DAG Recall

What it does

When the agent needs to recall something from past sessions, reading raw transcripts is expensive and often exceeds context limits. DAG Recall walks the hierarchical summary DAG built by memory-dag-compactor — starting from high-level (d2/d3) nodes, expanding into detailed (d0/d1) children — and assembles a focused, cited answer.

Inspired by lossless-claw's sub-agent recall pattern, where a lightweight agent fetches and expands nodes on demand rather than loading entire conversation histories.

When to invoke

• When the agent asks "what did we decide about X?" or "how did we implement Y?"
• When context about a past session is needed but the transcript isn't loaded
• When searching MEMORY.md returns only high-level summaries that need expansion
• Before starting work that depends on decisions or patterns from earlier sessions

How to use

python3 recall.py --query "how did we handle auth migration"   # Walk DAG + assemble answer