Packs
4 packscurated
Agents & MCP
Build agents, MCP servers and tool-using workflows.
34 skills · pack
@microsoft
Microsoft 365 Agents Toolkit
Toolkit for building and evaluating Microsoft 365 Copilot declarative agents — scaffolding, JSON manifest development, capability configuration, and eval workflows.
6 skills · pack
@dotnet
Dotnet AI
AI and ML skills for .NET: technology selection, LLM integration, agentic workflows, RAG pipelines, MCP, and classic ML with ML.NET.
5 skills · pack
@alirezarezvani
Engineering
37 advanced engineering skills: agent designer, agent workflow designer, RAG architect, database designer + schema designer + SQL assistant, migration architect, observability designer, dependency auditor, changelog generator (with semantic version bumper and hotfix/rollback procedures), API design reviewer, API test suite builder, CI/CD pipeline builder, MCP server builder, skill security auditor
33 skills · pack
Results for “agent-workflow”
10 skills
diegosouzapw agno
Build AI agents, multi-agent teams, and agentic workflows using the Agno framework, with reference files covering agents, teams, workflows, memory, knowledge, and deployment.
54 · bundle
oyi77 dify-workflow
Guides building LLM applications on the Dify platform, covering visual workflows, knowledge bases, agents, and API deployment.
10
affaan-m iterative-retrieval
Progressively refines context retrieval in multi-agent workflows to solve the subagent context problem.
226k
antigravity ai-ml
Orchestrates AI/ML workflows for building LLM applications, RAG systems, AI agents, and ML pipelines with observability and security.
42.4k
More results
nimoqup046-collab ai-ml
Orchestrates AI/ML development workflows covering LLM applications, RAG systems, AI agents, ML pipelines, and observability.
2
lingxling ai-ml
Orchestrates AI/ML workflows for building LLM applications, RAG systems, AI agents, and ML pipelines, covering design, integration, observability, and security.
253
lucaspmarie-a11y ai-ml
Orchestrates AI/ML workflows for building LLM applications, RAG systems, AI agents, and ML pipelines, covering design, integration, observability, and security.
5
scoheart tavily-best-practices
Reference for building Tavily-powered search, extraction, crawling, and research into agentic workflows and RAG systems.
2 · bundle
jorcan ai-ml
Orchestrates AI/ML workflows for building LLM applications, RAG systems, AI agents, and ML pipelines, covering design, integration, observability, and security.
0 · bundle
phoroth ai-ml
Orchestrates AI/ML workflows for building LLM applications, RAG systems, AI agents, and ML pipelines, covering design, integration, observability, and security.
3