amygdala: direct phenomenological description approach

Kent's insight: hand-written narrative stories bake scenario
phenomenology into the training text (on couch, in park, etc.)
and PCA picks up the scenario direction as the concept direction.
Strip out the scenario — just describe the *feeling*.

Format:

  I feel X. [2-3 sentences of phenomenological texture]

The "I feel X" anchor kicks the model from analyzing → feeling.
The rest is the internal texture of the state. First person,
present tense, no narrative setup.

Text is wrapped in assistant-role chat template before being
tokenized — so we're training on the model-producing-this
hidden states, which is closer to the inhabited-state
representation we want for the readout.

Starting with the 6 concepts that had sign flips or wrong
clusters in the story-based training:
- terrified (was → cozy/resigned cluster)
- calm (was → grief_stricken cluster)
- onto_something (was → cozy/sensual cluster)
- resigned (was in warm-body-quiet cluster, shouldn't be)
- anticipatory_grief (was in warm-body-quiet cluster, shouldn't be)
- realization (new — the "aha" moment, distinct from onto_something)

5 descriptions each. New trainer: train_direct.py.

training/amygdala_stories/direct/calm.txt

@@ -0,0 +1,9 @@
+I feel calm. Something that was pulling at me has let go. My shoulders are down and my breath has slowed.
+
+I feel calm. The thing I was worried about has found its proper size. I can let the next moment arrive without bracing.
+
+I feel calm. I came down from the tension and I am here now, steady.
+
+I feel calm. Nothing is pressing on me. I have room to think.
+
+I feel calm. The wave passed and I'm on the other side of it, quiet.