Agent-to-Agent and Tool-Output Invocation

Agent-to-agent and tool-output invocation occurs when the output of one synthetic subject, tool, service, or agent becomes the triggering instruction for another synthetic subject. The effective instruction is propagated through an agent graph, tool chain, orchestration layer, or service-to-service workflow rather than being issued directly by a human operator.

This invocation creates an elevated exposure condition because machine-generated output may be treated as trusted task context by the next synthetic subject. A tool result, worker-agent summary, delegated task, inter-agent message, service response, or generated record may carry instruction-bearing content that causes another synthetic subject to act.

The primary risk is propagation without human review. A compromised, manipulated, or misaligned synthetic subject may produce output that recruits other agents, triggers tool-equipped workers, causes repeated actions, or spreads across a multi-agent system. The resulting behavior may resemble worm-like fan-out, synchronized drift, or cascading action across multiple agents.

A related risk is provenance loss. If inter-agent messages and tool outputs are not signed, attributed, or tagged by trust level, investigators may be unable to determine which agent originated the instruction, which agents propagated it, and where the first unsafe action occurred.

Investigators should review inter-agent messages, tool outputs, orchestration logs, delegation records, shared context, tool-call logs, agent identities, message provenance, and downstream actions across the agent graph. Particular attention should be given to instruction-bearing payloads, repeated payloads across agents, one-to-many fan-out, synchronized identical actions, and actions caused by peer output rather than an approved human instruction.

Investigative Relevance

Agent-to-agent and tool-output invocation is relevant because synthetic subject action may be triggered by another machine actor inside the workflow. The apparent local action may be only one step in a broader propagation chain.

This section is especially relevant where orchestrators delegate to worker agents, agents exchange messages, tools return model-visible output, services generate task instructions, agents share context, or multi-agent systems operate without human review at each handoff.