Iterative Retrieval Pattern
Solves the "context problem" in multi-agent workflows where subagents don't know what context they need until they start working.
When to Activate
- Spawning subagents that need codebase context they cannot predict upfront
- Building multi-agent workflows where context is progressively refined
- Encountering "context too large" or "missing context" failures in agent tasks
- Designing RAG-like retrieval pipelines for code exploration
- Optimizing token usage in agent orchestration
The Problem
Subagents are spawned with limited context. They don't know:
- Which files contain relevant code
- What patterns exist in the codebase
- What terminology the project uses
Standard approaches fail:
- Send everything: Exceeds context limits
- Send nothing: Agent lacks critical information
- Guess what's needed: Often wrong
The Solution: Iterative Retrieval
A 4-phase loop that progressively refines context:
Phase 1: DISPATCH
Initial broad query to gather candidate files:
Phase 2: EVALUATE
Assess retrieved content for relevance:
Scoring criteria:
- High (0.8-1.0): Directly implements target functionality
- Medium (0.5-0.7): Contains related patterns or types
- Low (0.2-0.4): Tangentially related
- None (0-0.2): Not relevant, exclude
Phase 3: REFINE
Update search criteria based on evaluation:
Phase 4: LOOP
Repeat with refined criteria (max 3 cycles):
Practical Examples
Example 1: Bug Fix Context
Example 2: Feature Implementation
Integration with Agents
Use in agent prompts:
Best Practices
- Start broad, narrow progressively - Don't over-specify initial queries
- Learn codebase terminology - First cycle often reveals naming conventions
- Track what's missing - Explicit gap identification drives refinement
- Stop at "good enough" - 3 high-relevance files beats 10 mediocre ones
- Exclude confidently - Low-relevance files won't become relevant
- The Longform Guide - Subagent orchestration section
continuous-learning skill - For patterns that improve over time
- Agent definitions bundled with ECC (manual install path:
agents/)