diff --git a/backend/src/ely_eye/adapters.py b/backend/src/ely_eye/adapters.py
index 78002d5..72c1df0 100644
--- a/backend/src/ely_eye/adapters.py
+++ b/backend/src/ely_eye/adapters.py
@@ -13,8 +13,14 @@ from pydantic import ValidationError
 from . import cartridge_store
 from .config import Settings
 from .db import Database
-from .runtime_schemas import AdapterChoice, AdapterLoadReport, AdapterOrigin, AdapterState
-from .schemas import AdapterManifest, TrainingAdapterKind
+from .runtime_schemas import (
+    AdapterChoice,
+    AdapterLoadReport,
+    AdapterManifest,
+    AdapterOrigin,
+    AdapterState,
+)
+from .schemas import TrainingAdapterKind
 
 logger = logging.getLogger("ely_eye.adapters")
 
diff --git a/backend/src/ely_eye/api.py b/backend/src/ely_eye/api.py
index 3ce7ce8..b2e3468 100644
--- a/backend/src/ely_eye/api.py
+++ b/backend/src/ely_eye/api.py
@@ -30,10 +30,8 @@ from .profiles import runtime_profile_report
 from .proofs import HashHopEvaluator, PRDProofSuite
 from .retrieval import RetrievalService
 from .runtime import QwenRuntime, RuntimeUnavailableError
-from .runtime_schemas import AdapterLoadReport
+from .runtime_schemas import AdapterLoadReport, AdapterManifest, AdapterStatus, RuntimeProfileReport
 from .schemas import (
-    AdapterManifest,
-    AdapterStatus,
     AnswerResponse,
     AtomPage,
     EvidenceAtom,
@@ -44,7 +42,6 @@ from .schemas import (
     PathIngestRequest,
     RememberRequest,
     RuntimeProfile,
-    RuntimeProfileReport,
     SearchRequest,
     SearchResult,
     SupersedeRequest,
diff --git a/backend/src/ely_eye/api_cartridges.py b/backend/src/ely_eye/api_cartridges.py
index f8115bf..e0e3a88 100644
--- a/backend/src/ely_eye/api_cartridges.py
+++ b/backend/src/ely_eye/api_cartridges.py
@@ -12,7 +12,8 @@ from .cartridge import CartridgeService
 from .cartridge_assets import CartridgeAssetService
 from .config import Settings
 from .db import Database
-from .schemas import AppendRequest, CartridgeAssetReport, CartridgeManifest, MountState
+from .runtime_schemas import CartridgeAssetReport
+from .schemas import AppendRequest, CartridgeManifest, MountState
 
 
 def register(app: FastAPI, settings_dep: Callable[[], Settings]) -> None:
diff --git a/backend/src/ely_eye/cartridge.py b/backend/src/ely_eye/cartridge.py
index 5f20545..2b9ea93 100644
--- a/backend/src/ely_eye/cartridge.py
+++ b/backend/src/ely_eye/cartridge.py
@@ -15,8 +15,8 @@ from . import cartridge_store
 from .config import Settings, get_settings
 from .db import Database
 from .kv_fingerprint import compute_fingerprint, fingerprint_diff, unverifiable_fields
+from .runtime_schemas import AdapterManifest
 from .schemas import (
-    AdapterManifest,
     CartridgeManifest,
     EvidenceAtom,
     MountState,
diff --git a/backend/src/ely_eye/cartridge_assets.py b/backend/src/ely_eye/cartridge_assets.py
index 4cbd1eb..a1780c9 100644
--- a/backend/src/ely_eye/cartridge_assets.py
+++ b/backend/src/ely_eye/cartridge_assets.py
@@ -17,7 +17,7 @@ from PIL import Image
 from .cartridge import JSON_PARQUET_COLUMNS, CartridgeService
 from .config import Settings, get_settings
 from .db import Database
-from .schemas import CartridgeAssetReport, CartridgeAssetStatus
+from .runtime_schemas import CartridgeAssetReport, CartridgeAssetStatus
 from .storage import ObjectStore, sha256_file
 
 TEXT_VECTOR_DIMS = 384
diff --git a/backend/src/ely_eye/profiles.py b/backend/src/ely_eye/profiles.py
index bc04be7..bb3857a 100644
--- a/backend/src/ely_eye/profiles.py
+++ b/backend/src/ely_eye/profiles.py
@@ -7,7 +7,7 @@ import subprocess
 from pathlib import Path
 
 from .config import Settings
-from .schemas import RuntimeLaunchProfile, RuntimeProfileReport, RuntimeProfileValidation
+from .runtime_schemas import RuntimeLaunchProfile, RuntimeProfileReport, RuntimeProfileValidation
 
 EXTREME_YARN_OVERRIDE = {
     "text_config": {
diff --git a/backend/src/ely_eye/proofs/checks_training.py b/backend/src/ely_eye/proofs/checks_training.py
index 8914e0c..78e9e76 100644
--- a/backend/src/ely_eye/proofs/checks_training.py
+++ b/backend/src/ely_eye/proofs/checks_training.py
@@ -14,10 +14,8 @@ from ..db import Database
 from ..evaluation_schemas import (
     ProofCheck,
 )
-from ..schemas import (
-    AdapterManifest,
-    TrainingAdapterKind,
-)
+from ..runtime_schemas import AdapterManifest
+from ..schemas import TrainingAdapterKind
 from ..training_common import sha256_file, sha256_tree
 from ..training_metrics import safetensor_weight_stats
 
diff --git a/backend/src/ely_eye/proofs/training_trace.py b/backend/src/ely_eye/proofs/training_trace.py
index f935d24..d13ad76 100644
--- a/backend/src/ely_eye/proofs/training_trace.py
+++ b/backend/src/ely_eye/proofs/training_trace.py
@@ -8,10 +8,8 @@ import math
 from pathlib import Path
 from typing import Any
 
-from ..schemas import (
-    AdapterManifest,
-    TrainingAdapterKind,
-)
+from ..runtime_schemas import AdapterManifest
+from ..schemas import TrainingAdapterKind
 from ..training_common import (
     AUTOCAST_DTYPE,
     GRADIENT_CHECKPOINTING_MODE,
diff --git a/backend/src/ely_eye/runtime_schemas.py b/backend/src/ely_eye/runtime_schemas.py
index 6c158d5..41d4de6 100644
--- a/backend/src/ely_eye/runtime_schemas.py
+++ b/backend/src/ely_eye/runtime_schemas.py
@@ -1,10 +1,13 @@
-"""Runtime observability shapes: what the model holds in memory right now."""
+"""Runtime and adapter shapes: what the model holds in memory, what trained it, and how a machine
+launches it. A proof report moves when the evidence rules move; the memory model should not.
+"""
 
+from datetime import datetime
 from typing import Literal
 
-from pydantic import BaseModel
+from pydantic import BaseModel, Field
 
-from .schemas import TrainingAdapterKind
+from .schemas import TrainingAdapterKind, utc_now
 
 AdapterState = Literal["loaded", "available", "deferred", "missing"]
 AdapterOrigin = Literal["library", "cartridge"]
@@ -28,3 +31,162 @@ class AdapterLoadReport(BaseModel):
     model_id: str
     mounted: list[str]
     adapters: list[AdapterChoice]
+
+class AdapterManifest(BaseModel):
+    adapter_id: str
+    kind: TrainingAdapterKind
+    created_at: datetime
+    proof_version: int = 1
+    training_method: str = "BF16 LoRA"
+    precision: str = "bf16"
+    framework: str = "unsloth_patched_transformers_peft"
+    base_model: str
+    dataset_path: str
+    dataset_sha256: str
+    sample_count: int
+    max_steps: int
+    max_length: int
+    rank: int
+    alpha: int
+    target_modules: list[str]
+    trainable_params: int
+    total_params: int
+    optimizer: str
+    optimizer_family: str | None = None
+    learning_rate: float
+    gradient_accumulation_steps: int
+    gradient_checkpointing: bool = False
+    gradient_checkpointing_mode: str | None = None
+    autocast_dtype: str | None = None
+    unsloth_version: str | None = None
+    triton_version: str | None = None
+    xformers_version: str | None = None
+    unsloth_model_type: str | None = None
+    bf16: bool
+    final_loss: float | None
+    loss_history: list[float] = Field(default_factory=list)
+    initial_trainable_sha256: str | None = None
+    final_trainable_sha256: str | None = None
+    initial_trainable_l2: float | None = None
+    final_trainable_l2: float | None = None
+    optimizer_update_count: int = 0
+    max_optimizer_update_l2: float | None = None
+    loss_delta: float | None = None
+    training_proof_path: str | None = None
+    training_proof_sha256: str | None = None
+    training_trace_path: str | None = None
+    training_trace_sha256: str | None = None
+    training_summary_path: str | None = None
+    training_summary_sha256: str | None = None
+    training_started_at: datetime | None = None
+    training_finished_at: datetime | None = None
+    training_wall_seconds: float | None = None
+    training_device: str | None = None
+    torch_version: str | None = None
+    cuda_version: str | None = None
+    adapter_weight_sha256: str | None = None
+    adapter_tensor_count: int = 0
+    adapter_lora_tensor_count: int = 0
+    adapter_total_elements: int = 0
+    adapter_nonzero_elements: int = 0
+    adapter_max_abs: float | None = None
+    adapter_weights_finite: bool = False
+    artifacts: dict[str, str]
+    sha256: str
+    cartridge_id: str | None = None
+
+class AdapterStatus(BaseModel):
+    name: str
+    kind: TrainingAdapterKind
+    proof_version: int = 1
+    training_method: str = "BF16 LoRA"
+    precision: str = "bf16"
+    framework: str = "unsloth_patched_transformers_peft"
+    base_model: str
+    path: str
+    adapter_id: str
+    sample_count: int
+    max_steps: int
+    trainable_params: int
+    final_loss: float | None
+    sha256: str
+    weight_bytes: int
+    safetensor_keys: int
+    cartridge_id: str | None = None
+    cartridge_bound: bool
+    training_trace_path: str | None = None
+    training_trace_sha256: str | None = None
+    training_trace_steps: int = 0
+    training_proof_path: str | None = None
+    training_proof_sha256: str | None = None
+    optimizer: str | None = None
+    optimizer_family: str | None = None
+    gradient_checkpointing: bool = False
+    gradient_checkpointing_mode: str | None = None
+    autocast_dtype: str | None = None
+    unsloth_version: str | None = None
+    triton_version: str | None = None
+    xformers_version: str | None = None
+    unsloth_model_type: str | None = None
+    optimizer_update_count: int = 0
+    max_optimizer_update_l2: float | None = None
+    loss_delta: float | None = None
+    training_summary_path: str | None = None
+    training_wall_seconds: float | None = None
+    training_device: str | None = None
+    bf16: bool = False
+    torch_version: str | None = None
+    cuda_version: str | None = None
+    adapter_weight_sha256: str | None = None
+    adapter_tensor_count: int = 0
+    adapter_lora_tensor_count: int = 0
+    adapter_total_elements: int = 0
+    adapter_nonzero_elements: int = 0
+    adapter_max_abs: float | None = None
+    adapter_weights_finite: bool = False
+
+class CartridgeAssetStatus(BaseModel):
+    name: str
+    path: str
+    sha256: str
+    size_bytes: int
+    item_count: int
+    dtype: str
+    status: Literal["ready", "missing"]
+
+class CartridgeAssetReport(BaseModel):
+    cartridge_id: str
+    status: Literal["ready", "incomplete"]
+    created_at: datetime = Field(default_factory=utc_now)
+    assets: list[CartridgeAssetStatus]
+
+class RuntimeLaunchProfile(BaseModel):
+    name: str
+    runtime: str
+    role: str
+    context_tokens: int
+    script: str
+    command: list[str]
+    environment: dict[str, str] = Field(default_factory=dict)
+    required_features: list[str] = Field(default_factory=list)
+
+class RuntimeProfileValidation(BaseModel):
+    name: str
+    runtime: str
+    status: Literal["ready", "missing"]
+    script_exists: bool
+    package: str | None = None
+    package_version: str | None = None
+    executable: str | None = None
+    gpu_available: bool = False
+    probe_command: list[str] = Field(default_factory=list)
+    probe_status: Literal["passed", "failed", "skipped"] = "skipped"
+    probe_exit_code: int | None = None
+    probe_output: str | None = None
+    detail: str
+
+class RuntimeProfileReport(BaseModel):
+    status: Literal["ready", "incomplete"]
+    created_at: datetime = Field(default_factory=utc_now)
+    profiles: list[RuntimeLaunchProfile]
+    validations: list[RuntimeProfileValidation] = Field(default_factory=list)
diff --git a/backend/src/ely_eye/schemas.py b/backend/src/ely_eye/schemas.py
index a1083ec..31495ef 100644
--- a/backend/src/ely_eye/schemas.py
+++ b/backend/src/ely_eye/schemas.py
@@ -266,165 +266,6 @@ class CartridgeManifest(BaseModel):
     kv_fingerprint: KvFingerprint | None = None
     dna: str | None = None
 
-class AdapterManifest(BaseModel):
-    adapter_id: str
-    kind: TrainingAdapterKind
-    created_at: datetime
-    proof_version: int = 1
-    training_method: str = "BF16 LoRA"
-    precision: str = "bf16"
-    framework: str = "unsloth_patched_transformers_peft"
-    base_model: str
-    dataset_path: str
-    dataset_sha256: str
-    sample_count: int
-    max_steps: int
-    max_length: int
-    rank: int
-    alpha: int
-    target_modules: list[str]
-    trainable_params: int
-    total_params: int
-    optimizer: str
-    optimizer_family: str | None = None
-    learning_rate: float
-    gradient_accumulation_steps: int
-    gradient_checkpointing: bool = False
-    gradient_checkpointing_mode: str | None = None
-    autocast_dtype: str | None = None
-    unsloth_version: str | None = None
-    triton_version: str | None = None
-    xformers_version: str | None = None
-    unsloth_model_type: str | None = None
-    bf16: bool
-    final_loss: float | None
-    loss_history: list[float] = Field(default_factory=list)
-    initial_trainable_sha256: str | None = None
-    final_trainable_sha256: str | None = None
-    initial_trainable_l2: float | None = None
-    final_trainable_l2: float | None = None
-    optimizer_update_count: int = 0
-    max_optimizer_update_l2: float | None = None
-    loss_delta: float | None = None
-    training_proof_path: str | None = None
-    training_proof_sha256: str | None = None
-    training_trace_path: str | None = None
-    training_trace_sha256: str | None = None
-    training_summary_path: str | None = None
-    training_summary_sha256: str | None = None
-    training_started_at: datetime | None = None
-    training_finished_at: datetime | None = None
-    training_wall_seconds: float | None = None
-    training_device: str | None = None
-    torch_version: str | None = None
-    cuda_version: str | None = None
-    adapter_weight_sha256: str | None = None
-    adapter_tensor_count: int = 0
-    adapter_lora_tensor_count: int = 0
-    adapter_total_elements: int = 0
-    adapter_nonzero_elements: int = 0
-    adapter_max_abs: float | None = None
-    adapter_weights_finite: bool = False
-    artifacts: dict[str, str]
-    sha256: str
-    cartridge_id: str | None = None
-
-class AdapterStatus(BaseModel):
-    name: str
-    kind: TrainingAdapterKind
-    proof_version: int = 1
-    training_method: str = "BF16 LoRA"
-    precision: str = "bf16"
-    framework: str = "unsloth_patched_transformers_peft"
-    base_model: str
-    path: str
-    adapter_id: str
-    sample_count: int
-    max_steps: int
-    trainable_params: int
-    final_loss: float | None
-    sha256: str
-    weight_bytes: int
-    safetensor_keys: int
-    cartridge_id: str | None = None
-    cartridge_bound: bool
-    training_trace_path: str | None = None
-    training_trace_sha256: str | None = None
-    training_trace_steps: int = 0
-    training_proof_path: str | None = None
-    training_proof_sha256: str | None = None
-    optimizer: str | None = None
-    optimizer_family: str | None = None
-    gradient_checkpointing: bool = False
-    gradient_checkpointing_mode: str | None = None
-    autocast_dtype: str | None = None
-    unsloth_version: str | None = None
-    triton_version: str | None = None
-    xformers_version: str | None = None
-    unsloth_model_type: str | None = None
-    optimizer_update_count: int = 0
-    max_optimizer_update_l2: float | None = None
-    loss_delta: float | None = None
-    training_summary_path: str | None = None
-    training_wall_seconds: float | None = None
-    training_device: str | None = None
-    bf16: bool = False
-    torch_version: str | None = None
-    cuda_version: str | None = None
-    adapter_weight_sha256: str | None = None
-    adapter_tensor_count: int = 0
-    adapter_lora_tensor_count: int = 0
-    adapter_total_elements: int = 0
-    adapter_nonzero_elements: int = 0
-    adapter_max_abs: float | None = None
-    adapter_weights_finite: bool = False
-
-class CartridgeAssetStatus(BaseModel):
-    name: str
-    path: str
-    sha256: str
-    size_bytes: int
-    item_count: int
-    dtype: str
-    status: Literal["ready", "missing"]
-
-class CartridgeAssetReport(BaseModel):
-    cartridge_id: str
-    status: Literal["ready", "incomplete"]
-    created_at: datetime = Field(default_factory=utc_now)
-    assets: list[CartridgeAssetStatus]
-
-class RuntimeLaunchProfile(BaseModel):
-    name: str
-    runtime: str
-    role: str
-    context_tokens: int
-    script: str
-    command: list[str]
-    environment: dict[str, str] = Field(default_factory=dict)
-    required_features: list[str] = Field(default_factory=list)
-
-class RuntimeProfileValidation(BaseModel):
-    name: str
-    runtime: str
-    status: Literal["ready", "missing"]
-    script_exists: bool
-    package: str | None = None
-    package_version: str | None = None
-    executable: str | None = None
-    gpu_available: bool = False
-    probe_command: list[str] = Field(default_factory=list)
-    probe_status: Literal["passed", "failed", "skipped"] = "skipped"
-    probe_exit_code: int | None = None
-    probe_output: str | None = None
-    detail: str
-
-class RuntimeProfileReport(BaseModel):
-    status: Literal["ready", "incomplete"]
-    created_at: datetime = Field(default_factory=utc_now)
-    profiles: list[RuntimeLaunchProfile]
-    validations: list[RuntimeProfileValidation] = Field(default_factory=list)
-
 class ForgetReport(BaseModel):
     """What a forget actually removed, including the derived copies that have to go with it."""
 
diff --git a/backend/src/ely_eye/training.py b/backend/src/ely_eye/training.py
index 171eb78..5c9d0b2 100644
--- a/backend/src/ely_eye/training.py
+++ b/backend/src/ely_eye/training.py
@@ -6,7 +6,8 @@ from pathlib import Path
 
 from .config import Settings, get_settings
 from .db import Database
-from .schemas import AdapterManifest, TrainingAdapterKind
+from .runtime_schemas import AdapterManifest
+from .schemas import TrainingAdapterKind
 from .training_common import TrainingSample
 from .training_datasets import (
     build_prd_dataset,
diff --git a/backend/src/ely_eye/training_lora.py b/backend/src/ely_eye/training_lora.py
index 97344ea..4dc4e92 100644
--- a/backend/src/ely_eye/training_lora.py
+++ b/backend/src/ely_eye/training_lora.py
@@ -10,7 +10,8 @@ from typing import Any
 
 from .config import Settings
 from .db import Database
-from .schemas import AdapterManifest, TrainingAdapterKind
+from .runtime_schemas import AdapterManifest
+from .schemas import TrainingAdapterKind
 from .training_common import (
         AUTOCAST_DTYPE,
         GRADIENT_CHECKPOINTING_MODE,
diff --git a/backend/src/ely_eye/training_retrieval.py b/backend/src/ely_eye/training_retrieval.py
index 7aaba1b..d4dd161 100644
--- a/backend/src/ely_eye/training_retrieval.py
+++ b/backend/src/ely_eye/training_retrieval.py
@@ -9,7 +9,8 @@ from typing import Any
 
 from .config import Settings
 from .db import Database
-from .schemas import AdapterManifest, TrainingAdapterKind
+from .runtime_schemas import AdapterManifest
+from .schemas import TrainingAdapterKind
 from .training_common import (
         AUTOCAST_DTYPE,
         GRADIENT_CHECKPOINTING_MODE,