v0.10.0

Honest hardware, multilingual-safe models, no truncated stubs, memory-quality
report (docs/TODO §1/§3/§5/§6).

Added

• ygg quality — a store health report. Type/project distribution, exact
  duplicate pairs (content-hash), near-duplicate pairs (cosine ≥ threshold,
  default 0.95), cross-project leakage, and likely-truncated records (reuses the
  write-path truncation heuristic). Computed server-side (/quality) so
  embeddings never leave the engine; --json for scripting. Closes docs/TODO §6.

Added

• Hardware-aware acceleration tier + GPU warning (ygg recommend / hw).
  hw() now classifies inference as cpu / metal / cuda / rocm/vulkan and,
  crucially, warns when a GPU is present but won't accelerate inference — the
  Intel-Mac + AMD case, where macOS is Metal-only (Apple-Silicon oriented) and
  ROCm doesn't exist, so stock inference runs on CPU regardless of the card. The
  catalog surfaces the warning up top instead of silently running on CPU.
• Language-aware model catalog. Every model now carries a language/thinking
  tag (EN/RU/ZH · non-thinking, ⚠ NO Russian/Chinese, …). Added the Qwen
  upgrades qwen2.5:3b, qwen3:4b-instruct-2507, and gemma3:4b. If the local
  store is dominantly Russian/Chinese, recommend prints a steer away from
  English-only models.

Changed

• The recommended quality upgrade is now qwen2.5:3b, not llama3.2:3b —
  Llama 3.2 officially supports English + 7 European languages only, silently
  degrading non-English memory. Llama stays in the catalog, clearly flagged.

Fixed

• Truncated lessons are dropped, not persisted. A distilled lesson whose text
  ends mid-thought (trailing : / dangling connector / unbalanced bracket or
  quote — e.g. a list intro whose items never arrived) is now discarded at the
  write path and counted separately, instead of being stored as a stub. Length
  is deliberately not a signal (lessons are meant to be short).