escalate mode runs its blocking recall sub-agent only when the
message asks about the past and the deterministic memory lane found no strong
trusted trigger match. This keeps ordinary replies fast while preserving a
deeper search path for prior decisions, conversations, and temporal or
multi-hop questions.
Flat retrieval is strongest for direct fact matches and weaker on temporal and
multi-session questions. LongMemEval (arXiv:2410.10813)
measures that gap, while the PrefEval benchmark highlights the value of
preference-adjacent reminders. Escalation by default spends the blocking model
call where those harder recall shapes are actually present.
This page is an index. Active memory is documented on nine pages, one per
reader job. Open the page that matches your task.
Where each section moved
Every section heading from the previous single-page version keeps its anchor here, so an existing link such as/concepts/active-memory#lossless-claw still
resolves. Each entry points at the page that now holds the content.
- Remember across conversations
- Advanced Active Memory quick start
- How it works
- When it runs
- Session toggle
- How to see it
- Query modes
- Prompt styles
- Model fallback policy
- Memory tools
- Advanced escape hatches
- Transcript persistence
- Configuration
- Recommended setup
- Debugging
- Common issues