Results for “workflow-execution”

Automate retail operations by discovering and executing tools through the Rube MCP interface, with connection management and schema-aware execution.

Frames tasks with explicit goals, success evidence, stop conditions, and boundaries before execution, then routes work to the appropriate workflow.

Generate images, video, and audio with ComfyUI — install, launch, manage nodes/models, run workflows with parameter injection. Uses the official comfy-cli for lifecycle and direct REST/WebSocket API for execution.

Generate images, video, and audio with ComfyUI — install, launch, manage nodes/models, run workflows with parameter injection. Uses the official comfy-cli for lifecycle and direct REST/WebSocket API for execution.

Generate images, video, and audio with ComfyUI — install, launch, manage nodes/models, run workflows with parameter injection. Uses the official comfy-cli for lifecycle and direct REST/WebSocket API for execution.

Upgrade GitHub Actions to supported runtimes by selecting safe action versions, preserving workflow behavior, and validating post-upgrade execution.

Automates Pipeline CRM operations through Composio's Pipeline CRM toolkit via Rube MCP, including tool discovery, connection management, and workflow execution.

Detects the current state of an Open-workspace project and advances to the next logical workflow step, from discussion through planning, execution, verification, and completion.

Builds reliable serverless background jobs and event-driven workflows with Inngest, using durable steps, fan-out patterns, and scheduled functions without managing queues or workers.

Trigger.dev expert for background jobs, AI workflows, and reliable async execution with excellent developer experience and TypeScript-first design. Use when: trigger.dev, trigger dev, background task, ai background job, long running task.

Trigger.dev expert for background jobs, AI workflows, and reliable async execution with excellent developer experience and TypeScript-first design. Use when: trigger.dev, trigger dev, background task, ai background job, long running task.

Trigger.dev expert for background jobs, AI workflows, and reliable async execution with excellent developer experience and TypeScript-first design. Use when: trigger.dev, trigger dev, background task, ai background job, long running task.

Use when multi-company coordination, cross-team communication, or inter-company workflow execution is needed. This skill defines protocols for agents from different companies to cooperate on shared projects and tasks.

Trigger.dev expert for background jobs, AI workflows, and reliable async execution with excellent developer experience and TypeScript-first design. Use when "trigger.dev, trigger dev, background task, ai background job, long running task, integration task, scheduled task, trigger-dev, background-jobs, ai-workflows, typescript, integrations, async, tasks, serverless" mentioned.

Guides AI agents through engineering workflows with eval-first execution, task decomposition, cost-aware model routing, and review focus for generated code.

Evidence-first repo execution workflow for ECC. Use when the user wants a command run, a repo checked, a CI failure debugged, or a narrow fix pushed with exact proof of what was executed and verified.

Build and deploy apps/applets on the DNAnexus cloud genomics platform, manage data objects, run workflows, and use the dxpy Python SDK for genomics pipeline development and execution.

Builds a non-advisory prediction-market trade planning worksheet for Itô or venue workflows, inspecting venues, underliers, constraints, and manual execution steps without placing trades or recommending positions.

Build AI agents on Cloudflare Workers using the Agents SDK. Load when creating stateful agents, durable workflows, real-time WebSocket apps, scheduled tasks, MCP servers, chat applications, voice agents, or browser automation. Covers Agent class, state management, callable RPC, Workflows, durable execution, queues, retries, observability, and React hooks. Biases towards retrieval from Cloudflare docs over pre-trained knowledge.

Build AI agents on Cloudflare Workers using the Agents SDK. Load when creating stateful agents, durable workflows, real-time WebSocket apps, scheduled tasks, MCP servers, chat applications, voice agents, or browser automation. Covers Agent class, state management, callable RPC, Workflows, durable execution, queues, retries, observability, and React hooks. Biases towards retrieval from Cloudflare docs over pre-trained knowledge.

PIV workflow orchestrator - Plan, Implement, Validate loop for systematic multi-phase software development. Use when building features phase-by-phase with PRPs, automated validation loops, or multi-agent orchestration. Supports PRD creation, PRP generation, codebase analysis, and iterative execution with validation.

Generate images, video, and audio with ComfyUI — install, launch, manage nodes/models, run workflows with parameter injection. Uses the official comfy-cli for lifecycle and direct REST/WebSocket API for execution.

Write, review, debug, or test Python Xarray workflows for labeled N-dimensional DataArray and Dataset operations, including coordinates, alignment, indexing, groupby, resample, rolling, weighted reduction, Dask-backed execution, and NetCDF/Zarr I/O.

Submit and manage protocols on Ginkgo Bioworks Cloud Lab for autonomous lab execution, including protein expression, purification, quantification, RNA synthesis, and custom workflows via EstiMate.

Builds DAG visualizations using ReactFlow v12 with custom nodes, ELKjs auto-layout, Zustand state management, and live state updates via WebSocket. Use when implementing workflow visualization dashboards, creating custom agent node components, integrating ELK layout algorithms, or wiring execution state into React components. Activate on "ReactFlow", "workflow visualization", "DAG visualization", "ELKjs", "custom nodes", "node-based editor", "graph visualization". NOT for writing Mermaid diagrams (use mermaid-graph-writer), general React development, or static diagram rendering.

Run the Ouroboros specification-first development loop: reduce ambiguity with a Socratic interview grounded in live git data (commits, churn, contributors), freeze an immutable seed/spec, render the execution plan through spec-kit (/speckit.plan → /speckit.tasks), execute against that contract through cli-anything agent-native CLI harnesses (cli-hub, --json evidence), verify before claiming success, and keep looping until completion is actually verified. Use when the user wants spec-first clarification, git-aware interviews, immutable requirements, drift-aware implementation, harness-driven execution, or a persistent completion loop that should keep going until tests / checks / acceptance criteria pass. Triggers on: ooo, ouroboros, interview, seed, run workflow, evaluate, evolve, ooo ralph, specification first, socratic interview, git-aware interview, ambiguity reduction, execution plan, cli harness execute, persistent completion.

Build multi-agent AI systems with LangGraph — the low-level orchestration framework for stateful, graph-based agent workflows. Covers supervisor, swarm, and hierarchical multi-agent patterns; subgraph composition; state management (checkpointers/stores); persistence; evals; and production debugging. Reach for this when designing agent architectures that need cycles, conditional branching, parallel execution, or human-in-the-loop patterns.

Provides Gemini CLI delegation workflows for large-context analysis tasks, including English prompt formulation, execution flags, and safe result handling. Use when the user explicitly asks to use Gemini for a specific task such as broad codebase analysis or long-document processing. Triggers on "use gemini", "delegate to gemini", "run gemini cli", "ask gemini", "use gemini for this task".

Swap faces in a video using AI via the HeyGen API. Use when: (1) Replacing a face in a video with another face, (2) Face swapping from a source image onto a target video, (3) Creating personalized videos by swapping in a person's face, (4) Working with HeyGen's /v1/workflows/executions endpoint for face swap processing.

Coordinate multi-agent development pipelines using shared JSON task files. Use when dispatching work across dev team agents (code-agent, test-agent, docs-agent, monitor-bot), tracking pipeline progress, or running sequential/parallel workflows. Covers project init, task assignment, status tracking, agent dispatch via sessions_send, and result collection. Supports two modes: linear (sequential pipeline) and dag (dependency graph with parallel execution).

Product orchestrator for Prodig Suites that guides product planning, routes work to specialists, and coordinates execution across the product lifecycle. Use when the user is shaping a digital product, deciding next steps, or needs help choosing the right Prodig specialist or workflow. Triggers: 'prodig', 'digital product', 'product idea', 'product planning', 'which product agent should I use', 'SaaS planning', 'course creation', 'template pack', 'productized service'.

Provides Codex CLI delegation workflows for complex code generation and development tasks using OpenAI's GPT-5.3-codex models, including English prompt formulation, execution flags, sandbox modes, and safe result handling. Use when the user explicitly asks to use Codex for complex programming tasks such as code generation, refactoring, or architectural analysis. Triggers on "use codex", "delegate to codex", "run codex cli", "ask codex", "codex exec", "codex review".

Scales pandas/NumPy workflows beyond memory with Dask distributed computing — parallel DataFrames, arrays, delayed task graphs, and cluster execution. Use when existing pandas/NumPy code must run on larger-than-RAM data or across clusters, for parallel file processing, distributed ML, or integration with existing pandas code. For out-of-core analytics on a single machine prefer vaex; for in-memory speed prefer polars. Part of the AlterLab Academic Skills suite.

Build WinDAGs — the orchestration platform where AI agents accumulate genuine expertise through DAGs of skillful agents. Covers DAG design, execution engines, meta-DAG architecture, skill selection, dynamic mutation, visualization, and deployment. Activate on "windags", "agent DAG", "DAG of agents", "workflow orchestration", "agent pipeline", "dynamic DAG", "meta-DAG", "build windags", "implement windags". NOT for understanding WHY decisions were made (use windags-avatar), creating individual skills (use skill-architect), or managing skill libraries (use windags-librarian).

Universal Reasoning Framework implementing λο.τ calculus over holarchic structures. Provides severity-based routing (R0-R3 pipelines), modular cognitive architecture (DEC, EVL, PAT, SYN, MEA, HYP, INT), fractal execution patterns, multi-level validation (η≥4, KROG), and adaptive learning. Triggers on: (1) complex multi-step reasoning, (2) high-stakes decisions requiring validation, (3) research synthesis across domains, (4) system design and architecture, (5) crisis management, (6) performance optimization. Implements scale-invariant reasoning from micro (tool calls) through meso (skill composition) to macro (orchestrated workflows).

Cross-platform Python library for quantum computing, quantum machine learning, and quantum chemistry. Enables building and training quantum circuits with automatic differentiation, seamless integration with PyTorch/JAX/TensorFlow, and device-independent execution across simulators and quantum hardware (IBM, Amazon Braket, Google, Rigetti, IonQ, etc.). Use when working with quantum circuits, variational quantum algorithms (VQE, QAOA), quantum neural networks, hybrid quantum-classical models, molecular simulations, quantum chemistry calculations, or any quantum computing tasks requiring gradient-based optimization, hardware-agnostic programming, or quantum machine learning workflows.