「time」の検索結果

Azure AI Transcription SDK for Python. Use for real-time and batch speech-to-text transcription with timestamps and diarization.

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Conduct multi-round deep research on any GitHub Repo. Use when users request comprehensive analysis, timeline reconstruction, competitive analysis, or in-depth investigation of GitHub. Produces structured markdown reports with executive summaries, chronological timelines, metrics analysis, and Mermaid diagrams. Triggers on Github repository URL or open source 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。

Develop Openrind Shell's OpenShell-supervised PostgreSQL FUSE runtime, compatibility sync runtime, and just-bash library.

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Analyze meeting transcripts, recordings, and notes to extract action items, key decisions, topics, sentiment, and generate summaries using NLP and AI. Use when processing meeting transcripts, extracting action items, summarizing discussions, identifying key decisions, tracking topics and themes, analyzing sentiment, generating meeting notes, or building collaboration and productivity tools.

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Build real-time, reactive backend applications with Convex using TypeScript queries, mutations, and actions with automatic reactivity and optimistic updates. Use when building real-time collaborative applications, implementing reactive data synchronization, writing serverless backend functions, creating queries that auto-update, implementing mutations with transactional guarantees, handling file uploads with Convex storage, implementing authentication with Convex Auth, designing reactive database schemas, or building applications requiring instant data synchronization.

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When the user wants to optimize post-signup onboarding, user activation, first-run experience, or time-to-value. Also use when the user mentions "onboarding flow," "activation rate," "user activation," "first-run experience," "empty states," "onboarding checklist," "aha moment," "new user experience," "users aren't activating," "nobody completes setup," "low activation rate," "users sign up but don't use the product," "time to value," or "first session experience." Use this whenever users are signing up but not sticking around. For signup/registration optimization, see signup-flow-cro. For ongoing email sequences, see email-sequence.

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Investigate and triage runtime incidents involving the Adobe Dispatcher Apache HTTP Server module and related HTTPD configuration in AEM as a Cloud Service environments only, using runtime-backed MCP evidence.

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UI 預覽評審 SKILL — 截取 Cocos Editor Preview 畫面，與 proof draft 提供的參考圖逐 zone 比對，輸出視覺信心分數與 PASS/FAIL 評審報告，並回寫 runtime-verdict。USE FOR: ui-asset-qc 通過後，需要人工確認 + 自動評審的最終視覺驗收。DO NOT USE FOR: Runtime 崩潰（用 cocos-log-reader）、Browser QA 截圖（用 cocos-preview-qa）、資產規格問題（用 ui-asset-qc）。

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DEBUGGING SKILL — Read and analyze Cocos Creator project.log for runtime errors, warnings, and stack traces. USE FOR: any bug report, crash, UI glitch, TypeError, null reference, missing asset, CompositePanel mount fail, ChildPanel route fail, or screen spec wiring error. Load this skill FIRST before any runtime debugging session. DO NOT USE FOR: compile errors (use get_errors tool instead).

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UI 資產切件與候選收斂 SKILL — 從使用者提供的整頁 UI、2K 母圖、panel sheet 或單張素材，自動執行全切、auto-classify、auto-pick、temp/selected 分流、背景裁切、透明化與 post-process。USE FOR: 切出 panel / cap / badge / glyph / noise 候選、把未挑選切片集中到 temp 可一次清掃、把高信心候選升到 selected、再接 trim-png-by-background.js / postprocess-ui-asset.js。DO NOT USE FOR: runtime 畫面驗收（用 ui-runtime-verify）、純 icon 規格設計（用 UI-icon workflow）、單純修改 layout/skin JSON。

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Improve agent reliability over time — diagnose why agents fail and fix the setup. Triggers on: agent keeps failing, same mistake again, agent not improving, make agent smarter, agent quality plateau, agents ignore skills, agent skips tests, fix agent behavior, agent unreliable, improve agent setup, self-improving harness, agents worse over time, tune agent instructions, agent going in circles, agent ignores AGENTS.md, repeated agent errors. Requires harness v0 and eval harness. AUTO-ROUTED from harness-engineering on symptoms. Not first setup — harness-generation first.

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Measure, profile, and fix performance bottlenecks — Core Web Vitals, backend latency, bundle size, and database queries. Load when performance requirements exist, users report slowness, profiling reveals bottlenecks, or the user asks to optimize load time, LCP, INP, CLS, or response time. Not for premature optimization without evidence. Pairs with browser-testing-with-devtools and ci-cd-and-automation for regression guards.

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Build GSAP JavaScript animations for web apps — timelines, scroll-driven motion, SVG draw/morph/path effects, and React integration with useGSAP. Load when the user asks to animate with GSAP, add ScrollTrigger, draw SVG paths with GSAP, morph SVG shapes, sequence page animations, or wire GSAP in React/Next/Vue. Also triggers on "GSAP timeline", "DrawSVG", "MotionPath", "gsap.context", or "scroll animation library". Not for self-contained README/GitHub SVG files.

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WebSocket and Socket.io integration for real-time communication in Flutter

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Automate Desktime tasks via Rube MCP (Composio). Always search tools first for current schemas.

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Automate time tracking workflows in Clockify -- create and manage time entries, workspaces, and users through natural language commands.

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。

Conduct multi-round deep research on any GitHub Repo. Use when users request comprehensive analysis, timeline reconstruction, competitive analysis, or in-depth investigation of GitHub. Produces structured markdown reports with executive summaries, chronological timelines, metrics analysis, and Mermaid diagrams. Triggers on Github repository URL or open source 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。

Azure AI Transcription SDK for Python. Use for real-time and batch speech-to-text transcription with timestamps and diarization.

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。

Assigns pathogen lineages (SARS-CoV-2 Pangolin via UShER mode; Nextclade clade + QC; pango-designation alias_key.json resolution) and tracks variant frequencies over time using Nextstrain (Augur + Auspice), wastewater deconvolution (Freyja, COJAC, alcov, lineagespot), lineage fitness modelling (Wenseleers / Bedford-Figgins multinomial logistic), and recombinant detection (3SEQ, RDP4, Bolotie). Covers Pangolin pangolin-data version pinning (mandatory for reproducibility), Nextclade dataset versioning (lineage-defining mutations change with dataset), Freyja barcode forward-only date constraint, ARTIC primer scheme version churn (V3 / V4 / V4.1 / V5.3.2 / Midnight 1200) with documented dropout regions, recombinant X-prefix Pango designation lag, GISAID vs INSDC dual-deposition tensions, and the Karthikeyan 2022 wastewater early-detection signal with explicit reproducibility caveats. Use when assigning Pango lineages and Nextclade clades to viral consensus sequences, building Nextstrain Augur surveillance pipelines, deconvolving wastewater pooled samples into lineage frequencies with Freyja, tracking lineage frequencies and growth advantages over time, pinning pangolin-data / Nextclade dataset versions for reproducibility, handling ARTIC primer dropouts (V4.1 amplicons 64 / 76 / 88-90), or running variant surveillance for SARS-CoV-2 / influenza / Mpox / RSV / H5N1 / measles.

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Assesses genetic health of populations for conservation with Ne estimation across time horizons (LDNe NeEstimator V2 option-file API + SNeP physical-linkage correction; recent trajectory via GONE/GONE2; deep history via Stairway Plot 2 / dadi / fastsimcoal2 / PSMC), F-statistics, runs of homozygosity binned by length class to date inbreeding, genetic-load decomposition (Bertorelle 2022 realized vs masked), the modern 100/1000 Ne rule (Frankham 2014), Ne/Nc 2-6 orders of magnitude in marine fish (Hauser & Carvalho 2008), tree-sequence forward simulations (SLiM 4 + pyslim + tskit), and the Sukumaran-Knowles caveat against MSC methods for management-unit definition. Use when estimating Ne by time horizon, detecting inbreeding via F_ROH, decomposing genetic load, justifying conservation thresholds, distinguishing ESU/MU/DPS, configuring NeEstimator V2, or correcting LDNe physical linkage.

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Use this skill to explain to customers/sales prospects why FMCSA CSA scores are not available in real-time. Covers the SAFER refresh cycle and what 'real-time' actually means for CSA data.

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Designs, reconciles, and reviews an end-to-end Drydock program for safely staging agent runtimes: immutable worktree provenance, disposable VM containment, typed effect brokerage, global body accounting, resurrection, subscription-capacity economics, context compaction, operator control, evidence, and promotion. Use when several Drydock contracts must compose into one architecture, implementation hypertree, diagram set, or release plan. NOT for launching Port Daddy, running an untrusted subject, replacing focused containment/resurrection/capacity audits, or treating a design packet as runtime authority.

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Message queues, pub/sub, event sourcing with Kafka, RabbitMQ, Redis Streams. Activate on: event-driven, message queue, pub/sub, Kafka, RabbitMQ, event bus, async messaging, dead letter queue. NOT for: CQRS projections (use cqrs-event-sourcing-architect), real-time WebSocket (use websocket-realtime-expert), observability (use observability-apm-expert).

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Safe database migration manager for zero-downtime DDL changes and rollback plans. Activate on: database migration, schema change, DDL, rollback plan, zero-downtime migration, Prisma migrate, Drizzle kit, Flyway, column rename, table alter. NOT for: query optimization (use database-optimizer), ORM modeling (use data-pipeline-engineer), backup/restore (use devops-automator).

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。