Results for “hybridflow”

Guides architecture decisions, flow type selection, bulk safety validation, and fault handling standards for Salesforce Flow design and review.

Runs a three-phase AOI training pipeline: AutoML HPO baseline, DEFT iterative data improvement, and AutoML refinement on the augmented dataset.

Run the HyperFrames CLI to scaffold, author, lint, preview, render, and publish video compositions locally or on HeyGen Cloud, AWS Lambda, and Google Cloud Run.

FLOW framework integration for bloggers. Evidence-led content workflow using the Find, Optimize, Win loop with stage-specific AI prompts from the FLOW knowledge base (30 blog-applicable prompts, CC BY 4.0). Use when user says "FLOW", "FLOW framework", "blog flow", "evidence-led blogging", "find optimize win", or wants stage-specific blog prompts.

Build, run, and debug Nextflow data pipelines and nf-core workflows end to end, covering processes, channels, operators, configuration, testing, and deployment to HPC or cloud.

Quick Flow

OAuth2 Flows

Guides machine learning development with experiment tracking, hyperparameter optimization, model registry, and MLOps pipeline integration.

Expert hybrid cloud architect specializing in complex multi-cloud solutions across AWS/Azure/GCP and private clouds (OpenStack/VMware). Masters hybrid connectivity, workload placement optimization, edge computing, and cross-cloud automation. Handles compliance, cost optimization, disaster recovery, and migration strategies. Use PROACTIVELY for hybrid architecture, multi-cloud strategy, or complex infrastructure integration.

Manages the machine learning lifecycle with experiment tracking, model versioning, reproducible runs, and deployment through the MLflow platform.

Build and deploy machine learning models with TensorFlow, covering Keras, data pipelines, and production serving.

Designs, reviews, and troubleshoots Salesforce Flows from an admin perspective, covering flow type selection, bulkification, fault handling, and error diagnosis.

Design user flows and screen structures using UX patterns like progressive disclosure, hub-and-spoke navigation, and information pyramids.

Design user flows and screen structure using StyleSeed UX patterns such as progressive disclosure, hub-and-spoke navigation, and information pyramids.

Configure ViewModel state emission with StateFlow, SharedFlow, and sealed UiState classes in Android. Use for state modeling and sharing policies; defer generic lifecycle collection, navigation-event plumbing, Hilt injection, test code, and configuration-change recipes to their specific skills.

Terraform infrastructure-as-code workflow patterns: state and environments, module design, safe plan/apply, drift control, and CI guardrails

Run full computational-pathology workflows with PathML — whole-slide-image (WSI) analysis across 160+ slide formats, multiplexed immunofluorescence (CODEX, Vectra, MERFISH), nucleus segmentation/classification (HoVer-Net, HACTNet), tissue- and cell-graph construction, HDF5 dataset management, and deep-learning model training on pathology data. Use when the user builds end-to-end deep-learning pathology pipelines, analyzes multiplexed or spatial-proteomics slides, or segments nuclei. For lightweight H&E slide preprocessing, tissue masking, or plain Random/Grid/Score tile extraction prefer alterlab-histolab instead. Part of the AlterLab Academic Skills suite.

Route a task to the next synced SDLC workflow based on current artifacts and repo state.

Route goalflow (wanmol/goal-flow) work — a LangGraph framework that combines workflow graphs with agent loops — into exactly one mode: fit check, transpiling a Dify DSL export into runnable LangGraph Python, authoring workflow nodes and edges, building an `agent_kit` loop with middleware and a harness, wiring the serving layer (data adapters, SSE streaming, HITL, Redis/MySQL, API-key registration), or running the pre-publish security gate. Use when the user wants Dify's visual design without Dify's runtime, a graph node that hosts an agent loop, an OpenAI-compatible wire protocol over their own workflows, or prompt-injected `SKILL.md` capabilities. Triggers on: goalflow, goal-flow, dify to langgraph, dify transpiler, dify DSL export, BaseWorkflow, agent_kit, AgentBaseNode, DataAdapter, chunk processor, HITL interrupt, dify2langgraph. Route plain graph-API questions to `langgraph-fundamentals` and `langgraph-workflow`.

ByteDance's open-source super agent harness — spawns parallel sub-agents, Docker sandbox execution, persistent long-term memory, modular skills (research/report/slides). Built on LangChain + LangGraph. Triggers on: 'deerflow', 'deer-flow', 'bytedance agent', 'super agent harness', 'LangGraph agent orchestration', 'multi-hour agent tasks', 'spawn sub-agents', 'agent sandbox docker', 'persistent agent memory', 'agent skills system', 'AI research orchestrator', 'long-running agent tasks', 'agent with memory', 'langgraph orchestrator', 'IM channel agent integration'.

Finalizes a hotfix and merges it into main and develop using git-flow, then prunes stale branches and worktrees. This skill should be used when the user asks to "finish a hotfix", "merge hotfix branch", "complete hotfix", "git flow hotfix finish", or wants to finalize a hotfix.

当需要进入并维持高效、专注的心流状态，以提升学习、工作或技能获取效率时

Manage and monitor Flux CD GitOps reconciliation, sources, and Kustomizations on Kubernetes, including Helm releases, image automation, and drift detection.

Use when planning a USENIX FAST project timeline from venue fit through choosing a Spring or Fall deadline, double-blind submission, the author-response period, shepherding or a one-shot revision, artifact evaluation, and the open-access camera-ready, with backward-planning offsets tuned to storage evaluation and honest handling of the two-deadline cycle.

Globus CLI workflow for staging HuBMAP CODEX datasets from remote endpoints to HiPerGator

Orchestrate autonomous AI development pipelines through your Kanban board, managing multi-worker Claude Code dispatch, deterministic quality gates, adversarial review, per-task cost tracking, and crash-proof pipeline execution.

Claude Code + Codex dual orchestration for hybrid interactive and parallel workflows

Orchestrate autonomous AI development pipelines through your Kanban board (Asana, GitHub Projects, Linear). Manages multi-worker Claude Code dispatch, deterministic quality gates, adversarial review, per-task cost tracking, and crash-proof pipeline execution.

Design user flows and screen structure using UX patterns like progressive disclosure, hub-and-spoke navigation, and information pyramids to create coherent user journeys before building screens.

Guides a structured interview and repository research to clarify feature requirements, classify scope, and produce context artifacts for approval before design.

Routes ambiguous or multi-domain engineering requests to the smallest ordered skill set. Do not use for clear single-skill work or same-task follow-ups.

Universal project workflow with built-in quality auditing. Quick mode (fast brainstorm, ~5 min) or Deep mode (full plan with audits, ~30 min). Auto-picks based on task size. Trigger: 'build', 'create', 'plan', 'new project', 'brainstorm', 'design', 'UI', 'website', 'dashboard', 'app', 'help me build', or any project-level task.

Turn a repeatable workflow from the current session into a reusable OMC skill draft

当需要进入高度专注、高效且愉悦的心流状态以完成创造性或学习性任务时

Use to plan an ACM/IEEE HRI campaign backward from the full-paper deadline through the abstract-then-paper two-step, the rebuttal, the program-committee meeting, camera-ready, and the March conference, coordinating the parallel alt.HRI, Late-Breaking Reports, video, and Student Design deadlines.