Operating ProcedureExecution layer

Agent Handoff Integrity Check (Delivery)

A checklist with 7 steps: Map the full agent chain end-to-end before any client data enters the pipeline.

By InnovaAI ResearchPublished

What are the steps?

checklist

Agent Handoff Integrity Check (Delivery)

  1. 01

    Map the full agent chain end-to-end before any client data enters the pipeline.

    Document each agent's role, input schema, output schema, and the trigger condition that passes control to the next agent. Use a shared diagram or configuration file so the chain is auditable.

  2. 02

    Verify each agent's authentication and data-access scope matches the client's security requirements.

    For platforms like StackAI that support multi-tenant deployments, confirm that agents in regulated workflows read only the client's designated data stores and cannot cross tenant boundaries.

  3. 03

    Insert a validation gate after every agent that produces a client-facing output.

    A validation gate can be a human review step, a schema check, or a call to a separate verification agent. Without these gates, a single hallucinated fact propagates through the entire chain.

  4. 04

    Define fallback logic for each agent failure mode and test it with simulated errors.

    Common failure modes include API timeouts, malformed input, and low-confidence outputs. For each, specify whether the chain retries, skips, or halts and alerts an operator.

  5. 05

    Instrument every handoff with a unique trace ID and log the full payload.

    Trace IDs let operators replay a failed chain step-by-step. Logs should capture input, output, latency, and token cost per agent so you can audit and optimize later.

  6. 06

    Run a dry-run of the entire chain using synthetic client data before any live delivery.

    Use a representative sample that covers edge cases: missing fields, unusually long text, and known ambiguous queries. Confirm that the chain completes within the client's expected SLA.

  7. 07

    Document the chain's expected latency and cost per run, and set monitoring alerts for deviations.

    If a single agent's response time doubles or token usage spikes 20% above baseline, the monitoring system should notify the delivery lead before the client notices a delay.