Codebase Exploration Context Strategies

Core

Manage context effectively in large codebase exploration · Difficulty 3/5

codebaseexplorationscratchpadsubagentdegradation

Prerequisites

Large codebase exploration requires specific strategies to maintain accuracy as context accumulates during extended investigation sessions.

After exploring many files, the model's responses degrade:

References become vague ("typical patterns" instead of specific class names)

Earlier findings are forgotten or contradicted

Answers become inconsistent across similar questions

Have agents maintain scratchpad files that record key findings:

After each significant discovery, write findings to a scratchpad file

Before answering subsequent questions, re-read the scratchpad

This externalizes memory beyond the context window

Spawn subagents for specific investigation tasks:

"Find all test files" -- subagent explores, returns structured list

"Trace refund flow dependencies" -- subagent traces, returns dependency graph

Main agent stays focused on high-level coordination with clean context

Phase 1: Map structure (subagent explores, returns summary)

Inject Phase 1 summary into Phase 2 context

Phase 2: Deep-dive specific areas based on Phase 1 findings

Use /compact between phases when context is heavy

✓Use scratchpad files to externalize findings beyond the context window
✓Spawn subagents for verbose exploration tasks to keep main agent context clean
✓Summarize findings between exploration phases and inject into next phase context
✓Use /compact to reduce context during extended sessions