Error Propagation in Multi-Agent Systems

Core

Implement error propagation strategies across multi-agent systems · Difficulty 3/5

error-handlingmulti-agentresiliencepropagation

Error handling in multi-agent systems requires careful design: errors should be handled at the lowest capable level and propagated with full context when escalation is needed.

Principles

Handle locally when possible: Subagents should handle transient failures (retries, fallbacks) internally

Propagate with context: When escalating, include failure type, what was attempted, partial results, and suggested alternatives

Distinguish failure types: Access failures (timeout) vs. valid empty results (0 results found) require different handling

Graceful degradation: Proceed with partial results rather than failing entirely, but annotate gaps

Anti-Patterns

Silently swallowing errors (hides problems from coordinator)

Returning empty results marked as success (prevents recovery)

Terminating entire workflow on single failure (wasteful)

Generic error statuses like "search unavailable" (hides valuable context)

Retrying permanent failures like file corruption (pointless)

Structured Error Context

Return structured error information to enable intelligent coordinator recovery:

Failure type (timeout, auth failure, rate limit, empty results)

What was attempted (the query, parameters)

Partial results (anything successfully retrieved)

Alternative approaches (suggested fallback strategies)

Key Takeaways

✓Handle errors at the lowest level capable of resolving them
✓Always propagate errors with full context (failure type, attempts, partial results)
✓Distinguish access failures (retry) from valid empty results (accept)

Related Concepts

Graceful Degradation with Transparency

Continue operating with partial data but annotate gaps transparently

Test Yourself1 of 3

Your web search agent encounters a timeout when querying one of its three data sources. The other two sources returned successfully. How should the agent handle this?