// General Purpose Tracing
async function trace<T>(name: string, fn: () => Promise<T>): Promise<T>

// Step-Level Tracing
async function traceStep<T>(name: string, fn: () => Promise<T>): Promise<T>

// LLM-Specific Tracing
async function generateTextTraced<T = any>(args: any): Promise<T>

// Route Handler Tracing
function traceRoute<T extends (...args: any[]) => any>(name: string, fn: T): T

// Dry-Run Mode Detection
function isDryRunEnabled(): boolean

// Tool Execution Control
function shouldExecuteInDryRun(toolName: string): boolean

// LLM Simulation
async function logDryRunPrompt(
 messages: ChatCompletionRequestMessage[],
 purpose: string,
 executionState: ExecutionState,
 correlationId?: string
): Promise<void>

// Response Generation
function generateDefaultResponse<T>(schema: z.ZodType<T>): T

// Feedback Collection
async function logFeedback(params: {
 assetPackEvidenceId: string;
 userId: string;
 rating: -1 | 1;
 comment?: string;
}): Promise<void>

// Sentry Integration Configuration
import { startSpan } from '@bitcode/external-telemetry-sentry';

// Automatic span creation with performance monitoring
export async function trace<T>(name: string, fn: () => Promise<T>): Promise<T> {
 return startSpan({ name }, fn);
}

// Dry-Run Mode Detection
export function isDryRunEnabled(): boolean {
 return PIPELINE_CONSTANTS.DRY_RUN_MODE === true;
}

// Non-LLM Tool Whitelist
const nonLlmTools = [
 'cloneRepository',
 'initializeFileTracker',
 'analyzeRepository',
 'identifyCriticalPaths',
 'filterRelevantFiles'
];

// Supabase Client Configuration
const supabaseAdmin = createClient(SUPABASE_URL, SUPABASE_SERVICE_ROLE_KEY, {
 auth: { persistSession: false, autoRefreshToken: false }
});

// Route Handler Wrapping
export const authenticatedHandler = traceRoute('auth-handler', async (request) => {
 const authResult = await trace('authenticate-request', () =>
 authenticateRequest(request)
 );

 return await trace('process-request', () =>
 processAuthenticatedRequest(authResult)
 );
});

// Automatic LLM Tracing
const response = await generateTextTraced({
 model: anthropic('claude-3-sonnet'),
 messages: conversationMessages,
 temperature: 0.7
});

// Equivalent to:
const response = await trace('llm:generateText:claude-3-sonnet', () =>
 generateText({ model, messages, temperature })
);

// Conditional Tool Execution
if (isDryRunEnabled() && !shouldExecuteInDryRun(toolName)) {
 await logDryRunPrompt(messages, purpose, executionState, correlationId);
 return generateDefaultResponse(responseSchema);
}

// Normal execution path
return await executeTool(toolName, parameters);

// Automatic Error Reporting
export function traceRoute<T>(name: string, fn: T): T {
 return async (...args: any[]) => {
 try {
 return await trace(`api:${name}`, () => fn(...args));
 } catch (err) {
 const { status, body } = toHttpResponse(reportError(err));
 return new Response(JSON.stringify(body), {
 status,
 headers: { 'Content-Type': 'application/json' }
 });
 }
 };
}

// Automatic Mock Response Creation
function generateDefaultResponse<T>(schema: z.ZodType<T>): T {
 // Handle primitive types
 if (schema instanceof z.ZodString) return '' as T;
 if (schema instanceof z.ZodNumber) return 0 as T;
 if (schema instanceof z.ZodBoolean) return false as T;

 // Handle complex objects with recursive generation
 if (schema instanceof z.ZodObject) {
 const shape = schema._def.shape();
 const result: Record<string, any> = {};

 for (const [key, propSchema] of Object.entries(shape)) {
 if (!(propSchema instanceof z.ZodOptional)) {
 result[key] = generateDefaultResponse(propSchema as z.ZodType<any>);
 }
 }

 return result as T;
 }
}

// Comprehensive LLM Simulation
export async function logDryRunPrompt(
 messages: ChatCompletionRequestMessage[],
 purpose: string,
 executionState: ExecutionState,
 correlationId?: string
): Promise<void> {
 // Log detailed prompt information
 log('DRY RUN: LLM prompt that would have been sent', 'info', {
 purpose,
 messageCount: messages.length,
 systemPrompt: messages.find(m => m.role === 'system')?.content?.slice(0, 200),
 executionState,
 correlationId
 });

 // Stream simulation status
 await writeStreamMessage(dataStream, {
 type: 'status',
 progress: 'info',
 message: `DRY RUN: LLM prompt for ${purpose}`,
 metadata: { dryRun: true, purpose, correlationId }
 });
}