A2A-ACT-01Tier IIInter-Agent Communication

Agent-as-Tool (Sub-Agent Invocation)

Expose specialised agents to other agents as tools — with the same typed-contract discipline as any other tool.

Runtime: ActAgentOps: Build & IntegrateSee on the matrix →
AGENT-AS-TOOL Caller Agentreasoning Specialist Agent Atyped I/O Function Toolsame interface Specialist Agent Btyped I/OCaller does not know whether "tool" is a function or another agent.
In Plain English

This page is the complete instruction page for one pattern called "Agent-as-Tool (Sub-Agent Invocation)." It explains the problem this pattern solves, the idea behind the solution, when you should (and should not) use it, and what happens afterward — both the good effects and the costs.

This matters because building AI agents is not just about making them clever. It is also about making them safe and predictable. Following a well-tested pattern like this one helps avoid common mistakes, and shows you exactly which safety rules and regulations it connects to, listed under "Standards Mesh" on this page.

Context

Some sub-problems are better solved by a specialist agent than by a tool. A specialist has its own reasoning, memory, and guardrails. Treating it as just another callable function composes naturally.

Problem

Hand-wired multi-agent systems entangle control flow and obscure responsibility.

Forces

  • Specialist depth vs coordination cost
  • Composability vs emergent complexity

Solution

Expose each specialist agent behind a tool interface: named, typed inputs/outputs, cost and latency metadata, capability description. The caller does not need to know whether the "tool" is a function or another agent. Standard observability captures the delegation.

Applicability

  • Hierarchical multi-agent systems
  • Supervisor/worker patterns
  • Mixed human-agent organisations

Anti-Patterns

  • Tight coupling to specific agent implementations
  • Delegation without observability

Consequences

  • +Composable specialisation
  • +Substitutable implementations
  • Performance overhead of additional agent hops
  • Error propagation across agent boundaries