「tempo」の検索結果

Use when the user has finished building a mobile app, started Metro with `npm run dev`, and wants the running app monitored for runtime errors AND silent failures (empty lists, blank screens, swallowed network errors) and fixed autonomously. Accepts a free-text symptom (e.g., `/debug-app "todos not appearing on home screen"`) to drive persisted-log diagnostics — injects temporary console.log statements at data-path boundaries, reads the sanitized `.powernative/metro-logs/` log, and cleans up logs after the root cause is fixed. Supports port/platform filtering, configurable clean-cycle and timeout limits, and watch-only `--no-fix` mode. Otherwise polls with a durable byte cursor, fixes inline or routes appropriately, verifies each fix from new output, and exits after the configured clean checks (default 3). Foreground loop — blocks the conversation while running. Run only after the app is loaded.

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Generate a phased delivery orchestration plan for creative-direction-driven work: which skills run when, what locks at which gate, how handoffs occur, and how the cadence implements in the team's tools (Jira, Linear, Notion, Figma, GitHub) with AI agents via MCP and CLI. A temporal map of phases, lock points, handoff specs, gate definitions, and QA verification gates. Distinct from `creative-brief` (static project brief) and `creative-direction` (aesthetic direction). Triggers on integration orchestrator, delivery cadence, project orchestration, when does the brief lock, how to phase creative direction, design-development handoff, QA gate, agent-driven QA, and when a creative-direction project is starting, mid-flight with broken cadence, or integrating AI agents into PM workflow. Does NOT fire for project scoping (use `creative-brief`), aesthetic direction (use `creative-direction`), or general project management without a creative-direction throughline.

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Time series analysis and temporal pattern detection for scientific data

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Recherche, cartographie et analyse des thèses de doctorat françaises via theses.fr (API ABES) et TEL (HAL). Spécialisée droit avec filtrage par sous-disciplines juridiques. Ouverte sur d'autres domaines universitaires. Capacités : (1) recherche multi-critères — sujet, directeur, jury, établissement, école doctorale, période, statut soutenue/en préparation, discipline ; (2) cartographie académique — qui dirige sur quel sujet, qui siège dans quels jurys, réseaux de co-direction, écoles doctorales productives ; (3) analyses temporelles — évolution d'un sujet, détection de saturation, calendrier des soutenances à venir ; (4) filtrage sous-discipline juridique — droit privé, public, social, affaires, international, etc. Déclencher dès que l'utilisateur mentionne thèse, doctorat, directeur de thèse, jury de thèse, école doctorale, soutenance, doctorant, ou demande une analyse d'écosystème doctoral. Pour articles ou ouvrages de doctrine, utiliser plutôt recherche-doctrine.

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Argentine Supreme Court citation network analysis using JurisRank — a peer-reviewed PageRank algorithm with temporal decay for measuring jurisprudential authority. Ranks precedents by citation influence, traces doctrinal evolution, and detects constitutional drift. Published methodology: JCLLT (DOI: 10.47852/bonviewJCLLT62027951). Activate with: which cases to cite, rank precedents, case authority, doctrinal evolution, Argentine Supreme Court, CSJN jurisprudence, citation network, leading case, legal research Argentina.

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Archéologie des sources juridiques anciennes via Gallica (BNF, API stables, sans clé) : débats parlementaires du JO depuis 1871 (genèse des lois de la IIIe République), notes d'arrêt et doctrine d'origine dans les recueils Sirey et Dalloz, Bulletins civil et criminel anciens, Recueil Lebon, JO Lois et décrets 1881-2015, thèses et traités du XIXe-début XXe, Gazette des tribunaux, Bulletin de l'Inspection du travail. Déclencher dès que l'utilisateur cherche l'origine historique d'un texte, d'un concept ou d'une jurisprudence : « débats de la loi de 1884 », « note de Josserand », « que disait la doctrine en 1900 », « première apparition de la notion de… », « généalogie / histoire de l'article… », « arrêt ancien », « thèse d'avant-guerre », « Gallica », « BNF », ou toute recherche juridique antérieure aux bases modernes (Légifrance ne remonte pas avant l'époque contemporaine, Judilibre non plus). Déclencher aussi en COMPLÉMENT de travaux-preparatoires quand la loi étudiée est antérieure à 1958.

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Build students' capacity to place historical documents in their temporal and social context. Use when students read sources without considering what was happening at the time, or know the context but don't deploy it.

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Guidelines for creating temporary files in system temp directory. Use when agents need to create reports, logs, or progress files without cluttering the repository.

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Understand temporal meaning in context without performing calendar arithmetic.

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Step 3 of the PaperOrchestra pipeline (arXiv:2604.05018). Execute the literature search strategy from outline.json — discover candidate papers via web search, verify them through Semantic Scholar (Levenshtein > 70 fuzzy title match, temporal cutoff, dedup by paperId), cross-corroborate against Crossref + OpenAlex to flag hallucinated citations, build a BibTeX file, and draft Introduction + Related Work using ≥90% of the verified pool. Runs in parallel with the plotting-agent. TRIGGER when the orchestrator delegates Step 3 or when the user asks to "find citations for my paper", "draft the related work", or "build the bibliography".

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Detect and investigate bulk registration abuse on SaaS platforms. Given access to a user database (or exported CSV/JSON), run a multi-dimensional anomaly analysis — email domain clustering, registration tempo, UA fingerprinting, session structure, usage patterns, and credit consumption — to produce a scored abuse report with actionable recommendations. Use when investigating suspicious sign-up spikes, credit fraud, free-tier abuse, or account farming.

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Archives a completed feature to docs/evolution/, migrates lasting artifacts to permanent directories, and cleans up the temporary workspace. Use after all implementation steps pass and mutation testing completes.

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Write original rap lyrics with tempo, beat cues and performer parts. Use for this Bot Generator Bot template; creates drafts or simulations within its declared scope.

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Researches archives, contemporary accounts, and timeline reconstruction. Use when the album subject involves historical events that need primary source verification.

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Async communication patterns using message brokers and task queues. Use when building event-driven systems, background job processing, or service decoupling. Covers Kafka (event streaming), RabbitMQ (complex routing), NATS (cloud-native), Redis Streams, Celery (Python), BullMQ (TypeScript), Temporal (workflows), and event sourcing patterns.

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Monitoring, logging, and tracing implementation using OpenTelemetry as the unified standard. Use when building production systems requiring visibility into performance, errors, and behavior. Covers OpenTelemetry (metrics, logs, traces), Prometheus, Grafana, Loki, Jaeger, Tempo, structured logging (structlog, tracing, slog, pino), and alerting.

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Temporal pattern detection and forecasting. Use when analyzing trends over time, detecting seasonality, identifying anomalies in time series, or building simple forecasting models for planning.

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Delegate broad computer-use tasks to ARK CUA for Volcengine AgentPlan users through an authenticated cloud desktop, and synchronize explicit credentials to a caller-owned CUA through Credential Agent. Use for web or desktop-app operation, file workflows, reusable task contexts, artifacts, temporary CUA App URLs, desktop shutdown/start/recovery, inspection, or exact browser, environment, secret, Credential Set, and managed-file credential setup/sync/status/reset. Do not use when local reasoning or a purpose-built local/API tool can complete the request more directly.

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Use when designing, implementing, reviewing, testing, or cleaning up feature toggles, feature flags, kill switches, runtime configuration gates, canary controls, staged rollouts, experiments, or temporary compatibility switches in Java enterprise systems. This should trigger for requests such as Design a feature toggle strategy; Review this feature flag; Add a kill switch safely; Test toggle on and off paths; Clean up an expired feature toggle; Plan controlled rollout and rollback behavior. Part of Plinth Toolkit

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Review and fix temporal references in code comments.

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Implement distributed tracing with Jaeger and Tempo to track requests across microservices and identify performance bottlenecks. Use when debugging microservices, analyzing request flows, or implementing observability for distributed systems.

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Process and generate multimedia content using Google Gemini API. Capabilities include analyze audio files (transcription with timestamps, summarization, speech understanding, music/sound analysis up to 9.5 hours), understand images (captioning, object detection, OCR, visual Q&A, segmentation), process videos (scene detection, Q&A, temporal analysis, YouTube URLs, up to 6 hours), extract from documents (PDF tables, forms, charts, diagrams, multi-page), generate images (text-to-image, editing, composition, refinement). Use when working with audio/video files, analyzing images or screenshots, processing PDF documents, extracting structured data from media, creating images from text prompts, or implementing multimodal AI features. Supports multiple models (Gemini 2.5/2.0) with context windows up to 2M tokens.

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UMAP dimensionality reduction for visualization, clustering prep, and feature engineering. Fast nonlinear manifold learning preserving local and global structure. Standard UMAP (fit/transform, sklearn-compatible), supervised/semi-supervised, Parametric UMAP (NN encoder/decoder, TensorFlow), DensMAP (density), AlignedUMAP (temporal/batch). 15+ distance metrics, custom Numba metrics, precomputed distances. For linear reduction use PCA; for neighborhood graphs use sklearn NearestNeighbors.

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Databricks SQL (DBSQL) advanced features and SQL warehouse capabilities. This skill MUST be invoked when the user mentions: "DBSQL", "Databricks SQL", "SQL warehouse", "SQL scripting", "stored procedure", "CALL procedure", "materialized view", "CREATE MATERIALIZED VIEW", "pipe syntax", "|>", "geospatial", "H3", "ST_", "spatial SQL", "collation", "COLLATE", "ai_query", "ai_classify", "ai_extract", "ai_gen", "AI function", "http_request", "remote_query", "read_files", "Lakehouse Federation", "recursive CTE", "WITH RECURSIVE", "multi-statement transaction", "temp table", "temporary view", "pipe operator". SHOULD also invoke when the user asks about SQL best practices, data modeling patterns, or advanced SQL features on Databricks.

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