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Episodes

Where engrams are knowledge (“always do X”), episodes are history (“X happened at 14:32 in the deploy run”). They share infrastructure but answer different questions.

id: EPS-2026-0525-014
ts: 2026-05-25T14:32:18Z
agent: claude-code # who emitted it
channel: session # session | hook | incident | mcp | webhook
summary: "Deploy failed at migration step — column NOT NULL on populated table."
session: s_8f3a92 # links episodes from the same session

Episodes are append-only. Once written they’re never edited — only superseded by another episode.

QuestionUse
”Should I always do X?”Engram
”What did the agent do last Tuesday?”Episode
”Why did the deploy fail at 14:32?”Episode
”What’s the deploy procedure?”Engram
”How did we resolve this incident?”Episode (timeline) + engram (learning)

The natural flow is: episodes capture what happened, then a periodic distillation step promotes recurring patterns into engrams. The MCP tool plur_episode_to_engram does this on demand.

Terminal window
plur timeline --from "2026-05-20" --to "2026-05-25" --agent claude-code
plur timeline --channel incident --limit 20
plur timeline --session s_8f3a92

Or, from the agent, via plur_timeline — same parameters, MCP-shaped.

A session groups episodes that happened together. Every adapter starts a session at the beginning of a conversation and ends it when the user wraps up. The session ID flows through every episode emitted in that window, so you can reconstruct a single chat as a coherent timeline.

plur_session_start and plur_session_end are the explicit calls; adapters with lifecycle hooks (Claude Code, OpenClaw) call them for you.

When an engram is created during a session, the episode log records the link:

ts: 2026-05-25T14:40:01Z
channel: learning
summary: "Saved engram ENG-2026-0525-001 from correction."
links: [ENG-2026-0525-001]

This means every engram has a provenance — you can always trace back to the conversation that produced it. The CLI’s plur history ENG-... follows the chain.

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