Delete every knob the fixed profiles cannot honor

The CLI still advertised --model, --steps, --guidance-scale, --device and a
deprecated --auto. Each pinned a value the two surviving profiles fix -- the
model stack, the per-stage distilled schedule, CFG 1.0, CUDA -- so the only
outcome any of them had was an error raised several frames below the caller,
under a message naming an internal profile. A flag whose sole result is a
refusal is worse than no flag: it advertises a capability that does not exist,
and it lets a wrapper thread a value that will silently do nothing. They are
gone from the parser, from InvisibleEngine, and from WatermarkRemover, so the
failure is now a TypeError or a Click "No such option" at the point the caller
can act on.

The install hint was wrong in the same way. is_available() checked torch and
diffusers, then told the user to install [diffusion] -- which contains neither
DiffSynth nor the Z-Image face stage both profiles run. Following the advice
produced a second, different failure. The module list and the extra name now
live once in watermark_profiles (REMOVAL_MODULES, INVISIBLE_EXTRA) and are read
by both the CLI gate and the remover's precondition, which cannot drift apart
because they are the same tuple.

The adaptive-polish default moved out of the argument parser. It was resolved by
reading Click's parameter source, which put per-profile data in the CLI layer,
left the engine declaring the opposite default (False vs True) so a library
caller and a CLI caller on one profile got different output, and lost the polish
entirely for anything that supplies the flag non-interactively. The flag is now
tri-state (default=None) and resolve_adaptive_polish owns the per-profile
answer. The seed follows the same rule: the CLI stopped pre-resolving it.

Dead code removed with it: six scan_*_video wrappers and the _scan_video helper
none of them had a caller for, PNG_METADATA_KEYS, feather_region_composite and
the remover region path that was only reachable from a no-caller convenience
wrapper, remove_watermark_batch on both layers, try_empty_device_cache, the
_generate/_run_qwen_zimage pass-through pair, self.model_id, and the _internal
PEP 562 shim that no caller ever went through. get_device now answers cuda or
cpu only: mps and xpu travelled one frame to the same CUDA-only refusal while
costing a device probe each, and that refusal now names the resolved device, so
device=None on a CUDA-less host says 'cpu' rather than 'None'. The XPU wheel
index went with them.

Docs: README, cli, installation, python-api, supported-signals,
known-limitations and module-internals all still described the removed profiles,
the CPU/MPS/XPU ladder, a `default`->`sdxl` alias, and the wrong extra.
known-limitations still listed the retired SDXL strength ladder as current.
scripts/smoke_matrix.py and real_examples_e2e.py drove --device mps.

Next release is 0.25.0, not a patch: this removes public parameters and
narrows a published extra on top of the released 0.24.0.

pre-commit: 1) maintain.sh - exit 0 (1091 tests, Pyright 0 errors, no
vulnerabilities); 2) /simplify - 4 agents, 11 findings applied, 2 skipped
(dropping the `device` parameter entirely, which raiw-app pins; folding
diffsynth into the `diffusion` extra, which video-only callers do not need);
3) docs sync - grepped every removed identifier across README, docs/, scripts/,
.claude/; updated 9 docs; 4) CLAUDE.md - added the no-error-only-knobs rule to
.claude/rules/development.md

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>

pyproject.toml

@@ -86,16 +86,11 @@ detect = [
 ]
 diffusion = [
     "remove-ai-watermarks[pixels]",
+    # A CUDA-enabled torch build is required: invisible-watermark removal has no
+    # CPU, MPS or XPU path. The default PyPI wheel carries CUDA on Linux/Windows;
+    # on macOS there is no CUDA build and this extra installs only for the
+    # non-diffusion imports it shares.
     "torch>=2.0.0",
-    # The default PyPI torch wheel is a CPU/CUDA build. To drive an Intel GPU
-    # (Arc / Data Center) via ``--device xpu`` you need an XPU-enabled torch
-    # from PyTorch's XPU wheel index (Linux/Windows only -- there is no macOS
-    # XPU build). Install that build first, then this extra (torch is then
-    # already satisfied and won't be re-pulled):
-    #   pip install torch --index-url https://download.pytorch.org/whl/xpu
-    #   pip install 'remove-ai-watermarks[diffusion]'
-    # uv users can target the ``pytorch-xpu`` index declared under [tool.uv]:
-    #   uv pip install torch --index-url https://download.pytorch.org/whl/xpu
     "diffusers>=0.38.0",
     # diffusers 0.38's auto-pipeline registry imports ``Qwen3VLForConditional
     # Generation`` (its ``nucleusmoe_image`` pipeline), which only exists in
@@ -165,16 +160,9 @@ dev = [
     "uv-outdated>=0.1.0; python_version >= '3.12'",
     "uv-secure>=0.12.0; python_version >= '3.12'",
 ]
-all = ["remove-ai-watermarks[video,heif,detect,trustmark,diffusion,qwen-zimage,lama,migan]"]
-
-# PyTorch Intel-GPU (XPU) wheel index. ``explicit = true`` keeps it inert for
-# the default CPU/CUDA install: uv consults it only when a torch install
-# explicitly targets it (see the ``diffusion`` extra comment), so it does not alter
-# the locked CPU/CUDA resolution. Linux/Windows only -- no macOS XPU build.
-[[tool.uv.index]]
-name = "pytorch-xpu"
-url = "https://download.pytorch.org/whl/xpu"
-explicit = true
+# ``qwen-zimage`` already pulls ``diffusion``; naming both would suggest diffusion is
+# independently sufficient for a removal, which it is not.
+all = ["remove-ai-watermarks[video,heif,detect,trustmark,qwen-zimage,lama,migan]"]
 
 [project.scripts]
 remove-ai-watermarks = "remove_ai_watermarks.cli:main"