「tempo」の検索結果

Drive Chromium from standard Playwright APIs with a real-device fingerprint applied in the kernel, one persistent isolated profile per identity, and a per-profile proxy whose exit IP sets timezone and WebRTC - JavaScript (npm 'anti-detect-browser') or Python (PyPI 'antibrow'). Use when sessions must stay logged in across runs and stay separate, when a scraper or agent is blocked by an incoherent headless fingerprint, when checking ads or pricing from another region, when a page must be reached as a phone rather than a desktop, when automation mints a profile per task, when running several of your own accounts from one machine, or when testing how your own bot detection scores a real device. Also for 'antibrow', 'fingerprint browser', 'multi-account browser', '防关联', '多账号', '安卓模拟', 'Android profile', 'mobile fingerprint', 'temporary profile', 'CreepJS', 'residential proxy', 'browser-use', 'crawl4ai'. MCP control is browser-mcp-agent; isolation is multi-account-isolation.

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Structures git branches and worktrees: keeps unrelated changes on separate branches, isolates each in its own worktree created so the repository's setup runs, records dependencies with git-machete, and recombines them into a temporary mixdown branch for local testing. Use before creating any branch or worktree in a codebase that works on more than one branch, including branching off the default branch to start a change; when starting work in a fork, clone, or third-party checkout; when choosing what a new branch should be based on; when a branch is growing a second unrelated concern; when deciding whether to stack branches or keep them independent; when preparing a change for a pull request or patch submission; when handed an existing worktree or branch to implement and commit in a fork; or when a local build needs several in-progress branches combined. Not needed where the repository clearly commits everything to the trunk, or holds notes or personal data rather than code.

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Drafts Assignment and Assumption Agreements transferring contractual rights and obligations from assignor to assignee in asset purchase transactions. Covers assignment mechanics, liability assumption with temporal cutoff, third-party consent handling, reps and warranties, indemnification, and Exhibit A contract schedule. Trigger keywords: "assignment and assumption", "contract transfer", "assign contracts", "assume obligations", "asset purchase closing document", "assignor assignee agreement".

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Designs human-in-the-loop review points for DAG workflows. Determines what to present to the human, how to collect feedback, and how to route approve/reject/modify decisions back into the DAG. Use when adding approval gates, designing review UX, or handling human feedback in agent workflows. Activate on "human review", "approval gate", "human-in-the-loop", "human gate", "approval workflow", "user review step". NOT for executing human gates at runtime (use dag-runtime with Temporal signals), general UX design, or chatbot conversation design.

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Use when building Grafana dashboards backed by Prometheus, Loki, or Tempo, designing PromQL/LogQL queries, wiring template variables, setting alert rules, building SLO dashboards, or maintaining dashboards as code. Triggers: rate() vs increase() confusion, irate vs rate, label_replace, recording rules, alerting rule expressions, multi-dimensional template variables, ad-hoc filters, dashboard JSON model, provisioning via Terraform/grafonnet, p99 / histogram_quantile usage. NOT for Datadog/New Relic dashboards (vendor-specific), Grafana plugin development, or Loki ingestion pipeline tuning.

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Time-travel debugging for DAG executions. Inspect agent state at any node, replay decisions with modified inputs, compare execution traces side-by-side, and identify where reasoning diverged. Inspired by LangGraph Studio's state-editing model and Temporal's event history. Activate on "debug DAG", "replay execution", "time travel debug", "inspect node state", "what went wrong at step", "compare runs", "execution diff". NOT for live monitoring (use dag-runtime + websocket-streaming), failure analysis (use dag-ops), or general code debugging.

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Analyzes time-series and longitudinal RNA-seq for differential expression and trajectory structure. Covers DESeq2 LRT with reduced models, time as factor vs continuous vs natural splines, maSigPro (Nueda 2014 for RNA-seq), ImpulseDE2 with explicit impulse-model failure modes, DREAM for repeated measures via linear mixed models, pseudoreplication avoidance, conditional vs marginal modeling, and trajectory clustering with DPGP, Mfuzz (with Schwämmle 2010 fuzzifier estimation), and splines+k-means. Use when modeling time-course or longitudinal expression, choosing factor vs spline, handling repeated measures from the same subject, avoiding pseudoreplication, clustering temporal trajectories, or selecting between dedicated time-course tools and pairwise+LRT.

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Estimates time-scaled phylogenies, molecular-clock rates, effective reproduction number R_e, and population dynamics from dated pathogen genomes using TreeTime (maximum-likelihood) and BEAST2 (Bayesian; strict/relaxed clocks; coalescent, Bayesian-Skyline, Skygrid, Birth-Death-Skyline, and sampled-ancestor priors; structured coalescent via MASCOT). Covers root-to-tip clock QC via TempEst, date-randomisation tests, recombination masking via Gubbins/ClonalFrameML before clock inference for recombining bacteria, BDSKY origin-vs-rootHeight pitfalls, sampling-bias correction, multi-chain convergence diagnostics, and reconciling phylodynamic R_e with case-based R_t. Use when dating outbreak origins, estimating substitution rates, inferring R_e through time, building time-calibrated Nextstrain Augur trees, choosing between strict and relaxed clocks, fitting Birth-Death-Skyline models, diagnosing temporal-signal failure, running MASCOT for structured-population analyses, or using UShER for pandemic-scale placement.

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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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This skill should be used for time series machine learning tasks including classification, regression, clustering, forecasting, anomaly detection, segmentation, and similarity search. Use when working with temporal data, sequential patterns, or time-indexed observations requiring specialized algorithms beyond standard ML approaches. Particularly suited for univariate and multivariate time series analysis with scikit-learn compatible APIs.

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Use when male Chinese web novel writing or 男频小说写作 needs contemporary Chinese 热梗, 网络流行语, 轻笑话, 网络热门事件模板, 网络热门人物口头禅, 知名人物事件的安全化改写或模仿, 弹幕, 评论区, 角色对白, 短视频文案, Fanqie male-rank market radar, or work-study notes on writing style, characters, background, outline, and themes for AI-assisted fiction writing.

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Systematic VPS cleanup — analyze files, categorize by importance, safely delete temporary/old data to free disk space

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Use when choosing HOW to record change history / audit trails — walks the tier matrix (columns → audit log → temporal → event sourcing). Triggers on 'wer hat was wann', 'audit log'.

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Especialista em event sourcing, CQRS e padrões de arquitetura orientada por eventos. Domina design de event store, construção de projeções, orquestração de sagas e padrões de consistência eventual. Use PROATIVAMENTE para sistemas baseados em event sourcing, requisitos de trilha de auditoria ou modelagem de domínio complexa com consultas temporais.

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Especialista em backend reativo Convex: design de schema, funções TypeScript, assinaturas em tempo real, autenticação, armazenamento de arquivos, agendamento e deploy.

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Domine os princípios de design de APIs REST e GraphQL para construir APIs intuitivas, escaláveis e mantíveis que encantam desenvolvedores e resistem ao tempo.

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Auxilia na redação de conteúdo de alta qualidade através de pesquisa, adição de citações, melhoria de ganchos, iteração em esquemas e feedback em tempo real de cada seção. Transforma seu processo de escrita de esforço solo em parceria colaborativa.

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Plataforma de observabilidade de IA de código aberto para rastreamento de LLM, avaliação e monitoramento. Use ao debugar aplicações de LLM com rastreamentos detalhados, executar avaliações em datasets ou monitorar sistemas de IA em produção com insights em tempo real.

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Híbrido RNN+Transformer com inferência O(n). Tempo linear, contexto infinito, sem cache KV. Treina como GPT (paralelo), infere como RNN (sequencial). Projeto Linux Foundation AI. Produção em Windows, Office, NeMo. RWKV-7 (março de 2025). Modelos até 14B parâmetros.

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Rastreie experimentos de ML com logging automático, visualize treinamento em tempo real, otimize hiperparâmetros com sweeps e gerencie registro de modelos com W&B - plataforma colaborativa de MLOps

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Construa pipelines de dados escaláveis, data warehouses modernos e arquiteturas de streaming em tempo real. Implementa Apache Spark, dbt, Airflow e plataformas de dados nativas em nuvem.

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Acelere a inferência de LLMs usando especulative decoding, múltiplas cabeças Medusa e técnicas de lookahead decoding. Use ao otimizar velocidade de inferência (aceleração de 1,5-3,6×), reduzir latência em aplicações em tempo real ou fazer deploy de modelos com recursos computacionais limitados. Cobre modelos draft, atenção em árvore, iteração de Jacobi, geração paralela de tokens e estratégias de deploy em produção.

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Load this skill before implementing a fix for a barrier that may originate in a shared component, design system, renderer, or external dependency rather than this project's own code. Decide whether the responsible fix is local, an existing installed capability, or an upstream contribution before writing a workaround. Absolutely always record any temporary local divergence with an owner and removal condition. Under no circumstances open, comment on, or submit anything in an external project without explicit human approval.

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Mathematical foundations, logical structures, and formal verification guidance. Trigger when: - Designing protocol contracts, formal specifications, verifying state spaces, or using proof assistants. - Tasks involve: TLA+, Alloy, Lean, Coq, model checkers, invariants, temporal logic. - Prompt contains keywords: formal verification, alloy, tla+, lean, coq, invariant, state machine, model checker, liveness, safety.

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