A2A Skill Mesh

Design, validate, and orchestrate A2A-compliant multi-agent systems using artifact-driven Mesh Flow DAGs.

Install
cmdop skills install agensi-a2a-skill-mesh

A2A Skill Mesh is an architect-level skill published by agensi for designing and orchestrating multi-agent systems built on Google A2A concepts and Mesh Flow’s artifact-driven DAG orchestration. Rather than chaining prompts together loosely, it structures agent interactions around explicit task contracts, capability discovery, and defined security boundaries.

The skill generates Agent Cards — testable capability models that allow agents to discover each other and route work appropriately. Workflows are modeled as artifact-driven directed acyclic graphs (DAGs), meaning the graph structure is determined by data production and consumption rather than by agent persona descriptions alone. This compile-then-run discipline means agent interactions can be validated and visualized before execution, reducing broken handoffs between agents.

Task lifecycle contracts define how individual agents handle state, messages, and artifacts across the full span of a task. Security modeling establishes explicit gates covering authentication, authorization, and authority delegation between agents. The skill also supports generation of project manifests (project.yaml), execution plans, and Mermaid-based DAG visualizations for observability.

This skill is appropriate when building systems where multiple specialized agents must coordinate reliably under strict interoperability rules. It is not appropriate for simple single-agent workflows, nor for projects where no multi-agent coordination or A2A protocol compliance is required.

Use cases

  • Design a multi-agent pipeline with explicit artifact handoff contracts between specialized agents
  • Generate Agent Cards to enable capability discovery and routing across an agent mesh
  • Define task lifecycle contracts that govern how agents manage state and message passing
  • Model security boundaries with authentication and authorization gates between agent groups
  • Produce Mermaid-based DAG visualizations to inspect agent interaction graphs before execution
  • Generate project.yaml manifests and execution plans for A2A-compliant workflows

When to use it

  • Building systems where multiple specialized agents must discover and coordinate with each other
  • Workflows requiring strict protocol contracts at every agent handoff
  • Projects that need auditable, visualizable DAG representations of agent interactions
  • Architectures that require explicit security and authority boundaries between agents

When not to use it

  • Single-agent workflows with no inter-agent coordination
  • Projects that do not use or require A2A protocol compliance
  • Situations where a lightweight prompt chain is sufficient and formal DAG modeling adds unnecessary overhead
  • Environments where no Node/NPM-compatible tooling is available