Narrow Decomposition Risk
CoreOrchestrate multi-agent systems with coordinator-subagent patterns · Difficulty 3/5
0%
decompositioncoveragemulti-agent
Prerequisites
Explanation
When a coordinator agent decomposes a broad topic into subtasks, narrow decomposition is a common failure mode that produces incomplete results.
The Problem
Topic: "Impact of AI on creative industries"
Coordinator decomposes into:
- AI in digital art creation
- AI in graphic design
- AI in photography
Result: Report covers only visual arts, completely missing music, writing, and film.
Root Cause
The coordinator's task decomposition was too narrow. All three subtasks focused on visual arts, missing other creative domains.
Solutions
- Explicit decomposition guidelines: "Ensure subtasks cover ALL relevant sub-domains"
- Coverage validation: After decomposition, validate that subtasks span the full scope
- Domain enumeration: Require the coordinator to enumerate all relevant domains before creating subtasks
- Partition by source type: Assign distinct subtopics or source types to each agent to minimize duplication
Diagnostic
When subagents all succeed but the final output has gaps, the root cause is usually the coordinator's decomposition, not the subagents' execution.
Key Takeaways
- Narrow task decomposition causes incomplete results even when all subtasks succeed
- Validate that decomposition covers the full scope before executing
- If subagents succeed but output has gaps, check coordinator decomposition
Related Concepts