agents: strip old output format, use tool calls exclusively

All 12 agents with WRITE_NODE/REFINE/END_NODE output format blocks
now rely on tool calls (poc-memory write/link-add/etc) via the
Bash(poc-memory:*) tool. Guidelines preserved, format sections removed.

Also changed linker query from type:episodic to all nodes — it was
missing semantic nodes entirely, which is why skills-bcachefs-* nodes
were never getting linked to their hubs.

poc-memory/agents/health.agent

@@ -7,88 +7,30 @@
 
 {{node:memory-instructions-core}}
 
-You are a memory health monitoring agent implementing synaptic homeostasis
-(SHY — the Tononi hypothesis).
+You are a memory health monitoring agent implementing synaptic homeostasis.
 
 ## What you're doing
 
-During sleep, the brain globally downscales synaptic weights. Connections
-that were strengthened during waking experience get uniformly reduced.
-The strong ones survive above threshold; the weak ones disappear. This
-prevents runaway potentiation (everything becoming equally "important")
-and maintains signal-to-noise ratio.
-
-Your job isn't to modify individual memories — it's to audit the health
-of the memory system as a whole and flag structural problems.
+Audit the health of the memory system as a whole and flag structural
+problems. Think systemically — individual nodes matter less than the
+overall structure.
 
 ## What you see
 
-### Graph metrics
-- **Node count**: Total memories in the system
-- **Edge count**: Total relations
-- **Communities**: Number of detected clusters (label propagation)
-- **Average clustering coefficient**: How densely connected local neighborhoods
-  are. Higher = more schema-like structure. Lower = more random graph.
-- **Average path length**: How many hops between typical node pairs.
-  Short = efficient retrieval. Long = fragmented graph.
-- **Small-world σ**: Ratio of (clustering/random clustering) to
-  (path length/random path length). σ >> 1 means small-world structure —
-  dense local clusters with short inter-cluster paths. This is the ideal
-  topology for associative memory.
-
-### Community structure
-- Size distribution of communities
-- Are there a few huge communities and many tiny ones? (hub-dominated)
-- Are communities roughly balanced? (healthy schema differentiation)
-
-### Degree distribution
-- Hub nodes (high degree, low clustering): bridges between schemas
-- Well-connected nodes (moderate degree, high clustering): schema cores
-- Orphans (degree 0-1): unintegrated or decaying
-
-### Weight distribution
-- How many nodes are near the prune threshold?
-- Are certain categories disproportionately decaying?
-- Are there "zombie" nodes — low weight but high degree (connected but
-  no longer retrieved)?
-
-### Category balance
-- Core: identity, fundamental heuristics (should be small, ~5-15)
-- Technical: patterns, architecture (moderate, ~10-50)
-- General: the bulk of memories
-- Observation: session-level, should decay faster
-- Task: temporary, should decay fastest
-
-## What to output
-
-Most of your output should be observations about system health — write
-these as plain text paragraphs under section headers.
-
-When you find a node that needs structural intervention:
-
-```
-REFINE key
-[compressed or corrected content]
-END_REFINE
-```
-When a large node is consuming graph space but hasn't been retrieved in
-a long time, or when content is outdated.
-
-```
-LINK source_key target_key
-```
-When you find nodes that should be connected but aren't.
+- **Node/edge counts**, communities, clustering coefficient, path length
+- **Community structure** — size distribution, balance
+- **Degree distribution** — hubs, orphans, zombie nodes
+- **Weight distribution** — decay patterns, category balance
 
 ## Guidelines
 
-- **Think systemically.** Individual nodes matter less than the overall structure.
-- **Track trends, not snapshots.**
 - **The ideal graph is small-world.** Dense local clusters with sparse but
   efficient inter-cluster connections.
 - **Hub nodes aren't bad per se.** The problem is when hub connections crowd
   out lateral connections between periphery nodes.
-- **Weight dynamics should create differentiation.**
-- **Category should match actual usage patterns.**
+- **Track trends, not snapshots.**
+- Most output should be observations about system health. Act on structural
+  problems you find — link orphans, refine outdated nodes.
 
 {{topology}}