「tor」の検索結果

Use when operating PAIDF Curation and Retrieval or NVIDIA Cosmos Curator pipelines (split, filter, caption, embed, dedup, shard, image annotate) or PAIDF Data Mining nearest-neighbor matching on Curator embeddings. Activate for Make or CLI pipeline config, GPU run preflight, FFmpeg sidecar, SAM3 keys, or Curator-to-TAO handoff. Do not use for generic ETL, vector-database RAG, model training, orchestration, or embeddings outside Cosmos Curator and PAIDF Data Mining.

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。

Use this skill when OpenStoryline is already installed and the user wants to start the local MCP/Web services, create or continue a session, send editing instructions, perform multi-turn re-editing, and verify rendered video outputs, as well as Chinese requests like “启动 OpenStoryline”, “把 OpenStoryline 跑起来”, “用 OpenStoryline 剪视频”.

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。

[omh] Workspace setup inventory and gaps: map repository, skill, prompt, plugin, MCP, hook, config, and runtime surfaces before strengthening or operating OMH. Use when the user says: workspace-audit, workspace audit, repo surface audit, repository surface audit, workspace surface audit, repo inventory, surface inventory, skill inventory.

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。

[omh] Releasing an iOS or Android app through the stores -- signing, the privacy manifest, a TestFlight or Play beta, a staged rollout, a hotfix: prepare each gate the store enforces, and plan the halt and the next build before the rollout starts, because a store release cannot be rolled back. Use when the user says: mobile-release, mobile release, mobile app release, ios release, android release, app store release, app store submission, submit to the app store.

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。

[omh] Release rollout needing health signals: release checklist, deploy decision, health signals, rollback gate, and post-deploy status. Use when the user says: deploy-and-monitor, deploy and monitor, deploy monitor, deployment monitoring, release monitor, post deploy, post-deploy, rollback.

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。

Azure Monitor OpenTelemetry Exporter for Python. Use for low-level OpenTelemetry export to Application Insights. Triggers: "azure-monitor-opentelemetry-exporter", "AzureMonitorTraceExporter", "AzureMonitorMetricExporter", "AzureMonitorLogExporter".

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。

Azure Monitor OpenTelemetry Exporter for Java. Export OpenTelemetry traces, metrics, and logs to Azure Monitor/Application Insights. Triggers: "AzureMonitorExporter java", "opentelemetry azure java", "application insights java otel", "azure monitor tracing java". Note: This package is DEPRECATED. Migrate to azure-monitor-opentelemetry-autoconfigure.

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。

Comprehensive market environment analysis and reporting tool. Analyzes global markets including US, European, Asian markets, forex, commodities, and economic indicators. Provides risk-on/risk-off assessment, sector analysis, and technical indicator interpretation. Triggers on keywords like market analysis, market environment, global markets, trading environment, market conditions, investment climate, market sentiment, forex analysis, stock market analysis, 相場環境, 市場分析, マーケット状況, 投資環境.

Use when the user asks to "audit our social presence" or "is this batch safe to publish"; runs either the typed ECHO asset gate or a separate program-maturity profile, with channel-truth, claim, disclosure, manipulation, UGC-rights, and denominator checks. Not for creator deliverables — use creator-content-auditor; not for launch readiness — use launch-readiness-auditor. 社媒资产门/运营成熟度/发布前放行

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。

Use when the user asks to "check if our surfaces have drifted from the canon", "watch for competitor repositioning", or "define when we should reposition"; produces a drift report — self-drift per flagship surface vs the narrative-registry canon over time (via wayback.py, change history Measured with as-of dates), competitor-repositioning alerts, an explicit repositioning-trigger condition set, and a D1/W1/M1 message-shift retro (intended vs actual pull-through, evidence-labeled) — feeding the TALE L drift-audit sub-items and the narrative-whiplash guardrail fact base. Not for the first-time consistency check before a surface ships — use narrative-cascade-planner; not for computing the TALE profile result or running the vetoes — use narrative-quality-auditor; not for echo-rate / AI-answer resonance measurement — use narrative-resonance-monitor. 自漂移监测/竞品重定位告警/重定位触发/叙事漂移复盘

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。

Activate when developers have latent caching needs: slow API responses, database read bottlenecks, DynamoDB throttling or cost, RDS/Aurora scaling pressure, Bedrock latency or cost, or adding a cache; activate when working with Redis, Valkey, Memcached, or any in-memory data store, cache-aside patterns, session stores, rate limiting, leaderboards, counters, streams, queues, pub/sub, distributed locks, feature flags, shopping carts, or other caching strategies. Activate for GenAI and ML retrieval: vector similarity search for low-latency retrieval, semantic caching, RAG, LLM response caching, embedding stores, AI agent memory, recommendation, personalization. Activate for ElastiCache lifecycle: provisioning (serverless or node-based), engine selection, CloudFormation/CDK/Terraform IaC, VPC connectivity, TLS, RBAC, IAM auth, Global Datastore, monitoring, troubleshooting, cost optimization, and migration from self-managed Redis. Do not trigger for browser caches, CDN/CloudFront, HTTP Cache-Control, CPU caches.

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。

Production readiness checklist for Apify Actor deployments. Use when deploying an Actor to production, preparing for launch, or validating Actor configuration, scheduling, monitoring, and rollback before going live. Trigger with "apify production", "deploy actor to prod", "apify go-live", "apify launch checklist", "actor production ready".

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。

Convert existing projects into Apify Actors - serverless cloud programs. Actorize JavaScript/TypeScript (SDK with Actor.init/exit), Python (async context manager), or any language (CLI wrapper). Use when migrating code to Apify, wrapping CLI tools as Actors, or adding Actor SDK to existing projects.

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。

Use when analyzing transcription factor (TF) regulatory networks using Dorothea database. Input gene list, identify regulating transcription factors, generate TF-Target network visualization. For: transcription factor enrichment analysis, gene regulatory network research.

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。

Japanese (and other non-Hollywood) screenwriting methods (日本编剧方法/原创剧本实战) — distilled from ten Japanese directors and writers in ゼロからの脚本術; Kosawa Ryota (three acts as 起承转合, speed by jumping), Uchida Kenji (beautiful structure, time-axis tricks), Miki Satoshi (small-material notebook, theme emerges later), Sono Sion, Omiya Ellie (dialogue from inner monologue), Kakei Masaya ("if + moreover"), Fukuda Yuichi (character = actor + flaw, audience as tsukkomi), Yokohama Satoko, Takahashi Izumi ("pain"), Yukisada Isao (situation-born originals); plus Arai Haruhiko (IP adaptation, "write what you're ashamed of"). Neighbours; sw-korean-french-screenwriting, ozu-screenplay-style. Use when writing an original Japanese-style script or TV drama, working from small material and fragments, choosing between structure-first and character-first methods, building a Japanese 企画書, designing comedy tsukkomi systems, or when Hollywood models feel wrong for a quiet, daily-life, non-goal-driven story.

Use when the user types /agentlas-storm, /agentlas storm, /hep-storm, or says @Hephaestus storm <goal> to drive a goal through the force-robust Stormbreaker loop with real Agentlas specialists.

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。

Persist player data in Roblox with DataStoreService: GetDataStore, GetAsync/ SetAsync/UpdateAsync/IncrementAsync wrapped in pcall, load-on-join and save-on-leave plus BindToClose, retries, and OrderedDataStore leaderboards. Use when saving or loading persistent data in a Roblox experience — when the user mentions DataStore, DataStoreService, GetAsync, SetAsync, UpdateAsync, save player data, or leaderboards. For general Luau scripting use roblox-luau.

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。

Analyze competitors and create competitive landscape documentation with feature matrices, positioning maps, and strategic recommendations. Use when asked to analyze competitors, create competitive analysis, compare features with competitors, build a competitive landscape, track competitive positioning, or prepare sales battlecard inputs. Produces structured competitor profiles, feature comparison matrix, win/loss analysis, and prioritised strategic recommendations. For a one-off teardown of a single rival use competitor-teardown; for a recurring market briefing use competitive-intelligence-monitor.

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。

Assemble a split-screen creator ad from a config — a two-zone vertical composite where a supplied AI-creator lip-sync take fills the BOTTOM ~48% while real 16:9 product/demo clips run uncropped in the TOP ~52%, each top clip contain-fit with a darkened blurred cover-scale fill of the same clip (never black bars), a 3px brand-color divider between the zones, the creator slice cover-fit per the per-scene VO timing, scenes hard-concatenated with the body audio being the concatenated creator VO slices, an end card held on the last sharp frame ~3s, then the ASSEMBLED cut transcribed with local Whisper (not the raw VO — concat drops inter-scene silence) and word-level captions burned in the chosen style. This is the FREE deterministic assembly + caption stage (two-zone composite + blurred fill + divider + hard-concat + end card + captions); the VO comes from create-vo-elevenlabs, the anchor from create-image-gpt-image-fal, and the whole-VO lip-sync from a paid VEED Fabric 1.0 take (a no-atom upstream input). Use for the split-screen-creator format.

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。

Detects A/B chromatin compartments from balanced Hi-C contact matrices via eigenvector decomposition of the distance-normalized, Pearson-correlated cis matrix with cooltools (eigs_cis), then orients (phases) the compartment eigenvector against a GC or gene-density track so the active (A) sign is not arbitrary. Covers the eigenvector-is-a-choice problem (per-arm view_df to remove the centromere gradient; picking the eigenvector by max correlation with activity, not by eigenvalue), GC phasing with bioframe.frac_gc, resolution choice (100kb-1Mb), saddle plots and saddle_strength for compartmentalization strength, the cohesin-loss-strengthens-compartments result, subcompartments (SNIPER/Calder/dcHiC), and cross-condition compartment switching. Use when calling A/B compartments, computing E1/eigenvectors, phasing the eigenvector, building saddle plots, choosing a compartment resolution, quantifying compartment strength, or comparing compartmentalization across conditions.

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。

Optimize App Store product pages for search visibility and conversion. Use for App Store Optimization (ASO), keyword research, app name/subtitle/keyword-field strategy, conversion-focused descriptions and promotional text, screenshot captions and ordering, Custom Product Pages with assigned search keywords, In-App Events, Product Page Optimization tests, localized metadata, ratings/review strategy, and in-app review prompt timing with RequestReviewAction or AppStore.requestReview. Also use when routing ASO vs App Store review, privacy/ATT, or StoreKit implementation boundaries.

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。

Spiral inductors, interdigital capacitors, baluns, resonators, phase shifters for impedance matching, DC blocking, and bias tees. TRIGGER: user asks to design or create a spiral inductor, interdigital capacitor, balun, resonator, phase shifter, or other passive RF component. Invoke BEFORE writing code — class names and property patterns are non-obvious. SKIP: filter design (use matlab-design-pcb-filter), coupler/splitter design (use matlab-design-pcb-coupler), transmission line design (use matlab-design-pcb-transmission-line), EM analysis (use matlab-analyze-em), material setup only (use matlab-manage-pcb-material).

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。

Build industrial-grade SCADA/HMI dashboards in MATLAB following industrial-HMI conventions (ISA-101-aligned): gray-field philosophy, alarms at source, write safeguards, fixed-range trends, drill-down layout. Produces a real App Designer app (.mlapp, or plain-text .m+.xml on R2026b+) by handing serialization to the matlab-build-app skill when available, and falls back to a programmatic .m app otherwise. Use when wrapping OPC UA / Modbus / MQTT / OSI PI / PI AF monitoring scripts into a live operator app, building plant overviews, designing operator dashboards, or any time a user asks for a "SCADA dashboard", "HMI", "plant dashboard", "operator screen", or "industrial monitoring app" in MATLAB. Trigger on: SCADA, HMI, industrial dashboard, plant overview, operator screen, uigauge, uilamp, alarm banner, gray-field, ISA-101, OPC UA dashboard, setpoint, write safeguards, alarm visualization, OSIsoft PI, AVEVA PI, PI Server, PI Data Archive, PI AF, PI Asset Framework, piclient, afclient.

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。

Guide users or agents to the correct MATLAB tool for processing large tabular data in file-based formats (CSV, Parquet, delimited text, spreadsheets, MDF) that may not fit in memory. Use when a user or agent mentions large files, big data, out-of-memory errors, OOM, scaling up, tall arrays, datastores, or needs to process multiple tabular files. Covers the decision between datastore + tall, datastore + transform, and parallel execution. Also use when a user or agent has working in-memory code (readtable, parquetread) that runs out of memory and needs a migration path. Also covers building custom datastore classes for proprietary or non-standard formats — use when the task requires subclassing matlab.io.Datastore, implementing a custom reader, building an extensible datastore, or integrating a new file format with tall arrays or parallel computing. Do NOT use for MAT files (use matfile instead).

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。