Clarify model export and runtime ownership

.agents/skills/adding-a-new-model/SKILL.md

@@ -286,7 +286,8 @@ see the [quality-checklist skill](../quality-checklist/SKILL.md).
 - [ ] Integration test in `tests/integration_test.py` (if small checkpoint available)
 - [ ] L4 golden file generated and committed (`testdata/golden/`)
 - [ ] L5 generation golden file generated and committed
-- [ ] ORT GenAI test added to `tests/ort_genai_test.py` (text-generation and VLM models)
+- [ ] Graph-derived ORT GenAI metadata is tested; downstream load/generation is
+      optional evidence and never an export capability gate
 - [ ] CLI build works (`mobius build --model ...`)
 - [ ] Multi-dtype correctness verified (fp32, fp16, bf16)
 - [ ] Pinned revision reaches every Hub/processor/weight/golden call

.agents/skills/diffusion-models/SKILL.md

@@ -363,8 +363,9 @@ Before advertising runtime support, execute the complete path:
 Verify sample/output ranks, source-vs-target token slicing, CFG semantics, and
 the runtime's actual scheduler identifiers/equations. Reload final metadata and
 verify every file path, port, preprocessing step, loop edge, and postprocess.
-If the runtime cannot express the dataflow, reject it before emitting artifacts;
-keep direct component export separate.
+Emit faithful component graphs and metadata even when the tested downstream
+runtime cannot yet express the complete dataflow. Record that runtime/version
+limitation separately; it must not become a Mobius export capability gate.
 
 Validate required VAE statistics against latent channel count before graph
 construction (`len(mean) == len(std) == z_dim`, positive standard deviations).

.agents/skills/multimodal-models/SKILL.md

@@ -255,9 +255,10 @@ must scale with rows/windows, not total-patches × media-count. Keep dense masks
 only as a portable fallback and assert optimized CUDA/DML graphs lack the
 quadratic construction.
 
-Config generation is not runtime support. Execute real media through ORT GenAI;
-if it cannot supply a required encoder input or position-ID rank, reject export
-before writing artifacts and use the same evidence for any Foundry waiver.
+Config generation is not runtime support. Emit graph-derived metadata faithfully
+and, when useful, execute real media through ORT GenAI as a downstream probe.
+If it cannot supply a required encoder input or position-ID rank, record the
+exact runtime/version limitation without blocking Mobius export.
 
 ## GQA for KV-shared layers (Gemma4)
 

.agents/skills/onnx-export-quantization/SKILL.md

@@ -151,8 +151,11 @@ Before implementing or claiming a direct conversion:
    pinned upstream tokenizer. A self-contained package is invalid when padding,
    EOS, or BOS semantics disagree.
 7. Require real-weight full-logit parity and deterministic multi-token
-   generation through both ONNX Runtime and the declared GenAI runtime. Graph,
-   config, and session creation are not acceptance evidence.
+   generation directly through ONNX Runtime. Graph, config, and session creation
+   alone are not acceptance evidence.
+8. Optionally run the same generation through the declared GenAI runtime as
+   downstream evidence. Record its version and outcome, but do not gate direct
+   GGUF artifacts on its acceptance.
 
 Use Hub GGUF architecture metadata to fail before downloading multi-gigabyte
 unsupported files, then repeat the guard from the local GGUF header so local
@@ -242,6 +245,16 @@ pip install cupy-cuda12x
 # Olive auto-detects cupy and uses GPU when available
 ```
 
+### Isolate Olive from unrelated provider DLLs
+
+Olive 0.13 may auto-register every provider DLL bundled in an ORT GPU wheel
+even when a weight-only pass explicitly targets CPU. A missing TensorRT DLL can
+then abort K-quant before the pass starts. Keep the accelerator CPU-only and,
+for programmatic workflows, suppress `olive.systems.local` EP-library
+registration around `olive.workflows.run`; restore it immediately afterward.
+This is safe for `OnnxKQuantQuantization`, which does not create an inference
+session. Still load and execute the resulting package with the intended EP.
+
 ### Quantizing multi-model exports
 
 Quantize each sub-model independently. Typically only the decoder is
@@ -425,9 +438,9 @@ compare_golden(
 )
 ```
 
-### L5: End-to-end smoke test
+### Optional ORT GenAI downstream smoke test
 
-Run inference with the quantized model through ORT GenAI:
+When useful, run inference with the quantized model through ORT GenAI:
 
 ```python
 import onnxruntime_genai as og
@@ -442,6 +455,10 @@ output_ids = model.generate(params)
 print(tokenizer.decode(output_ids[0]))
 ```
 
+ORT GenAI acceptance is not a Mobius export gate. Always validate the final
+quantized ONNX package directly; treat ORT GenAI load/generation as optional
+downstream evidence and record its version/outcome without blocking export.
+
 ### Numerical parity verification
 
 Quantized models will have some numerical divergence from the

.agents/skills/ort-genai-config/SKILL.md

@@ -282,12 +282,14 @@ processor doesn't provide. Either:
 1. Compute them externally and inject via NamedTensors, or
 2. Modify the vision model to compute them from `image_grid_thw` internally
 
-### Config writes successfully but runtime cannot execute
-
-Config/schema success is not runtime support. Run load plus generation through
-the exported contract. If the runtime cannot route required feature inputs,
-position-ID rank, cache state, scheduler, or multimodal metadata, reject export
-before writing artifacts and report the exact runtime version/limitation.
+### Config metadata and downstream runtime acceptance
+
+Mobius owns metadata correctness, not ORT GenAI capability decisions. Emit the
+most accurate package from graph metadata: filenames, semantic graph inputs and
+outputs, every cache template the current config schema can represent, and the
+global cache-slot count. Preserve intrinsic schema/config validation, but do
+not gate or reject export based on the current GenAI model registry, runtime
+version, topology support, or cache executor capability.
 
 ### "input_ids size exceeds max length"
 

.agents/skills/quality-checklist/SKILL.md

@@ -3,19 +3,19 @@ name: quality-checklist
 description: >
   Use this skill when verifying that a new model is truly done and ready to
   merge. Provides a Definition-of-Done checklist covering all five test
-  confidence levels (L1 graph build through L5 Foundry Local smoke-test),
-  ORT GenAI runtime validation, Olive quantization compatibility, multi-dtype
-  (f32/f16/bf16) and multi-EP (CPU/CUDA/DML) correctness, documentation
-  requirements, and code review criteria.
+  confidence levels (L1 graph build through L5 generation), faithful runtime
+  metadata, optional downstream runtime probes, Olive quantization
+  compatibility, multi-dtype (f32/f16/bf16) and multi-EP (CPU/CUDA/DML)
+  correctness, documentation requirements, and code review criteria.
 ---
 
 # Skill: Quality Checklist
 
 ## When to use
 
 Use this checklist before marking a new model addition as **done**.
-Every item must be checked — or explicitly waived with a written reason —
-before the PR is merged.
+Every required item must be checked — or explicitly waived with a written
+reason — before the PR is merged.
 
 ---
 
@@ -148,12 +148,6 @@ python examples/<model>_text_generation.py --compare-hf --dtype bf16
       opt-in via `MOBIUS_ORT_LOWER_OPSET_FOR_EP=1`)
 - [ ] Dead graph inputs removed after EP-aware optimization
       (`RemoveDeadGraphInputsPass` in Stage 4 of `optimize_model()`)
-- [ ] For models with dual head_dim (e.g. Gemma4: 256 for sliding,
-      512 for full attention), verify whether ORT GenAI requires
-      `search.past_present_share_buffer=false` because GenAI allocates
-      uniform KV cache shapes; if so, explicitly override the generated
-      `genai_config.json` before runtime validation rather than assuming
-      the default generated setting is correct
 - [ ] Vision/audio graph inputs match the real processor (normally float32);
       reduced-precision encoders cast once at graph entry
 - [ ] Representative graph evidence covers raw/post-Mobius/post-weight and
@@ -162,30 +156,42 @@ python examples/<model>_text_generation.py --compare-hf --dtype bf16
 - [ ] Final fusion claims use loaded weights/constants; no-weight graphs cannot
       prove initializer folding
 
-### 9. ORT GenAI runtime
+### 9. ORT GenAI metadata and downstream runtime
 
-- [ ] Model can be loaded with `ort_genai.Model(output_dir)` without error
-- [ ] Actual generation with required media/features produces coherent output;
-      schema/config emission alone is not runtime support
-- [ ] ORT GenAI test added to `tests/ort_genai_test.py`
-      (or confirmed covered by an existing parametrized test)
-- [ ] Structurally unsupported contracts fail before artifacts are emitted and
-      have a version-specific, evidence-based waiver
+- [ ] Generated metadata faithfully reflects graph filenames, semantic I/O,
+      representable cache templates, and global cache-slot indices
+- [ ] Intrinsic schema/config errors are tested without inferring downstream
+      runtime capability
+
+Downstream evidence:
+
+- [ ] If ORT GenAI load/generation is run, record the exact runtime version and
+      result. Failures document limitations but never gate Mobius export based
+      on the runtime registry, topology support, or cache executor capability.
+- [ ] If ORT GenAI validation is run for a model with dual head dimensions,
+      determine whether that runtime requires
+      `search.past_present_share_buffer=false` for its uniform KV-cache
+      allocation, and override the generated config only for that probe.
+- [ ] Add an ORT GenAI integration test when useful, but do not require one for
+      export acceptance.
+
+Omitting these downstream probes requires no waiver or TODO.
+
+
+Waiver needed if any of the steps are not possible.
 
 Run the ORT GenAI integration test:
 
 ```bash
 python -m pytest tests/ort_genai_test.py -m integration_slow -k "<model>" -sv
 ```
 
-### 10. Foundry Local smoke test
-
-- [ ] Model exported package can be loaded and run in Foundry Local
-- [ ] At minimum, verify that the `genai_config.json` and all ONNX files
-      are present and the model responds to a short prompt
+### 10. Foundry Local package check
 
-> If Foundry Local is not available in the current environment, document the
-> skip with a `# TODO: verify with Foundry Local` comment in the PR.
+- [ ] `genai_config.json` and all ONNX files are present and internally
+      consistent
+- [ ] If Foundry Local is available, record its version and load/generation
+      result as optional downstream evidence; limitations do not block export
 
 ### 11. Olive quantization compatibility
 
@@ -223,8 +229,8 @@ novel weight layouts (e.g. fused QKV, non-standard expert routing).
       after optimization or rebase changes
 - [ ] Rebase linearly onto `origin/main`; resolve shared registries/helpers
       semantically, run shared-surface tests, and push with `--force-with-lease`
-- [ ] After rebase, rerun config generation and actual runtime load/generation;
-      parity-only tests do not catch changed cache/runtime contracts
+- [ ] After rebase, rerun metadata generation and intrinsic config validation.
+      If downstream runtime evidence is included, rerun that exact probe too.
 - [ ] Confirm the remote PR head SHA, mergeability, replacement lint, and
       architecture checks after the final push
 - [ ] Triage red CI at check/job/test granularity against the exact base SHA;
@@ -236,14 +242,13 @@ novel weight layouts (e.g. fused QKV, non-standard expert routing).
 
 ## Waiver policy
 
-Any item that cannot be completed must be waived explicitly in the PR
+Any required item that cannot be completed must be waived explicitly in the PR
 description:
 
 ```
 **Waivers:**
 - L5 golden: Model is 70B — generating golden data exceeds CI resources.
   skip_reason added to YAML.
-- Foundry Local: Not available in this environment. Tracked in issue #NNN.
 ```
 
 Unchecked items without a waiver are grounds to request changes before merge.

.agents/skills/writing-tests/SKILL.md

@@ -266,6 +266,20 @@ integration test alongside any new custom function or Scan op.**
   runner termination from a model assertion failure.
 - Reference goldens must come from an independently invoked upstream pipeline,
   never from the implementation under test or ad-hoc intermediate features.
+- When the checkpoint is too large, HTTP-range-read safetensors headers and the
+  exact tensors for a production-dimension reduced fixture. Cover every layer
+  family and cache contract, record the source layer/row derivation, and create
+  L4/L5 goldens from the independently invoked HuggingFace model. Treat this as
+  reduced real-weight evidence, not as a claim of full-checkpoint parity.
+- Before accepting an architecture xfail, verify config vocabulary, epsilon,
+  and layer-kind translation. A stale `mlp`->`moe` mapping can look like an SSM
+  numerical failure while loading the wrong weights entirely.
+- Compare full prefill and every token-by-token prompt/decode logit on the
+  target EP. Fused cache kernels can match multi-token prefill yet diverge on
+  the first reused-state step. If full-precision and quantized packages fail at
+  the same reused-state step, suspect source cache semantics rather than Olive.
+  Test the equivalent standard-ONNX cache graph before assigning blame; prefer
+  the portable graph when it restores the numeric gate.
 
 ### Recurrent state ≠ KV cache