feat(kon): add core crate — types, traits, hardware, model registry, recommendation

- Value objects: ModelId, EngineName, Megabytes, AudioSamples, Segment, Transcript
- KonError enum with thiserror
- Constants centralised: audio pipeline, VAD, RAM thresholds, inference threading
- SpeechToText and TextProcessor provider traits with ProviderRegistry
- Unified model registry (Whisper tiny/base/small/medium + Parakeet CTC int8)
- Hardware detection: probe_ram, probe_cpu, probe_gpu (stub), probe_os
- Recommendation engine: score_model (pure function), rank_recommendations (sorted)
- 5 tests passing, clippy clean

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

crates/core/src/error.rs

@@ -0,0 +1,41 @@
+use std::path::PathBuf;
+
+use crate::types::ModelId;
+
+#[derive(Debug, thiserror::Error)]
+pub enum KonError {
+    #[error("model not found: {0}")]
+    ModelNotFound(ModelId),
+
+    #[error("model not downloaded: {0}")]
+    ModelNotDownloaded(ModelId),
+
+    #[error("engine not loaded: call load_model first")]
+    EngineNotLoaded,
+
+    #[error("transcription failed: {0}")]
+    TranscriptionFailed(String),
+
+    #[error("audio decode failed: {0}")]
+    AudioDecodeFailed(String),
+
+    #[error("audio capture failed: {0}")]
+    AudioCaptureFailed(String),
+
+    #[error("model download failed: {0}")]
+    DownloadFailed(String),
+
+    #[error("file not found: {}", .0.display())]
+    FileNotFound(PathBuf),
+
+    #[error("storage error: {0}")]
+    StorageError(String),
+
+    #[error("io error: {0}")]
+    Io(#[from] std::io::Error),
+
+    #[error("{0}")]
+    Other(String),
+}
+
+pub type Result<T> = std::result::Result<T, KonError>;