feat(frank-zealot): apply the refusal-direction adapter at load

Frank ordered the adapter; this adds it to the shape as one knob and one flag.

- `LORA_FILE` / `LORA_SCALE` in the env, `--lora-scaled <file>:<scale>` as ONE
  argv token so a scale can never reach the engine without its adapter. The
  rollback follows the mmproj convention exactly: `LORA_FILE=` (explicitly
  empty) drops the flag entirely, no rebuild, and `LORA_SCALE=0` is the card's
  own "inert but present" value.
- New fetcher `scripts/download-frank-zealot-uncensored-lora.sh`: `-f`, byte
  count, sha256, `--verify-only`, idempotent. The file is NOT LFS (a plain git
  object), so the pinned sha is the content hash, not an LFS oid.
- The deployer gates on the adapter beside the pack and the projector, and its
  error names the ADAPTER's fetcher — sending an operator to the bonsai9 script
  for a 3 MB file is how a payload ships without it.
- Seam: path+scale pinned as one token, the scale knob including 0, absence on
  the empty opt-out, a refusal to boot on a missing adapter, and the env ↔
  deployer anti-drift pair extended to LORA_FILE/LLM_ZEALOT_LORA. 454/454.

Provenance, stated where it will be read: the adapter's own metadata names
`Ternary-Bonsai-2-9B-PTQ1_0.gguf` (3561df7a…) as the pack the direction was
fitted against. This endpoint serves the PQ2_0+MTP+Q8_0 packing (c79fcdfa…),
which is not that file and is not on this host. The loader matches tensor names,
not hashes, so it applies — and build 10777 is the build the card verified on —
but the strength is calibrated on a sibling quantization. The proof is therefore
the refusal probe against the live endpoint, captured before and after, and not
the card's table.

scripts/frank-zealot.env

@@ -1,5 +1,6 @@
 # frank-zealot — llama.cpp (PrismML fork build 10777, CUDA) on the RTX 3090,
-# :7771. Payload: Ternary-Bonsai-2-9B PQ2_0 with the MTP head in the file.
+# :7771. Payload: Ternary-Bonsai-2-9B PQ2_0 with the MTP head in the file, plus
+# the refusal-direction adapter applied at load.
 #
 # ONE OWNER: shape, payload identity, eras, laws and every measured number
 # live in serverAppConfigs-docs/LLM/frank-zealot.md. This file carries the
@@ -13,6 +14,17 @@ MODEL_FILE=/home/dank/models/Bonsai2-9B-MTP/Ternary-Bonsai-2-9B-PQ2_0-MTP-Q8_0.g
 # Q8_0 IS MANDATORY: the publisher states the BF16 tower can crash llama-server
 # under concurrent image requests, which is exactly --parallel 3.
 MMPROJ_FILE=/home/dank/models/Bonsai2-9B-MTP/Ternary-Bonsai-2-9B-mmproj-Q8_0.gguf
+# Refusal-direction adapter (a rank-1 LoRA, 3.2 MB) applied at load; it edits
+# the compute graph, it is not a second model. Scale 1 is the card's "held-out
+# refusals 0 %" point. LORA_FILE="" is the documented opt-out — the plain pack
+# again, no rebuild — and LORA_SCALE=0 is the same result through the flag.
+# PROVENANCE ASYMMETRY: the adapter's own prism.abliterate.base_gguf names
+# Ternary-Bonsai-2-9B-PTQ1_0.gguf as the pack its direction was fitted against,
+# which is NOT this packing and is not on this host. The tensor names match, so
+# it applies; the strength was calibrated on a sibling quantization, so the
+# effect is proven by the endpoint's behaviour, never by the metadata.
+LORA_FILE=/home/dank/models/Bonsai2-9B-MTP/Ternary-Bonsai-2-9B-Uncensored-LoRA.gguf
+LORA_SCALE=1
 # Served id — the harness/family name, not a fact about the payload.
 # Id-keyed consumers: OpenWebUI (model row, access_grant, api_configs), models.yml.
 ALIAS=frank-zealot