Graceful Degradation with Transparency

Core

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

degradationtransparencyresiliencecoverage

Prerequisites

Error Propagation in Multi-Agent Systems

When operating with incomplete data or partial failures, systems should continue operating while being transparent about limitations.

Principles

Don't fail entirely: Partial results are better than no results

Annotate gaps: Tell users what's missing and why

Distinguish failure types: Timeout (retry-able) vs empty results (valid)

Preserve completed work: Don't throw away successful results because one source failed

Coverage Annotations

Structure output with:

Which findings are well-supported (multiple sources)

Which topic areas have gaps (sources unavailable)

Confidence levels based on source coverage

Anti-Pattern

Proceeding with synthesis without indicating data gaps produces misleading reports. Users have no way to know certain areas lack coverage.

Silently Suppressing Errors

Returning empty results as success prevents the coordinator from making recovery decisions. The coordinator needs to know WHY results are empty to decide whether to retry, use an alternative source, or proceed with annotated gaps.

Key Takeaways

✓Continue operating with partial data but annotate gaps transparently
✓Distinguish retry-able failures from valid empty results
✓Never hide data gaps from downstream consumers

Related Concepts

Error Propagation in Multi-Agent Systems

Handle errors at the lowest level capable of resolving them

Handling Conflicting Data Sources

Preserve conflicting data with source attribution; don't choose one

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?