diff --git a/tico/quantization/examples/README.md b/tico/quantization/examples/README.md
index 82d263e5..22b87aec 100644
--- a/tico/quantization/examples/README.md
+++ b/tico/quantization/examples/README.md
@@ -12,15 +12,58 @@ The examples are intentionally small. Real implementation code lives in
 tico/quantization/examples/
 ├── README.md
 ├── quantize.py          # Run a config-driven quantization pipeline
-├── evaluate.py          # Evaluate an FP model or saved fake-quant checkpoint
+├── evaluate.py          # Evaluate an FP model or saved checkpoint
 ├── inspect.py           # Run trace/parity/debug tools
 └── configs/             # Reusable recipe presets
 ```
 
 ## Supported top-level actions
 
+### Which command should I use?
+
+Use `quantize.py` when you want to run a quantization recipe. It loads the
+model, builds calibration inputs, runs enabled `pipeline` stages such as GPTQ,
+PTQ, SpinQuant, or CLE, and then optionally evaluates and exports the resulting
+model.
+
+Use `evaluate.py` when you only want to evaluate a floating-point model or an
+already saved checkpoint. `evaluate.py` does **not** run `pipeline` stages from
+the config. If the config contains enabled stages such as `gptq` or `ptq`, they
+are ignored by `evaluate.py`.
+
+Use `inspect.py` for debug-oriented workflows such as trace, parity, runtime
+inspection, and wrapper-level smoke checks.
+
+Summary:
+
+| Command | Runs `pipeline` stages? | Builds calibration inputs? | Evaluates? | Exports? |
+|---|---:|---:|---:|---:|
+| `quantize.py` | Yes | Yes | If `evaluation.enabled=true` | If `export.enabled=true` |
+| `evaluate.py` | No | No | Yes | No |
+| `inspect.py` | Mode-dependent | Mode-dependent | Debug only | Debug only |
+
+Common usage patterns:
+
+```bash
+# Run GPTQ/PTQ and evaluate the quantized model in the same process.
+python -m tico.quantization.examples.quantize \
+  --config tico/quantization/examples/configs/llama_gptq_ptq.yaml \
+  --set evaluation.enabled=true \
+  --set export.enabled=false
+```
+
+```bash
+# Evaluate a saved checkpoint without running quantization again.
+python -m tico.quantization.examples.evaluate \
+  --config tico/quantization/examples/configs/llama_gptq_ptq.yaml \
+  --checkpoint ./out/llama/quantized_model.pt
+```
+
 ### Quantize
 
+`quantize.py` is the command that executes the recipe pipeline. It runs the
+enabled stages under `pipeline` in the order they appear in the config.
+
 ```bash
 python -m tico.quantization.examples.quantize \
   --config tico/quantization/examples/configs/llama_gptq_ptq.yaml \
@@ -39,14 +82,64 @@ python -m tico.quantization.examples.quantize \
   --model Qwen/Qwen3-VL-2B-Instruct
 ```
 
+Examples:
+
+```bash
+# Run quantization only. Skip evaluation and export.
+python -m tico.quantization.examples.quantize \
+  --config tico/quantization/examples/configs/llama_gptq_ptq.yaml \
+  --set evaluation.enabled=false \
+  --set export.enabled=false
+```
+
+```bash
+# Run quantization and evaluate the quantized model. Skip export.
+python -m tico.quantization.examples.quantize \
+  --config tico/quantization/examples/configs/llama_gptq_ptq.yaml \
+  --set evaluation.enabled=true \
+  --set export.enabled=false
+```
+
+```bash
+# Run quantization and export configured artifacts. Skip evaluation.
+python -m tico.quantization.examples.quantize \
+  --config tico/quantization/examples/configs/llama_gptq_ptq.yaml \
+  --set evaluation.enabled=false \
+  --set export.enabled=true \
+  --output-dir ./out/llama
+```
+
 ### Evaluate
 
+`evaluate.py` evaluates the model loaded by the adapter, or the model loaded
+from `--checkpoint` when one is provided. It does not prepare, calibrate,
+convert, or export the model.
+
+Running this command with a GPTQ/PTQ config evaluates the floating-point model,
+because the `pipeline` section is not executed by `evaluate.py`:
+
+```bash
+python -m tico.quantization.examples.evaluate \
+  --config tico/quantization/examples/configs/llama_gptq_ptq.yaml
+```
+
+To evaluate a quantized result, pass a saved checkpoint:
+
 ```bash
 python -m tico.quantization.examples.evaluate \
   --config tico/quantization/examples/configs/llama_gptq_ptq.yaml \
   --checkpoint ./out/llama/quantized_model.pt
 ```
 
+Task overrides are supported:
+
+```bash
+python -m tico.quantization.examples.evaluate \
+  --config tico/quantization/examples/configs/llama_gptq_ptq.yaml \
+  --checkpoint ./out/llama/quantized_model.pt \
+  --tasks winogrande,arc_easy
+```
+
 ### Inspect / debug
 
 ```bash
@@ -121,6 +214,65 @@ module.name: mean|diff|=..., max|diff|=...
 is omitted, trace mode records all named modules. Use a small calibration sample
 count before tracing large Qwen3-VL models.
 
+#### Wrapper smoke mode
+
+Wrapper smoke mode runs module-level sanity checks for quantization wrappers.
+It is useful when you want to quickly validate `prepare -> calibrate -> convert`,
+numerical parity, plotting, and optional Circle export for a single wrapped
+module.
+
+List available wrapper smoke cases:
+
+```bash
+python -m tico.quantization.examples.inspect \
+  --mode wrapper-smoke \
+  --list-cases
+```
+
+Example output:
+
+```text
+Available wrapper smoke cases:
+
+  nn_linear
+  nn_conv3d
+  nn_conv3d_special_case
+  nn_layernorm
+  nn_tied_embedding
+
+  llama_attention_prefill
+  llama_attention_decode
+  llama_mlp
+  llama_decoder_layer_prefill
+  llama_decoder_layer_decode
+
+  qwen3_vl_text_attention
+  qwen3_vl_text_mlp
+  qwen3_vl_text_decoder_layer
+  qwen3_vl_text_model
+  qwen3_vl_vision_attention
+```
+
+Run one case:
+
+```bash
+python -m tico.quantization.examples.inspect \
+  --config tico/quantization/examples/configs/wrapper_smoke.yaml \
+  --mode wrapper-smoke \
+  --case llama_attention_prefill
+```
+
+Run one case with Circle export:
+
+```bash
+python -m tico.quantization.examples.inspect \
+  --config tico/quantization/examples/configs/wrapper_smoke.yaml \
+  --mode wrapper-smoke \
+  --case llama_attention_prefill \
+  --export circle \
+  --output-dir ./out/wrapper_smoke \
+  --strict
+```
 
 ## CLI overrides
 
@@ -134,6 +286,51 @@ python -m tico.quantization.examples.quantize \
   --set export.enabled=false
 ```
 
+Values are parsed as YAML-like scalars when possible:
+
+```bash
+--set evaluation.enabled=true
+--set calibration.n_samples=1
+--set model.hf_token=null
+--set runtime.dtype=float32
+```
+
+List indices are zero-based. This is most useful for toggling entries in the
+`pipeline` list:
+
+```yaml
+pipeline:
+  - name: spinquant       # pipeline.0
+    enabled: false
+
+  - name: cle             # pipeline.1
+    enabled: false
+
+  - name: gptq            # pipeline.2
+    enabled: true
+
+  - name: ptq             # pipeline.3
+    enabled: true
+```
+
+For the example above, enable SpinQuant from the command line with:
+
+```bash
+python -m tico.quantization.examples.quantize \
+  --config tico/quantization/examples/configs/llama_gptq_ptq.yaml \
+  --set pipeline.0.enabled=true
+```
+
+You can also override fields inside later stages by index. For example, if the
+PTQ stage is `pipeline.3`, change its SpinQuant rotation weight bit-width with:
+
+```bash
+python -m tico.quantization.examples.quantize \
+  --config tico/quantization/examples/configs/llama_gptq_ptq.yaml \
+  --set pipeline.0.enabled=true \
+  --set pipeline.3.spin_rotation_weight_bits=8
+```
+
 Convenience aliases are also available:
 
 ```bash
@@ -142,8 +339,34 @@ Convenience aliases are also available:
 --output-dir  # overrides export.output_dir, quantize.py only
 ```
 
-Prefer adding a dedicated config preset when the change modifies list-valued
-sections such as `pipeline`.
+Prefer adding a dedicated config preset when the change adds, removes, or
+reorders list-valued sections such as `pipeline`. Command-line list overrides
+are convenient for toggling existing stages or changing simple scalar fields,
+but they are easy to misuse when the stage order differs between configs.
+
+Good command-line overrides:
+
+```bash
+--set pipeline.0.enabled=true
+--set pipeline.2.weight_bits=4
+--set pipeline.3.activation_dtype=int16
+```
+
+Prefer a new config file for structural changes:
+
+```yaml
+pipeline:
+  - name: spinquant
+    enabled: true
+
+  - name: gptq
+    enabled: true
+    weight_bits: 4
+
+  - name: ptq
+    enabled: true
+    activation_dtype: int16
+```
 
 ## Developer rule: do not add one script per model or algorithm
 
@@ -263,3 +486,11 @@ python -m tico.quantization.examples.inspect \
   --mode trace \
   --set calibration.n_samples=1
 ```
+
+```bash
+python -m tico.quantization.examples.inspect \
+  --config tico/quantization/examples/configs/wrapper_smoke.yaml \
+  --mode wrapper-smoke \
+  --case nn_linear \
+  --no-plot
+```