general improvements (#17)

* refactor(hooks): simplify hook execution with shared context

- [x] Extract BaseInput struct to eliminate duplicate fields across hooks
- [x] Create RunHook handler pattern for session-start and user-prompt
- [x] Create RunStatuslineHook for fast statusline rendering without worker startup
- [x] Add HookContext struct to pass port, project, CWD, SessionID to handlers
- [x] Add db/interface.go with ObservationReader/Writer interfaces
- [x] Add comprehensive conflict management tests in sqlite/conflict_test.go
- [x] Add vector client tests for Count, ModelVersion, NeedsRebuild, GetStaleVectors
- [x] Add FilterByThreshold helper tests for query result filtering
- [x] Make handlers_test more robust for network-dependent update checks
- [x] Update package versions in UI

* Move to GORM + general cleanup

* feat(mcp): add observation relations discovery and scoring integration

- [x] Add find_related_observations MCP tool for discovering related observations by confidence
- [x] Integrate scoring calculator and recalculator into MCP server initialization
- [x] Add pattern, relation, and session stores to MCP server dependencies
- [x] Register MCP server in Claude Code settings during plugin installation
- [x] Update install scripts (bash, PowerShell) to configure MCP server settings
- [x] Switch plugin manifest files to template-based versioning (plugin.json.tpl, marketplace.json.tpl)
- [x] Update all MCP server tests to pass new dependency parameters

internal/embedding/service.go

@@ -292,19 +292,19 @@ func (m *bgeModel) computeBatch(sentences []string) ([][]float32, error) {
 	if err != nil {
 		return nil, fmt.Errorf("create input_ids tensor: %w", err)
 	}
-	defer inputIdsTensor.Destroy()
+	defer func() { _ = inputIdsTensor.Destroy() }()
 
 	attentionMaskTensor, err := ort.NewTensor(inputShape, attentionMaskData)
 	if err != nil {
 		return nil, fmt.Errorf("create attention_mask tensor: %w", err)
 	}
-	defer attentionMaskTensor.Destroy()
+	defer func() { _ = attentionMaskTensor.Destroy() }()
 
 	tokenTypeIdsTensor, err := ort.NewTensor(inputShape, tokenTypeIdsData)
 	if err != nil {
 		return nil, fmt.Errorf("create token_type_ids tensor: %w", err)
 	}
-	defer tokenTypeIdsTensor.Destroy()
+	defer func() { _ = tokenTypeIdsTensor.Destroy() }()
 
 	// Create output tensor based on pooling strategy
 	var outputShape ort.Shape
@@ -324,7 +324,7 @@ func (m *bgeModel) computeBatch(sentences []string) ([][]float32, error) {
 	if err != nil {
 		return nil, fmt.Errorf("create output tensor: %w", err)
 	}
-	defer outputTensor.Destroy()
+	defer func() { _ = outputTensor.Destroy() }()
 
 	// Run inference
 	inputTensors := []ort.Value{inputIdsTensor, attentionMaskTensor, tokenTypeIdsTensor}