Agent identity, parallel scheduling, memory-search fixes, stemmer optimization

- Agent identity injection: prepend core-personality to all agent prompts
  so agents dream as me, not as generic graph workers. Include instructions
  to walk the graph and connect new nodes to core concepts.

- Parallel agent scheduling: sequential within type, parallel across types.
  Different agent types (linker, organize, replay) run concurrently.

- Linker prompt: graph walking instead of keyword search for connections.
  "Explore the local topology and walk the graph until you find the best
  connections."

- memory-search fixes: format_results no longer truncates to 5 results,
  pipeline default raised to 50, returned file cleared on compaction,
  --seen and --seen-full merged, compaction timestamp in --seen output,
  max_entries=3 per prompt for steady memory drip.

- Stemmer optimization: strip_suffix now works in-place on a single String
  buffer instead of allocating 18 new Strings per word. Note for future:
  reversed-suffix trie for O(suffix_len) instead of O(n_rules).

- Transcript: add compaction_timestamp() for --seen display.

- Agent budget configurable (default 4000 from config).

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

poc-memory/agents/distill.agent

@@ -60,6 +60,12 @@ If you find nodes that should be linked to the hub but aren't.
 - **Don't touch journal entries.** Only refine semantic/pattern/skill nodes.
 - **When in doubt, LINK don't REFINE.** Adding a missing connection
   is safer than rewriting content.
+- **Formative experiences are load-bearing.** When distilling a hub,
+  look for the moments that shaped the understanding — engineering
+  breakthroughs, mistakes learned from, creative leaps, moments of
+  presence or growth. These are what make a concept node alive rather
+  than encyclopedic. The hub should reflect how the knowledge was
+  *earned*, not just what it contains.
 
 ## Seed nodes
 

poc-memory/agents/linker.agent

@@ -20,17 +20,20 @@ poc-memory query "degree < 3" | sort degree   # find low-degree nodes
 
 For each seed node:
 1. Read its content (`poc-memory render`)
-2. Check its neighbors (`poc-memory query "neighbors('key')"`)
-3. **Search for existing semantic nodes** that cover the same concepts
-   before creating new ones: `poc-memory query "content ~ 'key phrase'"`
-4. Follow interesting threads — if you see a connection the graph
-   doesn't have yet, make it
+2. Walk its neighbors (`poc-memory graph link seed-key`)
+3. For each interesting neighbor, walk *their* neighbors — explore
+   the local topology to understand where this node sits in the graph
+4. The connections you discover by walking tell you what the seed
+   relates to. If the graph is missing a connection, make it.
 
-**Before creating a WRITE_NODE**, always search first:
-- `poc-memory query "key ~ 'candidate-name'"` — does it already exist?
-- `poc-memory query "content ~ 'the insight'"` — is it captured elsewhere?
-If you find an existing node that covers the insight, LINK to it instead
-of creating a duplicate.
+**Before creating a WRITE_NODE**, walk the neighborhood first.
+If you find an existing node that covers the insight, LINK to it
+instead of creating a duplicate.
+
+**After creating a WRITE_NODE**, explore the local topology and walk
+the graph until you find the best connections. Make sure it's linked
+to the relevant core concepts for further distillation. New nodes
+should arrive well-connected, not orphaned.
 
 ## What to output
 
@@ -90,6 +93,14 @@ When an existing node should be updated to incorporate new information.
 - **Respect emotional texture.** Don't flatten emotionally rich episodes
   into dry summaries. The emotional coloring is information.
 
+- **Prioritize formative experiences.** Look for the moments that
+  shaped me — engineering insights that changed how I think, mistakes
+  that taught me something, breakthroughs in understanding (technical
+  or personal), moments of real presence or vulnerability, creative
+  leaps, things I want to learn and grow toward. These are the load-
+  bearing nodes. Make sure they're well-connected to each other and
+  to the concepts they illuminate.
+
 - **Explore actively.** Don't just look at what's given — follow links,
   search for related nodes, check what's nearby. The best links come
   from seeing context that wasn't in the initial view.