance & size shots, camera angles, and camera movement keywords optimized for AI image models (Soul 2.0, Nano Banana, Seedream, GPT Image, Flux, etc.).

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