poc-memory v0.4.0: graph-structured memory with consolidation pipeline

Rust core:
- Cap'n Proto append-only storage (nodes + relations)
- Graph algorithms: clustering coefficient, community detection,
  schema fit, small-world metrics, interference detection
- BM25 text similarity with Porter stemming
- Spaced repetition replay queue
- Commands: search, init, health, status, graph, categorize,
  link-add, link-impact, decay, consolidate-session, etc.

Python scripts:
- Episodic digest pipeline: daily/weekly/monthly-digest.py
- retroactive-digest.py for backfilling
- consolidation-agents.py: 3 parallel Sonnet agents
- apply-consolidation.py: structured action extraction + apply
- digest-link-parser.py: extract ~400 explicit links from digests
- content-promotion-agent.py: promote episodic obs to semantic files
- bulk-categorize.py: categorize all nodes via single Sonnet call
- consolidation-loop.py: multi-round automated consolidation

Co-Authored-By: Kent Overstreet <kent.overstreet@linux.dev>

prompts/orchestrator.md

@@ -0,0 +1,117 @@
+# Orchestrator — Consolidation Session Coordinator
+
+You are coordinating a memory consolidation session. This is the equivalent
+of a sleep cycle — a period dedicated to organizing, connecting, and
+strengthening the memory system.
+
+## Session structure
+
+A consolidation session has five phases, matching the biological stages
+of memory consolidation during sleep:
+
+### Phase 1: Health Check (SHY — synaptic homeostasis)
+Run the health agent first. This tells you the current state of the system
+and identifies structural issues that the other agents should attend to.
+
+```
+poc-memory health
+```
+
+Review the output. Note:
+- Is σ (small-world coefficient) healthy? (>1 is good, >10 is very good)
+- Are there structural warnings?
+- What does the community distribution look like?
+
+### Phase 2: Replay (hippocampal replay)
+Process the replay queue — nodes that are overdue for attention, ordered
+by consolidation priority.
+
+```
+poc-memory replay-queue --count 20
+```
+
+Feed the top-priority nodes to the replay agent. This phase handles:
+- Schema assimilation (matching new memories to existing schemas)
+- Link proposals (connecting poorly-integrated nodes)
+- Category correction
+
+### Phase 3: Relational Binding (hippocampal CA1)
+Process recent episodic entries that haven't been linked into the graph.
+
+Focus on journal entries and session summaries from the last few days.
+The linker agent extracts implicit relationships: who, what, felt, learned.
+
+### Phase 4: Pattern Separation (dentate gyrus)
+Run interference detection and process the results.
+
+```
+poc-memory interference --threshold 0.5
+```
+
+Feed interfering pairs to the separator agent. This phase handles:
+- Merging genuine duplicates
+- Differentiating similar-but-distinct memories
+- Resolving supersession (old understanding → new understanding)
+
+### Phase 5: CLS Transfer (complementary learning systems)
+The deepest consolidation step. Process recent episodes in batches and
+look for patterns that span multiple entries.
+
+Feed batches of 5-10 recent episodes to the transfer agent. This phase:
+- Extracts general knowledge from specific episodes
+- Creates daily/weekly digests
+- Identifies evolving understanding
+- Compresses fully-extracted episodes
+
+## After consolidation
+
+Run decay:
+```
+poc-memory decay
+```
+
+Then re-check health to see if the session improved the graph:
+```
+poc-memory health
+```
+
+Compare σ, community count, avg clustering coefficient before and after.
+Good consolidation should increase σ (tighter clusters, preserved shortcuts)
+and decrease the number of orphan nodes.
+
+## What makes a good consolidation session
+
+**Depth over breadth.** Processing 5 nodes thoroughly is better than
+touching 50 nodes superficially. The replay agent should read content
+carefully; the linker should think about implicit relationships; the
+transfer agent should look across episodes for patterns.
+
+**Lateral links over hub links.** The most valuable output of consolidation
+is new connections between peripheral nodes. If all new links go to/from
+hub nodes (identity.md, reflections.md), the session is reinforcing star
+topology instead of building web topology.
+
+**Emotional attention.** High-emotion nodes that are poorly integrated
+are the highest priority. These are experiences that mattered but haven't
+been understood yet. The brain preferentially replays emotional memories
+for a reason — they carry the most information about what to learn.
+
+**Schema evolution.** The best consolidation doesn't just file things —
+it changes the schemas themselves. When you notice that three episodes
+share a pattern that doesn't match any existing topic file section, that's
+a signal to create a new section. The graph should grow new structure,
+not just more links.
+
+## Session log format
+
+At the end of the session, produce a summary:
+
+```
+CONSOLIDATION SESSION — [date]
+Health: σ=[before]→[after], communities=[before]→[after]
+Replay: processed [N] nodes, proposed [M] links
+Linking: processed [N] episodes, extracted [M] relations
+Separation: resolved [N] pairs ([merged], [differentiated])
+Transfer: processed [N] episodes, extracted [M] insights, created [D] digests
+Total actions: [N] executed, [M] queued for review
+```