#nextflow #dsl2 #modules #nextflow #nf_core #nf_test #pipelines #workflows

Using **nf-core** helps you create and run bioinformatics pipelines easily. It provides a collection of ready-made modules for tools like `fastqc` and `bwa`, which you can add to your pipelines. This makes it easy to share and reuse code across different projects. **nf-core** also helps ensure that your analyses are reliable and can be repeated by others, which is important for scientific research. You can easily install, update, and manage these modules using **nf-core tools**, making your work more efficient and consistent.

https://github.com/nf-core/modules

#go #agents #ai #caching #ci_cd #containers #continuous_deployment #continuous_integration #dag #dagger #devops #docker #graphql #workflows

Dagger is a tool that helps make workflows easier to manage. It lets you break down complex tasks into smaller, reusable parts that can run in different environments. This means you can work with many languages and tools without worrying about compatibility issues. Dagger also helps you see what's happening in your workflows, making it easier to fix problems. It saves time and money by caching results, so you don't have to redo tasks. Overall, Dagger makes it simpler to build and manage workflows, especially for AI and software development tasks.

https://github.com/dagger/dagger

#ruby #angular #bcf #boards #bug_tracker #gantt #gantt_chart #ifc #issue_tracker #kanban #openproject #project_management #project_planning #roadmap #ruby #scrum #timeline #workflows

OpenProject is a powerful tool for managing projects. It helps teams work together by organizing tasks, tracking time, and setting budgets. You can use it for both traditional and agile project management. It offers features like Gantt charts, Kanban boards, and bug tracking. OpenProject is open-source, meaning it's free and customizable. You can choose to host it on your own servers or use their cloud service. This flexibility and collaboration make it a great choice for teams looking to manage projects efficiently.

https://github.com/opf/openproject

#typescript #agents #ai #cloudflare #durable_objects #workflows

Cloudflare Agents helps developers build intelligent AI systems that can remember things, communicate in real-time, and work on their own at a global scale. These AI agents can maintain their state and memory, allowing them to learn from interactions and respond better over time. The benefit to users is that they can create powerful AI tools more easily and affordably, without needing complex infrastructure. This means users can automate tasks more efficiently and make their AI systems smarter and more responsive.

https://github.com/cloudflare/agents

#typescript #cli #clustering #concurrency #dependency_injection #effect #error_handling #javascript #observability #opentelemetry #platform #schema #typescript #workflows

Effect is a powerful TypeScript framework that helps you build reliable and complex applications by managing side effects like logging, network calls, and database operations in a safe and organized way. It uses a core `Effect` type to describe workflows that are lazy, composable, and type-safe, allowing you to handle errors and dependencies explicitly. The framework is modular, with many packages for AI, CLI tools, distributed computing, SQL databases, and more, making it flexible for various needs. Using Effect improves code quality, concurrency handling, and maintainability, helping you write robust TypeScript apps efficiently[1][2][4][5].

https://github.com/Effect-TS/effect

#go #cli #event_driven #event_driven_architecture #queues #serverless #serverless_functions #workflow_engine #workflows

Inngest lets you write reliable, long-running background functions called durable workflows that automatically handle retries, scheduling, and state management without needing to manage infrastructure like queues or servers. You write functions in your preferred language using their SDKs, run and test them locally with the Inngest Dev Server, then deploy them on your own infrastructure or Inngest’s platform. It supports complex workflows with steps that retry on failure, concurrency control, and event triggers. This saves you time and effort by simplifying event-driven app development, improving reliability, and scaling automatically without extra setup. It also offers tools for monitoring and managing workflows easily.

https://github.com/inngest/inngest

#java #distributed_systems #durable_execution #grpc #java #javascript #microservice_orchestration #orchestration_engine #orchestrator #reactjs #spring_boot #workflow_automation #workflow_engine #workflow_management #workflows

Conductor is an open-source tool that helps you manage and automate complex workflows involving many microservices and systems. It makes your workflows flexible, reliable, and scalable by handling retries, errors, and monitoring automatically. You can define workflows as code in JSON, use various task types, and manage workflows dynamically without tightly coupling services. It offers an easy-to-use web interface and supports multiple databases like Redis and MySQL. This helps you build, run, and monitor workflows efficiently, saving time and reducing errors in managing distributed applications. It also has SDKs for Java, Python, JavaScript, Go, and C# to integrate easily with your projects.

https://github.com/conductor-oss/conductor

#python #agent_framework #agentic_ai #agents #ai #dotnet #multi_agent #orchestration #python #sdk #workflows

Microsoft Agent Framework is an open-source toolkit that helps you build and manage AI agents and multi-agent workflows using Python or .NET. It combines the best features of previous Microsoft AI projects to let you create simple chatbots or complex workflows where multiple agents work together. It supports many AI models, connects easily to external tools and APIs, and runs anywhere—on cloud or on-premises. The framework also includes features like human review, workflow checkpointing, and monitoring to make your AI applications reliable and adaptable. This means you can build powerful, flexible AI solutions faster and with less code.

https://github.com/microsoft/agent-framework

#typescript #mcp #mcp_server #n8n #workflows

n8n-MCP is a tool that connects AI assistants like Claude to the n8n workflow automation platform, giving AI deep knowledge of over 500 n8n nodes, their properties, operations, and documentation. It helps you quickly find, configure, and validate workflow templates or build workflows from scratch with real-world examples and smart filtering. You can deploy it easily via npx, Docker, or cloud services. This saves you time, reduces errors, and boosts confidence by letting AI assist in designing and managing complex automations safely, as you test changes before applying them to production. It makes building and maintaining workflows faster and more reliable.

https://github.com/czlonkowski/n8n-mcp

#python #agents #ai_agents #anthropic #anthropic_claude #automation #claude #claude_code #claude_code_cli #claude_code_commands #claude_code_plugin #claude_code_plugins #claude_code_subagents #claude_skills #claudecode #claudecode_config #claudecode_subagents #orchestration #sub_agents #subagents #workflows

Claude Code Plugins provide a comprehensive system of 63 focused plugins containing 85 specialized agents, 47 skills, and 44 development tools organized for intelligent automation across software development. You install only what you need, keeping token usage minimal while accessing domain experts in architecture, languages, infrastructure, quality, and operations. Each plugin loads independently with its own agents and commands, letting you compose multiple plugins for complex workflows. This granular design means faster, cleaner sessions with progressive disclosure—knowledge loads only when activated. The benefit is significant productivity gains: you get expert-level assistance tailored to your specific task without unnecessary overhead, enabling your entire team to work more efficiently on development, infrastructure, security, and automation challenges.

https://github.com/wshobson/agents