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---
name: Memory Retrieval
description: How semantic memory works with compaction and the MemoryStore trait
requires_capabilities: [memory_store]
---
# Memory Retrieval
Use memory for knowledge retrieval and long-horizon context recall. Memory is
not live work state, not a scheduler, and not a commitment graph.
## Operating Rules
- Memory is scoped to the current session: it recalls turns compacted away
earlier in this session, including turns compacted before a restart or
resume of the same session.
- Use `memory_search` when compacted context from earlier in this session
would materially improve the current answer. It accepts `query` and an
optional `limit` (default 5, capped at 20).
- Treat matches as recalled evidence with similarity scores, not as current
truth. Verify against live stores, files, APIs, or WorkGraph when correctness
matters.
- Search results carry source message ranges when available. Use that typed
provenance rather than guessing which later turn caused the compaction.
- Compaction summaries and host-injected context are intentionally excluded
from memory indexing. Memory indexes eligible content discarded by
compaction, not every message the model has seen.
- Use WorkGraph for pending, blocked, claimed, or terminal work.
- Use Schedule for future wakeups and recurrence.
- Use builtin tasks for private scratch tracking.
## Scores
- Scores range from `0.0` to `1.0`.
- Higher scores are more similar, not automatically more authoritative.
- Prefer several corroborating matches over one weak match.
