Distill session episodes into persistent memory patterns
Transforms episodic session logs into refined semantic memory patterns.
/plugin marketplace add c-daly/agent-swarm/plugin install agent-swarm@fearsidhe-pluginsThis skill inherits all available tools. When active, it can use any tool Claude has access to.
Transforms episodic session logs into refined semantic memory patterns.
/distill # Distill episodes at current scope
/distill show # Show current memory without distilling
/distill episodes # Show pending episodes awaiting distillation
During agent work, learnings are logged to .context/EPISODES.md:
## Session: 2026-01-10T14:30:00Z
- **Task**: Fix authentication bug
- **Outcome**: success
- **Learnings**:
- JWT tokens need refresh handling in middleware
- Error messages should include request ID
When /distill runs:
Results are saved to .context/MEMORY.md:
# Memory: [Scope]
## Patterns Observed
- JWT tokens need refresh handling
Confidence: high | Last reinforced: 2026-01-10
## Pitfalls Discovered
- Avoid storing tokens in localStorage
Confidence: medium | Last reinforced: 2026-01-08
When invoked, run:
python3 ~/.claude/plugins/agent-swarm/context/memory.py distill .
For showing memory:
python3 ~/.claude/plugins/agent-swarm/context/memory.py show .
For pending episodes:
python3 ~/.claude/plugins/agent-swarm/context/memory.py episodes .
Agents can log learnings by including in their output:
LEARNING: [description of pattern, pitfall, or approach]
These are captured by post-task hooks and added to EPISODES.md.
| Confidence | Meaning |
|---|---|
| 0.0 - 0.2 | Uncertain, may be pruned |
| 0.2 - 0.4 | Low, needs reinforcement |
| 0.4 - 0.7 | Medium, established pattern |
| 0.7 - 0.95 | High, well-validated |
Distillation triggers automatically when:
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