merge: resolve conflicts with develop (telemetry + lockfile)

Keep both Mosaic Telemetry section (from develop) and Matrix Dev
Environment section (from feature branch) in .env.example.
Regenerate pnpm-lock.yaml with both dependency trees merged.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

apps/api/src/app.module.ts

@@ -37,6 +37,7 @@ import { JobStepsModule } from "./job-steps/job-steps.module";
 import { CoordinatorIntegrationModule } from "./coordinator-integration/coordinator-integration.module";
 import { FederationModule } from "./federation/federation.module";
 import { CredentialsModule } from "./credentials/credentials.module";
+import { MosaicTelemetryModule } from "./mosaic-telemetry";
 import { RlsContextInterceptor } from "./common/interceptors/rls-context.interceptor";
 
 @Module({
@@ -97,6 +98,7 @@ import { RlsContextInterceptor } from "./common/interceptors/rls-context.interce
     CoordinatorIntegrationModule,
     FederationModule,
     CredentialsModule,
+    MosaicTelemetryModule,
   ],
   controllers: [AppController, CsrfController],
   providers: [

apps/api/src/llm/llm-cost-table.ts

@@ -0,0 +1,109 @@
+/**
+ * LLM Cost Table
+ *
+ * Maps model names to per-token costs in microdollars (USD * 1,000,000).
+ * For example, $0.003 per 1K tokens = 3,000 microdollars per 1K tokens = 3 microdollars per token.
+ *
+ * Costs are split into input (prompt) and output (completion) pricing.
+ * Ollama models run locally and are free (0 cost).
+ */
+
+/**
+ * Per-token cost in microdollars for a single model.
+ */
+export interface ModelCost {
+  /** Cost per input token in microdollars */
+  inputPerToken: number;
+  /** Cost per output token in microdollars */
+  outputPerToken: number;
+}
+
+/**
+ * Cost table mapping model name prefixes to per-token pricing.
+ *
+ * Model matching is prefix-based: "claude-sonnet-4-5" matches "claude-sonnet-4-5-20250929".
+ * More specific prefixes are checked first (longest match wins).
+ *
+ * Prices sourced from provider pricing pages as of 2026-02.
+ */
+const MODEL_COSTS: Record<string, ModelCost> = {
+  // Anthropic Claude models (per-token microdollars)
+  // claude-sonnet-4-5: $3/M input, $15/M output
+  "claude-sonnet-4-5": { inputPerToken: 3, outputPerToken: 15 },
+  // claude-opus-4: $15/M input, $75/M output
+  "claude-opus-4": { inputPerToken: 15, outputPerToken: 75 },
+  // claude-3-5-haiku / claude-haiku-4-5: $0.80/M input, $4/M output
+  "claude-haiku-4-5": { inputPerToken: 0.8, outputPerToken: 4 },
+  "claude-3-5-haiku": { inputPerToken: 0.8, outputPerToken: 4 },
+  // claude-3-5-sonnet: $3/M input, $15/M output
+  "claude-3-5-sonnet": { inputPerToken: 3, outputPerToken: 15 },
+  // claude-3-opus: $15/M input, $75/M output
+  "claude-3-opus": { inputPerToken: 15, outputPerToken: 75 },
+  // claude-3-sonnet: $3/M input, $15/M output
+  "claude-3-sonnet": { inputPerToken: 3, outputPerToken: 15 },
+  // claude-3-haiku: $0.25/M input, $1.25/M output
+  "claude-3-haiku": { inputPerToken: 0.25, outputPerToken: 1.25 },
+
+  // OpenAI models (per-token microdollars)
+  // gpt-4o: $2.50/M input, $10/M output
+  "gpt-4o-mini": { inputPerToken: 0.15, outputPerToken: 0.6 },
+  "gpt-4o": { inputPerToken: 2.5, outputPerToken: 10 },
+  // gpt-4-turbo: $10/M input, $30/M output
+  "gpt-4-turbo": { inputPerToken: 10, outputPerToken: 30 },
+  // gpt-4: $30/M input, $60/M output
+  "gpt-4": { inputPerToken: 30, outputPerToken: 60 },
+  // gpt-3.5-turbo: $0.50/M input, $1.50/M output
+  "gpt-3.5-turbo": { inputPerToken: 0.5, outputPerToken: 1.5 },
+
+  // Ollama / local models: free
+  // These are catch-all entries; any model not matched above falls through to getModelCost default
+};
+
+/**
+ * Sorted model prefixes from longest to shortest for greedy prefix matching.
+ * Ensures "gpt-4o-mini" matches before "gpt-4o" and "claude-3-5-haiku" before "claude-3-haiku".
+ */
+const SORTED_PREFIXES = Object.keys(MODEL_COSTS).sort((a, b) => b.length - a.length);
+
+/**
+ * Look up per-token cost for a given model name.
+ *
+ * Uses longest-prefix matching: the model name is compared against known
+ * prefixes from longest to shortest. If no prefix matches, returns zero cost
+ * (assumes local/free model).
+ *
+ * @param modelName - Full model name (e.g. "claude-sonnet-4-5-20250929", "gpt-4o")
+ * @returns Per-token cost in microdollars
+ */
+export function getModelCost(modelName: string): ModelCost {
+  const normalized = modelName.toLowerCase();
+
+  for (const prefix of SORTED_PREFIXES) {
+    if (normalized.startsWith(prefix)) {
+      const cost = MODEL_COSTS[prefix];
+      if (cost !== undefined) {
+        return cost;
+      }
+    }
+  }
+
+  // Unknown or local model — assume free
+  return { inputPerToken: 0, outputPerToken: 0 };
+}
+
+/**
+ * Calculate total cost in microdollars for a given model and token counts.
+ *
+ * @param modelName - Full model name
+ * @param inputTokens - Number of input (prompt) tokens
+ * @param outputTokens - Number of output (completion) tokens
+ * @returns Total cost in microdollars (USD * 1,000,000)
+ */
+export function calculateCostMicrodollars(
+  modelName: string,
+  inputTokens: number,
+  outputTokens: number
+): number {
+  const cost = getModelCost(modelName);
+  return Math.round(cost.inputPerToken * inputTokens + cost.outputPerToken * outputTokens);
+}

apps/api/src/llm/llm-telemetry-tracker.service.spec.ts

@@ -0,0 +1,487 @@
+import { describe, it, expect, beforeEach, vi } from "vitest";
+import { Test, TestingModule } from "@nestjs/testing";
+import { TaskType, Complexity, Harness, Provider, Outcome } from "@mosaicstack/telemetry-client";
+import type { TaskCompletionEvent, EventBuilderParams } from "@mosaicstack/telemetry-client";
+import { MosaicTelemetryService } from "../mosaic-telemetry/mosaic-telemetry.service";
+import {
+  LlmTelemetryTrackerService,
+  estimateTokens,
+  mapProviderType,
+  mapHarness,
+  inferTaskType,
+} from "./llm-telemetry-tracker.service";
+import type { LlmCompletionParams } from "./llm-telemetry-tracker.service";
+import { getModelCost, calculateCostMicrodollars } from "./llm-cost-table";
+
+// ---------- Cost Table Tests ----------
+
+describe("llm-cost-table", () => {
+  describe("getModelCost", () => {
+    it("should return cost for claude-sonnet-4-5 models", () => {
+      const cost = getModelCost("claude-sonnet-4-5-20250929");
+      expect(cost.inputPerToken).toBe(3);
+      expect(cost.outputPerToken).toBe(15);
+    });
+
+    it("should return cost for claude-opus-4 models", () => {
+      const cost = getModelCost("claude-opus-4-6");
+      expect(cost.inputPerToken).toBe(15);
+      expect(cost.outputPerToken).toBe(75);
+    });
+
+    it("should return cost for claude-haiku-4-5 models", () => {
+      const cost = getModelCost("claude-haiku-4-5-20251001");
+      expect(cost.inputPerToken).toBe(0.8);
+      expect(cost.outputPerToken).toBe(4);
+    });
+
+    it("should return cost for gpt-4o", () => {
+      const cost = getModelCost("gpt-4o");
+      expect(cost.inputPerToken).toBe(2.5);
+      expect(cost.outputPerToken).toBe(10);
+    });
+
+    it("should return cost for gpt-4o-mini (longer prefix matches first)", () => {
+      const cost = getModelCost("gpt-4o-mini");
+      expect(cost.inputPerToken).toBe(0.15);
+      expect(cost.outputPerToken).toBe(0.6);
+    });
+
+    it("should return zero cost for unknown/local models", () => {
+      const cost = getModelCost("llama3.2");
+      expect(cost.inputPerToken).toBe(0);
+      expect(cost.outputPerToken).toBe(0);
+    });
+
+    it("should return zero cost for ollama models", () => {
+      const cost = getModelCost("mistral:7b");
+      expect(cost.inputPerToken).toBe(0);
+      expect(cost.outputPerToken).toBe(0);
+    });
+
+    it("should be case-insensitive", () => {
+      const cost = getModelCost("Claude-Sonnet-4-5-20250929");
+      expect(cost.inputPerToken).toBe(3);
+    });
+  });
+
+  describe("calculateCostMicrodollars", () => {
+    it("should calculate cost for claude-sonnet-4-5 with token counts", () => {
+      // 1000 input tokens * 3 + 500 output tokens * 15 = 3000 + 7500 = 10500
+      const cost = calculateCostMicrodollars("claude-sonnet-4-5-20250929", 1000, 500);
+      expect(cost).toBe(10500);
+    });
+
+    it("should return 0 for local models", () => {
+      const cost = calculateCostMicrodollars("llama3.2", 1000, 500);
+      expect(cost).toBe(0);
+    });
+
+    it("should return 0 when token counts are 0", () => {
+      const cost = calculateCostMicrodollars("claude-opus-4-6", 0, 0);
+      expect(cost).toBe(0);
+    });
+
+    it("should round the result to integer microdollars", () => {
+      // gpt-4o-mini: 0.15 * 3 + 0.6 * 7 = 0.45 + 4.2 = 4.65 -> rounds to 5
+      const cost = calculateCostMicrodollars("gpt-4o-mini", 3, 7);
+      expect(cost).toBe(5);
+    });
+  });
+});
+
+// ---------- Helper Function Tests ----------
+
+describe("helper functions", () => {
+  describe("estimateTokens", () => {
+    it("should estimate ~1 token per 4 characters", () => {
+      expect(estimateTokens("abcd")).toBe(1);
+      expect(estimateTokens("abcdefgh")).toBe(2);
+    });
+
+    it("should round up for partial tokens", () => {
+      expect(estimateTokens("abc")).toBe(1);
+      expect(estimateTokens("abcde")).toBe(2);
+    });
+
+    it("should return 0 for empty string", () => {
+      expect(estimateTokens("")).toBe(0);
+    });
+  });
+
+  describe("mapProviderType", () => {
+    it("should map claude to ANTHROPIC", () => {
+      expect(mapProviderType("claude")).toBe(Provider.ANTHROPIC);
+    });
+
+    it("should map openai to OPENAI", () => {
+      expect(mapProviderType("openai")).toBe(Provider.OPENAI);
+    });
+
+    it("should map ollama to OLLAMA", () => {
+      expect(mapProviderType("ollama")).toBe(Provider.OLLAMA);
+    });
+  });
+
+  describe("mapHarness", () => {
+    it("should map ollama to OLLAMA_LOCAL", () => {
+      expect(mapHarness("ollama")).toBe(Harness.OLLAMA_LOCAL);
+    });
+
+    it("should map claude to API_DIRECT", () => {
+      expect(mapHarness("claude")).toBe(Harness.API_DIRECT);
+    });
+
+    it("should map openai to API_DIRECT", () => {
+      expect(mapHarness("openai")).toBe(Harness.API_DIRECT);
+    });
+  });
+
+  describe("inferTaskType", () => {
+    it("should return IMPLEMENTATION for embed operation", () => {
+      expect(inferTaskType("embed")).toBe(TaskType.IMPLEMENTATION);
+    });
+
+    it("should return UNKNOWN when no context provided for chat", () => {
+      expect(inferTaskType("chat")).toBe(TaskType.UNKNOWN);
+    });
+
+    it("should return PLANNING for brain context", () => {
+      expect(inferTaskType("chat", "brain")).toBe(TaskType.PLANNING);
+    });
+
+    it("should return PLANNING for planning context", () => {
+      expect(inferTaskType("chat", "planning")).toBe(TaskType.PLANNING);
+    });
+
+    it("should return CODE_REVIEW for review context", () => {
+      expect(inferTaskType("chat", "code-review")).toBe(TaskType.CODE_REVIEW);
+    });
+
+    it("should return TESTING for test context", () => {
+      expect(inferTaskType("chat", "test-generation")).toBe(TaskType.TESTING);
+    });
+
+    it("should return DEBUGGING for debug context", () => {
+      expect(inferTaskType("chatStream", "debug-session")).toBe(TaskType.DEBUGGING);
+    });
+
+    it("should return REFACTORING for refactor context", () => {
+      expect(inferTaskType("chat", "refactor")).toBe(TaskType.REFACTORING);
+    });
+
+    it("should return DOCUMENTATION for doc context", () => {
+      expect(inferTaskType("chat", "documentation")).toBe(TaskType.DOCUMENTATION);
+    });
+
+    it("should return CONFIGURATION for config context", () => {
+      expect(inferTaskType("chat", "config-update")).toBe(TaskType.CONFIGURATION);
+    });
+
+    it("should return SECURITY_AUDIT for security context", () => {
+      expect(inferTaskType("chat", "security-check")).toBe(TaskType.SECURITY_AUDIT);
+    });
+
+    it("should return IMPLEMENTATION for chat context", () => {
+      expect(inferTaskType("chat", "chat")).toBe(TaskType.IMPLEMENTATION);
+    });
+
+    it("should be case-insensitive", () => {
+      expect(inferTaskType("chat", "BRAIN")).toBe(TaskType.PLANNING);
+    });
+
+    it("should return UNKNOWN for unrecognized context", () => {
+      expect(inferTaskType("chat", "something-else")).toBe(TaskType.UNKNOWN);
+    });
+  });
+});
+
+// ---------- LlmTelemetryTrackerService Tests ----------
+
+describe("LlmTelemetryTrackerService", () => {
+  let service: LlmTelemetryTrackerService;
+  let mockTelemetryService: {
+    eventBuilder: { build: ReturnType<typeof vi.fn> } | null;
+    trackTaskCompletion: ReturnType<typeof vi.fn>;
+    isEnabled: boolean;
+  };
+
+  const mockEvent: TaskCompletionEvent = {
+    instance_id: "test-instance",
+    event_id: "test-event",
+    schema_version: "1.0.0",
+    timestamp: new Date().toISOString(),
+    task_duration_ms: 1000,
+    task_type: TaskType.IMPLEMENTATION,
+    complexity: Complexity.LOW,
+    harness: Harness.API_DIRECT,
+    model: "claude-sonnet-4-5-20250929",
+    provider: Provider.ANTHROPIC,
+    estimated_input_tokens: 100,
+    estimated_output_tokens: 200,
+    actual_input_tokens: 100,
+    actual_output_tokens: 200,
+    estimated_cost_usd_micros: 3300,
+    actual_cost_usd_micros: 3300,
+    quality_gate_passed: true,
+    quality_gates_run: [],
+    quality_gates_failed: [],
+    context_compactions: 0,
+    context_rotations: 0,
+    context_utilization_final: 0,
+    outcome: Outcome.SUCCESS,
+    retry_count: 0,
+  };
+
+  beforeEach(async () => {
+    mockTelemetryService = {
+      eventBuilder: {
+        build: vi.fn().mockReturnValue(mockEvent),
+      },
+      trackTaskCompletion: vi.fn(),
+      isEnabled: true,
+    };
+
+    const module: TestingModule = await Test.createTestingModule({
+      providers: [
+        LlmTelemetryTrackerService,
+        {
+          provide: MosaicTelemetryService,
+          useValue: mockTelemetryService,
+        },
+      ],
+    }).compile();
+
+    service = module.get<LlmTelemetryTrackerService>(LlmTelemetryTrackerService);
+  });
+
+  it("should be defined", () => {
+    expect(service).toBeDefined();
+  });
+
+  describe("trackLlmCompletion", () => {
+    const baseParams: LlmCompletionParams = {
+      model: "claude-sonnet-4-5-20250929",
+      providerType: "claude",
+      operation: "chat",
+      durationMs: 1200,
+      inputTokens: 150,
+      outputTokens: 300,
+      callingContext: "chat",
+      success: true,
+    };
+
+    it("should build and track a telemetry event for Anthropic provider", () => {
+      service.trackLlmCompletion(baseParams);
+
+      expect(mockTelemetryService.eventBuilder?.build).toHaveBeenCalledWith(
+        expect.objectContaining({
+          task_duration_ms: 1200,
+          task_type: TaskType.IMPLEMENTATION,
+          complexity: Complexity.LOW,
+          harness: Harness.API_DIRECT,
+          model: "claude-sonnet-4-5-20250929",
+          provider: Provider.ANTHROPIC,
+          actual_input_tokens: 150,
+          actual_output_tokens: 300,
+          outcome: Outcome.SUCCESS,
+        })
+      );
+
+      expect(mockTelemetryService.trackTaskCompletion).toHaveBeenCalledWith(mockEvent);
+    });
+
+    it("should build and track a telemetry event for OpenAI provider", () => {
+      service.trackLlmCompletion({
+        ...baseParams,
+        model: "gpt-4o",
+        providerType: "openai",
+      });
+
+      expect(mockTelemetryService.eventBuilder?.build).toHaveBeenCalledWith(
+        expect.objectContaining({
+          model: "gpt-4o",
+          provider: Provider.OPENAI,
+          harness: Harness.API_DIRECT,
+        })
+      );
+    });
+
+    it("should build and track a telemetry event for Ollama provider", () => {
+      service.trackLlmCompletion({
+        ...baseParams,
+        model: "llama3.2",
+        providerType: "ollama",
+      });
+
+      expect(mockTelemetryService.eventBuilder?.build).toHaveBeenCalledWith(
+        expect.objectContaining({
+          model: "llama3.2",
+          provider: Provider.OLLAMA,
+          harness: Harness.OLLAMA_LOCAL,
+        })
+      );
+    });
+
+    it("should calculate cost in microdollars correctly", () => {
+      service.trackLlmCompletion(baseParams);
+
+      // claude-sonnet-4-5: 150 * 3 + 300 * 15 = 450 + 4500 = 4950
+      const expectedActualCost = 4950;
+
+      expect(mockTelemetryService.eventBuilder?.build).toHaveBeenCalledWith(
+        expect.objectContaining({
+          // Estimated values are 0 when no PredictionService is injected
+          estimated_cost_usd_micros: 0,
+          actual_cost_usd_micros: expectedActualCost,
+        })
+      );
+    });
+
+    it("should calculate zero cost for ollama models", () => {
+      service.trackLlmCompletion({
+        ...baseParams,
+        model: "llama3.2",
+        providerType: "ollama",
+      });
+
+      expect(mockTelemetryService.eventBuilder?.build).toHaveBeenCalledWith(
+        expect.objectContaining({
+          estimated_cost_usd_micros: 0,
+          actual_cost_usd_micros: 0,
+        })
+      );
+    });
+
+    it("should track FAILURE outcome when success is false", () => {
+      service.trackLlmCompletion({
+        ...baseParams,
+        success: false,
+      });
+
+      expect(mockTelemetryService.eventBuilder?.build).toHaveBeenCalledWith(
+        expect.objectContaining({
+          outcome: Outcome.FAILURE,
+        })
+      );
+    });
+
+    it("should infer task type from calling context", () => {
+      service.trackLlmCompletion({
+        ...baseParams,
+        callingContext: "brain",
+      });
+
+      expect(mockTelemetryService.eventBuilder?.build).toHaveBeenCalledWith(
+        expect.objectContaining({
+          task_type: TaskType.PLANNING,
+        })
+      );
+    });
+
+    it("should set empty quality gates arrays for direct LLM calls", () => {
+      service.trackLlmCompletion(baseParams);
+
+      expect(mockTelemetryService.eventBuilder?.build).toHaveBeenCalledWith(
+        expect.objectContaining({
+          quality_gate_passed: true,
+          quality_gates_run: [],
+          quality_gates_failed: [],
+        })
+      );
+    });
+
+    it("should silently skip when telemetry is disabled (eventBuilder is null)", () => {
+      mockTelemetryService.eventBuilder = null;
+
+      // Should not throw
+      service.trackLlmCompletion(baseParams);
+
+      expect(mockTelemetryService.trackTaskCompletion).not.toHaveBeenCalled();
+    });
+
+    it("should not throw when eventBuilder.build throws an error", () => {
+      mockTelemetryService.eventBuilder = {
+        build: vi.fn().mockImplementation(() => {
+          throw new Error("Build failed");
+        }),
+      };
+
+      // Should not throw
+      expect(() => service.trackLlmCompletion(baseParams)).not.toThrow();
+    });
+
+    it("should not throw when trackTaskCompletion throws an error", () => {
+      mockTelemetryService.trackTaskCompletion.mockImplementation(() => {
+        throw new Error("Track failed");
+      });
+
+      // Should not throw
+      expect(() => service.trackLlmCompletion(baseParams)).not.toThrow();
+    });
+
+    it("should handle streaming operation with estimated tokens", () => {
+      service.trackLlmCompletion({
+        ...baseParams,
+        operation: "chatStream",
+        inputTokens: 50,
+        outputTokens: 100,
+      });
+
+      expect(mockTelemetryService.eventBuilder?.build).toHaveBeenCalledWith(
+        expect.objectContaining({
+          actual_input_tokens: 50,
+          actual_output_tokens: 100,
+          // Estimated values are 0 when no PredictionService is injected
+          estimated_input_tokens: 0,
+          estimated_output_tokens: 0,
+        })
+      );
+    });
+
+    it("should handle embed operation", () => {
+      service.trackLlmCompletion({
+        ...baseParams,
+        operation: "embed",
+        outputTokens: 0,
+        callingContext: undefined,
+      });
+
+      expect(mockTelemetryService.eventBuilder?.build).toHaveBeenCalledWith(
+        expect.objectContaining({
+          task_type: TaskType.IMPLEMENTATION,
+          actual_output_tokens: 0,
+        })
+      );
+    });
+
+    it("should pass all required EventBuilderParams fields", () => {
+      service.trackLlmCompletion(baseParams);
+
+      const buildCall = (mockTelemetryService.eventBuilder?.build as ReturnType<typeof vi.fn>).mock
+        .calls[0][0] as EventBuilderParams;
+
+      // Verify all required fields are present
+      expect(buildCall).toHaveProperty("task_duration_ms");
+      expect(buildCall).toHaveProperty("task_type");
+      expect(buildCall).toHaveProperty("complexity");
+      expect(buildCall).toHaveProperty("harness");
+      expect(buildCall).toHaveProperty("model");
+      expect(buildCall).toHaveProperty("provider");
+      expect(buildCall).toHaveProperty("estimated_input_tokens");
+      expect(buildCall).toHaveProperty("estimated_output_tokens");
+      expect(buildCall).toHaveProperty("actual_input_tokens");
+      expect(buildCall).toHaveProperty("actual_output_tokens");
+      expect(buildCall).toHaveProperty("estimated_cost_usd_micros");
+      expect(buildCall).toHaveProperty("actual_cost_usd_micros");
+      expect(buildCall).toHaveProperty("quality_gate_passed");
+      expect(buildCall).toHaveProperty("quality_gates_run");
+      expect(buildCall).toHaveProperty("quality_gates_failed");
+      expect(buildCall).toHaveProperty("context_compactions");
+      expect(buildCall).toHaveProperty("context_rotations");
+      expect(buildCall).toHaveProperty("context_utilization_final");
+      expect(buildCall).toHaveProperty("outcome");
+      expect(buildCall).toHaveProperty("retry_count");
+    });
+  });
+});

apps/api/src/llm/llm-telemetry-tracker.service.ts

@@ -0,0 +1,224 @@
+import { Injectable, Logger, Optional } from "@nestjs/common";
+import { MosaicTelemetryService } from "../mosaic-telemetry/mosaic-telemetry.service";
+import { PredictionService } from "../mosaic-telemetry/prediction.service";
+import { TaskType, Complexity, Harness, Provider, Outcome } from "@mosaicstack/telemetry-client";
+import type { LlmProviderType } from "./providers/llm-provider.interface";
+import { calculateCostMicrodollars } from "./llm-cost-table";
+
+/**
+ * Parameters for tracking an LLM completion event.
+ */
+export interface LlmCompletionParams {
+  /** Full model name (e.g. "claude-sonnet-4-5-20250929") */
+  model: string;
+  /** Provider type discriminator */
+  providerType: LlmProviderType;
+  /** Operation type that was performed */
+  operation: "chat" | "chatStream" | "embed";
+  /** Duration of the LLM call in milliseconds */
+  durationMs: number;
+  /** Number of input (prompt) tokens consumed */
+  inputTokens: number;
+  /** Number of output (completion) tokens generated */
+  outputTokens: number;
+  /**
+   * Optional calling context hint for task type inference.
+   * Examples: "brain", "chat", "embed", "planning", "code-review"
+   */
+  callingContext?: string | undefined;
+  /** Whether the call succeeded or failed */
+  success: boolean;
+}
+
+/**
+ * Estimated token count from text length.
+ * Uses a rough approximation of ~4 characters per token (GPT/Claude average).
+ */
+export function estimateTokens(text: string): number {
+  return Math.ceil(text.length / 4);
+}
+
+/** Map LLM provider type to telemetry Provider enum */
+export function mapProviderType(providerType: LlmProviderType): Provider {
+  switch (providerType) {
+    case "claude":
+      return Provider.ANTHROPIC;
+    case "openai":
+      return Provider.OPENAI;
+    case "ollama":
+      return Provider.OLLAMA;
+    default:
+      return Provider.UNKNOWN;
+  }
+}
+
+/** Map LLM provider type to telemetry Harness enum */
+export function mapHarness(providerType: LlmProviderType): Harness {
+  switch (providerType) {
+    case "ollama":
+      return Harness.OLLAMA_LOCAL;
+    default:
+      return Harness.API_DIRECT;
+  }
+}
+
+/**
+ * Infer the task type from calling context and operation.
+ *
+ * @param operation - The LLM operation (chat, chatStream, embed)
+ * @param callingContext - Optional hint about the caller's purpose
+ * @returns Inferred TaskType
+ */
+export function inferTaskType(
+  operation: "chat" | "chatStream" | "embed",
+  callingContext?: string
+): TaskType {
+  // Embedding operations are typically for indexing/search
+  if (operation === "embed") {
+    return TaskType.IMPLEMENTATION;
+  }
+
+  if (!callingContext) {
+    return TaskType.UNKNOWN;
+  }
+
+  const ctx = callingContext.toLowerCase();
+
+  if (ctx.includes("brain") || ctx.includes("planning") || ctx.includes("plan")) {
+    return TaskType.PLANNING;
+  }
+  if (ctx.includes("review") || ctx.includes("code-review")) {
+    return TaskType.CODE_REVIEW;
+  }
+  if (ctx.includes("test")) {
+    return TaskType.TESTING;
+  }
+  if (ctx.includes("debug")) {
+    return TaskType.DEBUGGING;
+  }
+  if (ctx.includes("refactor")) {
+    return TaskType.REFACTORING;
+  }
+  if (ctx.includes("doc")) {
+    return TaskType.DOCUMENTATION;
+  }
+  if (ctx.includes("config")) {
+    return TaskType.CONFIGURATION;
+  }
+  if (ctx.includes("security") || ctx.includes("audit")) {
+    return TaskType.SECURITY_AUDIT;
+  }
+  if (ctx.includes("chat") || ctx.includes("implement")) {
+    return TaskType.IMPLEMENTATION;
+  }
+
+  return TaskType.UNKNOWN;
+}
+
+/**
+ * LLM Telemetry Tracker Service
+ *
+ * Builds and submits telemetry events for LLM completions.
+ * All tracking is non-blocking and fire-and-forget; telemetry errors
+ * never propagate to the caller.
+ *
+ * @example
+ * ```typescript
+ * // After a successful chat completion
+ * this.telemetryTracker.trackLlmCompletion({
+ *   model: "claude-sonnet-4-5-20250929",
+ *   providerType: "claude",
+ *   operation: "chat",
+ *   durationMs: 1200,
+ *   inputTokens: 150,
+ *   outputTokens: 300,
+ *   callingContext: "chat",
+ *   success: true,
+ * });
+ * ```
+ */
+@Injectable()
+export class LlmTelemetryTrackerService {
+  private readonly logger = new Logger(LlmTelemetryTrackerService.name);
+
+  constructor(
+    private readonly telemetry: MosaicTelemetryService,
+    @Optional() private readonly predictionService?: PredictionService
+  ) {}
+
+  /**
+   * Track an LLM completion event via Mosaic Telemetry.
+   *
+   * This method is intentionally fire-and-forget. It catches all errors
+   * internally and logs them without propagating to the caller.
+   *
+   * @param params - LLM completion parameters
+   */
+  trackLlmCompletion(params: LlmCompletionParams): void {
+    try {
+      const builder = this.telemetry.eventBuilder;
+      if (!builder) {
+        // Telemetry is disabled — silently skip
+        return;
+      }
+
+      const taskType = inferTaskType(params.operation, params.callingContext);
+      const provider = mapProviderType(params.providerType);
+
+      const costMicrodollars = calculateCostMicrodollars(
+        params.model,
+        params.inputTokens,
+        params.outputTokens
+      );
+
+      // Query predictions for estimated fields (graceful degradation)
+      let estimatedInputTokens = 0;
+      let estimatedOutputTokens = 0;
+      let estimatedCostMicros = 0;
+
+      if (this.predictionService) {
+        const prediction = this.predictionService.getEstimate(
+          taskType,
+          params.model,
+          provider,
+          Complexity.LOW
+        );
+
+        if (prediction?.prediction && prediction.metadata.confidence !== "none") {
+          estimatedInputTokens = prediction.prediction.input_tokens.median;
+          estimatedOutputTokens = prediction.prediction.output_tokens.median;
+          estimatedCostMicros = prediction.prediction.cost_usd_micros.median ?? 0;
+        }
+      }
+
+      const event = builder.build({
+        task_duration_ms: params.durationMs,
+        task_type: taskType,
+        complexity: Complexity.LOW,
+        harness: mapHarness(params.providerType),
+        model: params.model,
+        provider,
+        estimated_input_tokens: estimatedInputTokens,
+        estimated_output_tokens: estimatedOutputTokens,
+        actual_input_tokens: params.inputTokens,
+        actual_output_tokens: params.outputTokens,
+        estimated_cost_usd_micros: estimatedCostMicros,
+        actual_cost_usd_micros: costMicrodollars,
+        quality_gate_passed: true,
+        quality_gates_run: [],
+        quality_gates_failed: [],
+        context_compactions: 0,
+        context_rotations: 0,
+        context_utilization_final: 0,
+        outcome: params.success ? Outcome.SUCCESS : Outcome.FAILURE,
+        retry_count: 0,
+      });
+
+      this.telemetry.trackTaskCompletion(event);
+    } catch (error: unknown) {
+      // Never let telemetry errors propagate
+      const msg = error instanceof Error ? error.message : String(error);
+      this.logger.warn(`Failed to track LLM telemetry event: ${msg}`);
+    }
+  }
+}

apps/api/src/llm/llm.module.ts

@@ -3,13 +3,14 @@ import { LlmController } from "./llm.controller";
 import { LlmProviderAdminController } from "./llm-provider-admin.controller";
 import { LlmService } from "./llm.service";
 import { LlmManagerService } from "./llm-manager.service";
+import { LlmTelemetryTrackerService } from "./llm-telemetry-tracker.service";
 import { PrismaModule } from "../prisma/prisma.module";
 import { LlmUsageModule } from "../llm-usage/llm-usage.module";
 
 @Module({
   imports: [PrismaModule, LlmUsageModule],
   controllers: [LlmController, LlmProviderAdminController],
-  providers: [LlmService, LlmManagerService],
+  providers: [LlmService, LlmManagerService, LlmTelemetryTrackerService],
   exports: [LlmService, LlmManagerService],
 })
 export class LlmModule {}

apps/api/src/llm/llm.service.spec.ts

@@ -3,6 +3,7 @@ import { Test, TestingModule } from "@nestjs/testing";
 import { ServiceUnavailableException } from "@nestjs/common";
 import { LlmService } from "./llm.service";
 import { LlmManagerService } from "./llm-manager.service";
+import { LlmTelemetryTrackerService } from "./llm-telemetry-tracker.service";
 import type { ChatRequestDto, EmbedRequestDto, ChatResponseDto, EmbedResponseDto } from "./dto";
 import type {
   LlmProviderInterface,
@@ -14,6 +15,9 @@ describe("LlmService", () => {
   let mockManagerService: {
     getDefaultProvider: ReturnType<typeof vi.fn>;
   };
+  let mockTelemetryTracker: {
+    trackLlmCompletion: ReturnType<typeof vi.fn>;
+  };
   let mockProvider: {
     chat: ReturnType<typeof vi.fn>;
     chatStream: ReturnType<typeof vi.fn>;
@@ -41,6 +45,11 @@ describe("LlmService", () => {
       getDefaultProvider: vi.fn().mockResolvedValue(mockProvider),
     };
 
+    // Create mock telemetry tracker
+    mockTelemetryTracker = {
+      trackLlmCompletion: vi.fn(),
+    };
+
     const module: TestingModule = await Test.createTestingModule({
       providers: [
         LlmService,
@@ -48,6 +57,10 @@ describe("LlmService", () => {
           provide: LlmManagerService,
           useValue: mockManagerService,
         },
+        {
+          provide: LlmTelemetryTrackerService,
+          useValue: mockTelemetryTracker,
+        },
       ],
     }).compile();
 
@@ -135,6 +148,45 @@ describe("LlmService", () => {
       expect(result).toEqual(response);
     });
 
+    it("should track telemetry on successful chat", async () => {
+      const response: ChatResponseDto = {
+        model: "llama3.2",
+        message: { role: "assistant", content: "Hello" },
+        done: true,
+        promptEvalCount: 10,
+        evalCount: 20,
+      };
+      mockProvider.chat.mockResolvedValue(response);
+
+      await service.chat(request, "chat");
+
+      expect(mockTelemetryTracker.trackLlmCompletion).toHaveBeenCalledWith(
+        expect.objectContaining({
+          model: "llama3.2",
+          providerType: "ollama",
+          operation: "chat",
+          inputTokens: 10,
+          outputTokens: 20,
+          callingContext: "chat",
+          success: true,
+        })
+      );
+    });
+
+    it("should track telemetry on failed chat", async () => {
+      mockProvider.chat.mockRejectedValue(new Error("Chat failed"));
+
+      await expect(service.chat(request)).rejects.toThrow(ServiceUnavailableException);
+
+      expect(mockTelemetryTracker.trackLlmCompletion).toHaveBeenCalledWith(
+        expect.objectContaining({
+          model: "llama3.2",
+          operation: "chat",
+          success: false,
+        })
+      );
+    });
+
     it("should throw ServiceUnavailableException on error", async () => {
       mockProvider.chat.mockRejectedValue(new Error("Chat failed"));
 
@@ -177,6 +229,94 @@ describe("LlmService", () => {
       expect(chunks[1].message.content).toBe(" world");
     });
 
+    it("should track telemetry after stream completes", async () => {
+      async function* mockGenerator(): AsyncGenerator<ChatResponseDto> {
+        yield {
+          model: "llama3.2",
+          message: { role: "assistant", content: "Hello" },
+          done: false,
+        };
+        yield {
+          model: "llama3.2",
+          message: { role: "assistant", content: " world" },
+          done: true,
+          promptEvalCount: 5,
+          evalCount: 10,
+        };
+      }
+
+      mockProvider.chatStream.mockReturnValue(mockGenerator());
+
+      const chunks: ChatResponseDto[] = [];
+      for await (const chunk of service.chatStream(request, "brain")) {
+        chunks.push(chunk);
+      }
+
+      expect(mockTelemetryTracker.trackLlmCompletion).toHaveBeenCalledWith(
+        expect.objectContaining({
+          model: "llama3.2",
+          providerType: "ollama",
+          operation: "chatStream",
+          inputTokens: 5,
+          outputTokens: 10,
+          callingContext: "brain",
+          success: true,
+        })
+      );
+    });
+
+    it("should estimate tokens when provider does not return counts in stream", async () => {
+      async function* mockGenerator(): AsyncGenerator<ChatResponseDto> {
+        yield {
+          model: "llama3.2",
+          message: { role: "assistant", content: "Hello world" },
+          done: false,
+        };
+        yield {
+          model: "llama3.2",
+          message: { role: "assistant", content: "" },
+          done: true,
+        };
+      }
+
+      mockProvider.chatStream.mockReturnValue(mockGenerator());
+
+      const chunks: ChatResponseDto[] = [];
+      for await (const chunk of service.chatStream(request)) {
+        chunks.push(chunk);
+      }
+
+      // Should use estimated tokens since no actual counts provided
+      expect(mockTelemetryTracker.trackLlmCompletion).toHaveBeenCalledWith(
+        expect.objectContaining({
+          operation: "chatStream",
+          success: true,
+          // Input estimated from "Hi" -> ceil(2/4) = 1
+          inputTokens: 1,
+          // Output estimated from "Hello world" -> ceil(11/4) = 3
+          outputTokens: 3,
+        })
+      );
+    });
+
+    it("should track telemetry on stream failure", async () => {
+      async function* errorGenerator(): AsyncGenerator<ChatResponseDto> {
+        throw new Error("Stream failed");
+      }
+
+      mockProvider.chatStream.mockReturnValue(errorGenerator());
+
+      const generator = service.chatStream(request);
+      await expect(generator.next()).rejects.toThrow(ServiceUnavailableException);
+
+      expect(mockTelemetryTracker.trackLlmCompletion).toHaveBeenCalledWith(
+        expect.objectContaining({
+          operation: "chatStream",
+          success: false,
+        })
+      );
+    });
+
     it("should throw ServiceUnavailableException on error", async () => {
       async function* errorGenerator(): AsyncGenerator<ChatResponseDto> {
         throw new Error("Stream failed");
@@ -210,6 +350,41 @@ describe("LlmService", () => {
       expect(result).toEqual(response);
     });
 
+    it("should track telemetry on successful embed", async () => {
+      const response: EmbedResponseDto = {
+        model: "llama3.2",
+        embeddings: [[0.1, 0.2, 0.3]],
+        totalDuration: 500,
+      };
+      mockProvider.embed.mockResolvedValue(response);
+
+      await service.embed(request, "embed");
+
+      expect(mockTelemetryTracker.trackLlmCompletion).toHaveBeenCalledWith(
+        expect.objectContaining({
+          model: "llama3.2",
+          providerType: "ollama",
+          operation: "embed",
+          outputTokens: 0,
+          callingContext: "embed",
+          success: true,
+        })
+      );
+    });
+
+    it("should track telemetry on failed embed", async () => {
+      mockProvider.embed.mockRejectedValue(new Error("Embedding failed"));
+
+      await expect(service.embed(request)).rejects.toThrow(ServiceUnavailableException);
+
+      expect(mockTelemetryTracker.trackLlmCompletion).toHaveBeenCalledWith(
+        expect.objectContaining({
+          operation: "embed",
+          success: false,
+        })
+      );
+    });
+
     it("should throw ServiceUnavailableException on error", async () => {
       mockProvider.embed.mockRejectedValue(new Error("Embedding failed"));
 

apps/api/src/llm/llm.service.ts

@@ -1,13 +1,15 @@
 import { Injectable, OnModuleInit, Logger, ServiceUnavailableException } from "@nestjs/common";
 import { LlmManagerService } from "./llm-manager.service";
+import { LlmTelemetryTrackerService, estimateTokens } from "./llm-telemetry-tracker.service";
 import type { ChatRequestDto, ChatResponseDto, EmbedRequestDto, EmbedResponseDto } from "./dto";
-import type { LlmProviderHealthStatus } from "./providers/llm-provider.interface";
+import type { LlmProviderHealthStatus, LlmProviderType } from "./providers/llm-provider.interface";
 
 /**
  * LLM Service
  *
  * High-level service for LLM operations. Delegates to providers via LlmManagerService.
  * Maintains backward compatibility with the original API while supporting multiple providers.
+ * Automatically tracks completions via Mosaic Telemetry (non-blocking).
  *
  * @example
  * ```typescript
@@ -33,7 +35,10 @@ import type { LlmProviderHealthStatus } from "./providers/llm-provider.interface
 export class LlmService implements OnModuleInit {
   private readonly logger = new Logger(LlmService.name);
 
-  constructor(private readonly llmManager: LlmManagerService) {
+  constructor(
+    private readonly llmManager: LlmManagerService,
+    private readonly telemetryTracker: LlmTelemetryTrackerService
+  ) {
     this.logger.log("LLM service initialized");
   }
 
@@ -91,14 +96,45 @@ export class LlmService implements OnModuleInit {
    * Perform a synchronous chat completion.
    *
    * @param request - Chat request with messages and configuration
+   * @param callingContext - Optional context hint for telemetry task type inference
    * @returns Complete chat response
    * @throws {ServiceUnavailableException} If provider is unavailable or request fails
    */
-  async chat(request: ChatRequestDto): Promise<ChatResponseDto> {
+  async chat(request: ChatRequestDto, callingContext?: string): Promise<ChatResponseDto> {
+    const startTime = Date.now();
+    let providerType: LlmProviderType = "ollama";
+
     try {
       const provider = await this.llmManager.getDefaultProvider();
-      return await provider.chat(request);
+      providerType = provider.type;
+      const response = await provider.chat(request);
+
+      // Fire-and-forget telemetry tracking
+      this.telemetryTracker.trackLlmCompletion({
+        model: response.model,
+        providerType,
+        operation: "chat",
+        durationMs: Date.now() - startTime,
+        inputTokens: response.promptEvalCount ?? 0,
+        outputTokens: response.evalCount ?? 0,
+        callingContext,
+        success: true,
+      });
+
+      return response;
     } catch (error: unknown) {
+      // Track failure (fire-and-forget)
+      this.telemetryTracker.trackLlmCompletion({
+        model: request.model,
+        providerType,
+        operation: "chat",
+        durationMs: Date.now() - startTime,
+        inputTokens: 0,
+        outputTokens: 0,
+        callingContext,
+        success: false,
+      });
+
       const errorMessage = error instanceof Error ? error.message : String(error);
       this.logger.error(`Chat failed: ${errorMessage}`);
       throw new ServiceUnavailableException(`Chat completion failed: ${errorMessage}`);
@@ -107,20 +143,75 @@ export class LlmService implements OnModuleInit {
   /**
    * Perform a streaming chat completion.
    * Yields response chunks as they arrive from the provider.
+   * Aggregates token usage and tracks telemetry after the stream ends.
    *
    * @param request - Chat request with messages and configuration
+   * @param callingContext - Optional context hint for telemetry task type inference
    * @yields Chat response chunks
    * @throws {ServiceUnavailableException} If provider is unavailable or request fails
    */
-  async *chatStream(request: ChatRequestDto): AsyncGenerator<ChatResponseDto, void, unknown> {
+  async *chatStream(
+    request: ChatRequestDto,
+    callingContext?: string
+  ): AsyncGenerator<ChatResponseDto, void, unknown> {
+    const startTime = Date.now();
+    let providerType: LlmProviderType = "ollama";
+    let aggregatedContent = "";
+    let lastChunkInputTokens = 0;
+    let lastChunkOutputTokens = 0;
+
     try {
       const provider = await this.llmManager.getDefaultProvider();
+      providerType = provider.type;
       const stream = provider.chatStream(request);
 
       for await (const chunk of stream) {
+        // Accumulate content for token estimation
+        aggregatedContent += chunk.message.content;
+
+        // Some providers include token counts on the final chunk
+        if (chunk.promptEvalCount !== undefined) {
+          lastChunkInputTokens = chunk.promptEvalCount;
+        }
+        if (chunk.evalCount !== undefined) {
+          lastChunkOutputTokens = chunk.evalCount;
+        }
+
         yield chunk;
       }
+
+      // After stream completes, track telemetry
+      // Use actual token counts if available, otherwise estimate from content length
+      const inputTokens =
+        lastChunkInputTokens > 0
+          ? lastChunkInputTokens
+          : estimateTokens(request.messages.map((m) => m.content).join(" "));
+      const outputTokens =
+        lastChunkOutputTokens > 0 ? lastChunkOutputTokens : estimateTokens(aggregatedContent);
+
+      this.telemetryTracker.trackLlmCompletion({
+        model: request.model,
+        providerType,
+        operation: "chatStream",
+        durationMs: Date.now() - startTime,
+        inputTokens,
+        outputTokens,
+        callingContext,
+        success: true,
+      });
     } catch (error: unknown) {
+      // Track failure (fire-and-forget)
+      this.telemetryTracker.trackLlmCompletion({
+        model: request.model,
+        providerType,
+        operation: "chatStream",
+        durationMs: Date.now() - startTime,
+        inputTokens: 0,
+        outputTokens: 0,
+        callingContext,
+        success: false,
+      });
+
       const errorMessage = error instanceof Error ? error.message : String(error);
       this.logger.error(`Stream failed: ${errorMessage}`);
       throw new ServiceUnavailableException(`Streaming failed: ${errorMessage}`);
@@ -130,14 +221,48 @@ export class LlmService implements OnModuleInit {
    * Generate embeddings for the given input texts.
    *
    * @param request - Embedding request with model and input texts
+   * @param callingContext - Optional context hint for telemetry task type inference
    * @returns Embeddings response with vector arrays
    * @throws {ServiceUnavailableException} If provider is unavailable or request fails
    */
-  async embed(request: EmbedRequestDto): Promise<EmbedResponseDto> {
+  async embed(request: EmbedRequestDto, callingContext?: string): Promise<EmbedResponseDto> {
+    const startTime = Date.now();
+    let providerType: LlmProviderType = "ollama";
+
     try {
       const provider = await this.llmManager.getDefaultProvider();
-      return await provider.embed(request);
+      providerType = provider.type;
+      const response = await provider.embed(request);
+
+      // Estimate input tokens from the input text
+      const inputTokens = estimateTokens(request.input.join(" "));
+
+      // Fire-and-forget telemetry tracking
+      this.telemetryTracker.trackLlmCompletion({
+        model: response.model,
+        providerType,
+        operation: "embed",
+        durationMs: Date.now() - startTime,
+        inputTokens,
+        outputTokens: 0, // Embeddings don't produce output tokens
+        callingContext,
+        success: true,
+      });
+
+      return response;
     } catch (error: unknown) {
+      // Track failure (fire-and-forget)
+      this.telemetryTracker.trackLlmCompletion({
+        model: request.model,
+        providerType,
+        operation: "embed",
+        durationMs: Date.now() - startTime,
+        inputTokens: 0,
+        outputTokens: 0,
+        callingContext,
+        success: false,
+      });
+
       const errorMessage = error instanceof Error ? error.message : String(error);
       this.logger.error(`Embed failed: ${errorMessage}`);
       throw new ServiceUnavailableException(`Embedding failed: ${errorMessage}`);

apps/api/src/mosaic-telemetry/index.ts

@@ -0,0 +1,17 @@
+/**
+ * Mosaic Telemetry module — task completion tracking and crowd-sourced predictions.
+ *
+ * **Not to be confused with the OpenTelemetry (OTEL) TelemetryModule** at
+ * `src/telemetry/`, which handles distributed request tracing.
+ *
+ * @module mosaic-telemetry
+ */
+
+export { MosaicTelemetryModule } from "./mosaic-telemetry.module";
+export { MosaicTelemetryService } from "./mosaic-telemetry.service";
+export {
+  loadMosaicTelemetryConfig,
+  toSdkConfig,
+  MOSAIC_TELEMETRY_ENV,
+  type MosaicTelemetryModuleConfig,
+} from "./mosaic-telemetry.config";

apps/api/src/mosaic-telemetry/mosaic-telemetry.config.ts

@@ -0,0 +1,78 @@
+import type { ConfigService } from "@nestjs/config";
+import type { TelemetryConfig } from "@mosaicstack/telemetry-client";
+
+/**
+ * Configuration interface for the Mosaic Telemetry module.
+ * Maps environment variables to SDK configuration.
+ */
+export interface MosaicTelemetryModuleConfig {
+  /** Whether telemetry collection is enabled. Default: true */
+  enabled: boolean;
+  /** Base URL of the telemetry server */
+  serverUrl: string;
+  /** API key for authentication (64-char hex string) */
+  apiKey: string;
+  /** Instance UUID for this client */
+  instanceId: string;
+  /** If true, log events instead of sending them. Default: false */
+  dryRun: boolean;
+}
+
+/**
+ * Environment variable names used by the Mosaic Telemetry module.
+ */
+export const MOSAIC_TELEMETRY_ENV = {
+  ENABLED: "MOSAIC_TELEMETRY_ENABLED",
+  SERVER_URL: "MOSAIC_TELEMETRY_SERVER_URL",
+  API_KEY: "MOSAIC_TELEMETRY_API_KEY",
+  INSTANCE_ID: "MOSAIC_TELEMETRY_INSTANCE_ID",
+  DRY_RUN: "MOSAIC_TELEMETRY_DRY_RUN",
+} as const;
+
+/**
+ * Read Mosaic Telemetry configuration from environment variables via NestJS ConfigService.
+ *
+ * @param configService - NestJS ConfigService instance
+ * @returns Parsed module configuration
+ */
+export function loadMosaicTelemetryConfig(
+  configService: ConfigService
+): MosaicTelemetryModuleConfig {
+  const enabledRaw = configService.get<string>(MOSAIC_TELEMETRY_ENV.ENABLED, "true");
+  const dryRunRaw = configService.get<string>(MOSAIC_TELEMETRY_ENV.DRY_RUN, "false");
+
+  return {
+    enabled: enabledRaw.toLowerCase() === "true",
+    serverUrl: configService.get<string>(MOSAIC_TELEMETRY_ENV.SERVER_URL, ""),
+    apiKey: configService.get<string>(MOSAIC_TELEMETRY_ENV.API_KEY, ""),
+    instanceId: configService.get<string>(MOSAIC_TELEMETRY_ENV.INSTANCE_ID, ""),
+    dryRun: dryRunRaw.toLowerCase() === "true",
+  };
+}
+
+/**
+ * Convert module config to SDK TelemetryConfig format.
+ * Includes the onError callback for NestJS Logger integration.
+ *
+ * @param config - Module configuration
+ * @param onError - Error callback (typically NestJS Logger)
+ * @returns SDK-compatible TelemetryConfig
+ */
+export function toSdkConfig(
+  config: MosaicTelemetryModuleConfig,
+  onError?: (error: Error) => void
+): TelemetryConfig {
+  const sdkConfig: TelemetryConfig = {
+    serverUrl: config.serverUrl,
+    apiKey: config.apiKey,
+    instanceId: config.instanceId,
+    enabled: config.enabled,
+    dryRun: config.dryRun,
+  };
+
+  if (onError) {
+    sdkConfig.onError = onError;
+  }
+
+  return sdkConfig;
+}

apps/api/src/mosaic-telemetry/mosaic-telemetry.controller.ts

@@ -0,0 +1,92 @@
+import { Controller, Get, Query, UseGuards, BadRequestException } from "@nestjs/common";
+import { AuthGuard } from "../auth/guards/auth.guard";
+import { PredictionService } from "./prediction.service";
+import {
+  TaskType,
+  Complexity,
+  Provider,
+  type PredictionResponse,
+} from "@mosaicstack/telemetry-client";
+
+/**
+ * Valid values for query parameter validation.
+ */
+const VALID_TASK_TYPES = new Set<string>(Object.values(TaskType));
+const VALID_COMPLEXITIES = new Set<string>(Object.values(Complexity));
+const VALID_PROVIDERS = new Set<string>(Object.values(Provider));
+
+/**
+ * Response DTO for the estimate endpoint.
+ */
+interface EstimateResponseDto {
+  data: PredictionResponse | null;
+}
+
+/**
+ * Mosaic Telemetry Controller
+ *
+ * Provides API endpoints for accessing telemetry prediction data.
+ * All endpoints require authentication via AuthGuard.
+ *
+ * This controller is intentionally lightweight - it delegates to PredictionService
+ * for the actual prediction logic and returns results directly to the frontend.
+ */
+@Controller("telemetry")
+@UseGuards(AuthGuard)
+export class MosaicTelemetryController {
+  constructor(private readonly predictionService: PredictionService) {}
+
+  /**
+   * GET /api/telemetry/estimate
+   *
+   * Get a cost/token estimate for a given task configuration.
+   * Returns prediction data including confidence level, or null if
+   * no prediction is available.
+   *
+   * @param taskType - Task type enum value (e.g. "implementation", "planning")
+   * @param model - Model name (e.g. "claude-sonnet-4-5")
+   * @param provider - Provider enum value (e.g. "anthropic", "openai")
+   * @param complexity - Complexity level (e.g. "low", "medium", "high")
+   * @returns Prediction response with estimates and confidence
+   */
+  @Get("estimate")
+  getEstimate(
+    @Query("taskType") taskType: string,
+    @Query("model") model: string,
+    @Query("provider") provider: string,
+    @Query("complexity") complexity: string
+  ): EstimateResponseDto {
+    if (!taskType || !model || !provider || !complexity) {
+      throw new BadRequestException(
+        "Missing query parameters. Required: taskType, model, provider, complexity"
+      );
+    }
+
+    if (!VALID_TASK_TYPES.has(taskType)) {
+      throw new BadRequestException(
+        `Invalid taskType "${taskType}". Valid values: ${[...VALID_TASK_TYPES].join(", ")}`
+      );
+    }
+
+    if (!VALID_PROVIDERS.has(provider)) {
+      throw new BadRequestException(
+        `Invalid provider "${provider}". Valid values: ${[...VALID_PROVIDERS].join(", ")}`
+      );
+    }
+
+    if (!VALID_COMPLEXITIES.has(complexity)) {
+      throw new BadRequestException(
+        `Invalid complexity "${complexity}". Valid values: ${[...VALID_COMPLEXITIES].join(", ")}`
+      );
+    }
+
+    const prediction = this.predictionService.getEstimate(
+      taskType as TaskType,
+      model,
+      provider as Provider,
+      complexity as Complexity
+    );
+
+    return { data: prediction };
+  }
+}

apps/api/src/mosaic-telemetry/mosaic-telemetry.module.spec.ts

@@ -0,0 +1,212 @@
+import { describe, it, expect, vi, beforeEach } from "vitest";
+import { Test, TestingModule } from "@nestjs/testing";
+import { ConfigModule } from "@nestjs/config";
+import { MosaicTelemetryModule } from "./mosaic-telemetry.module";
+import { MosaicTelemetryService } from "./mosaic-telemetry.service";
+
+// Mock the telemetry client to avoid real HTTP calls
+vi.mock("@mosaicstack/telemetry-client", async (importOriginal) => {
+  const actual = await importOriginal<typeof import("@mosaicstack/telemetry-client")>();
+
+  class MockTelemetryClient {
+    private _isRunning = false;
+
+    constructor(_config: unknown) {
+      // no-op
+    }
+
+    get eventBuilder() {
+      return { build: vi.fn().mockReturnValue({ event_id: "test-event-id" }) };
+    }
+
+    start(): void {
+      this._isRunning = true;
+    }
+
+    async stop(): Promise<void> {
+      this._isRunning = false;
+    }
+
+    track(_event: unknown): void {
+      // no-op
+    }
+
+    getPrediction(_query: unknown): unknown {
+      return null;
+    }
+
+    async refreshPredictions(_queries: unknown): Promise<void> {
+      // no-op
+    }
+
+    get queueSize(): number {
+      return 0;
+    }
+
+    get isRunning(): boolean {
+      return this._isRunning;
+    }
+  }
+
+  return {
+    ...actual,
+    TelemetryClient: MockTelemetryClient,
+  };
+});
+
+describe("MosaicTelemetryModule", () => {
+  let module: TestingModule;
+
+  beforeEach(() => {
+    vi.clearAllMocks();
+  });
+
+  describe("module initialization", () => {
+    it("should compile the module successfully", async () => {
+      module = await Test.createTestingModule({
+        imports: [
+          ConfigModule.forRoot({
+            isGlobal: true,
+            envFilePath: [],
+            load: [
+              () => ({
+                MOSAIC_TELEMETRY_ENABLED: "false",
+              }),
+            ],
+          }),
+          MosaicTelemetryModule,
+        ],
+      }).compile();
+
+      expect(module).toBeDefined();
+      await module.close();
+    });
+
+    it("should provide MosaicTelemetryService", async () => {
+      module = await Test.createTestingModule({
+        imports: [
+          ConfigModule.forRoot({
+            isGlobal: true,
+            envFilePath: [],
+            load: [
+              () => ({
+                MOSAIC_TELEMETRY_ENABLED: "false",
+              }),
+            ],
+          }),
+          MosaicTelemetryModule,
+        ],
+      }).compile();
+
+      const service = module.get<MosaicTelemetryService>(MosaicTelemetryService);
+      expect(service).toBeDefined();
+      expect(service).toBeInstanceOf(MosaicTelemetryService);
+
+      await module.close();
+    });
+
+    it("should export MosaicTelemetryService for injection in other modules", async () => {
+      module = await Test.createTestingModule({
+        imports: [
+          ConfigModule.forRoot({
+            isGlobal: true,
+            envFilePath: [],
+            load: [
+              () => ({
+                MOSAIC_TELEMETRY_ENABLED: "false",
+              }),
+            ],
+          }),
+          MosaicTelemetryModule,
+        ],
+      }).compile();
+
+      const service = module.get(MosaicTelemetryService);
+      expect(service).toBeDefined();
+
+      await module.close();
+    });
+  });
+
+  describe("lifecycle integration", () => {
+    it("should initialize service on module init when enabled", async () => {
+      module = await Test.createTestingModule({
+        imports: [
+          ConfigModule.forRoot({
+            isGlobal: true,
+            envFilePath: [],
+            load: [
+              () => ({
+                MOSAIC_TELEMETRY_ENABLED: "true",
+                MOSAIC_TELEMETRY_SERVER_URL: "https://tel.test.local",
+                MOSAIC_TELEMETRY_API_KEY: "a".repeat(64),
+                MOSAIC_TELEMETRY_INSTANCE_ID: "550e8400-e29b-41d4-a716-446655440000",
+                MOSAIC_TELEMETRY_DRY_RUN: "false",
+              }),
+            ],
+          }),
+          MosaicTelemetryModule,
+        ],
+      }).compile();
+
+      await module.init();
+
+      const service = module.get<MosaicTelemetryService>(MosaicTelemetryService);
+      expect(service.isEnabled).toBe(true);
+
+      await module.close();
+    });
+
+    it("should not start client when disabled via env", async () => {
+      module = await Test.createTestingModule({
+        imports: [
+          ConfigModule.forRoot({
+            isGlobal: true,
+            envFilePath: [],
+            load: [
+              () => ({
+                MOSAIC_TELEMETRY_ENABLED: "false",
+              }),
+            ],
+          }),
+          MosaicTelemetryModule,
+        ],
+      }).compile();
+
+      await module.init();
+
+      const service = module.get<MosaicTelemetryService>(MosaicTelemetryService);
+      expect(service.isEnabled).toBe(false);
+
+      await module.close();
+    });
+
+    it("should cleanly shut down on module destroy", async () => {
+      module = await Test.createTestingModule({
+        imports: [
+          ConfigModule.forRoot({
+            isGlobal: true,
+            envFilePath: [],
+            load: [
+              () => ({
+                MOSAIC_TELEMETRY_ENABLED: "true",
+                MOSAIC_TELEMETRY_SERVER_URL: "https://tel.test.local",
+                MOSAIC_TELEMETRY_API_KEY: "a".repeat(64),
+                MOSAIC_TELEMETRY_INSTANCE_ID: "550e8400-e29b-41d4-a716-446655440000",
+                MOSAIC_TELEMETRY_DRY_RUN: "false",
+              }),
+            ],
+          }),
+          MosaicTelemetryModule,
+        ],
+      }).compile();
+
+      await module.init();
+
+      const service = module.get<MosaicTelemetryService>(MosaicTelemetryService);
+      expect(service.isEnabled).toBe(true);
+
+      await expect(module.close()).resolves.not.toThrow();
+    });
+  });
+});

apps/api/src/mosaic-telemetry/mosaic-telemetry.module.ts

@@ -0,0 +1,41 @@
+import { Module, Global } from "@nestjs/common";
+import { ConfigModule } from "@nestjs/config";
+import { AuthModule } from "../auth/auth.module";
+import { MosaicTelemetryService } from "./mosaic-telemetry.service";
+import { PredictionService } from "./prediction.service";
+import { MosaicTelemetryController } from "./mosaic-telemetry.controller";
+
+/**
+ * Global module providing Mosaic Telemetry integration via @mosaicstack/telemetry-client.
+ *
+ * Tracks task completion events and provides crowd-sourced predictions for
+ * token usage, cost estimation, and quality metrics.
+ *
+ * **This is separate from the OpenTelemetry (OTEL) TelemetryModule** which
+ * handles distributed request tracing. This module is specifically for
+ * Mosaic Stack's own telemetry aggregation service.
+ *
+ * Configuration via environment variables:
+ * - MOSAIC_TELEMETRY_ENABLED (boolean, default: true)
+ * - MOSAIC_TELEMETRY_SERVER_URL (string)
+ * - MOSAIC_TELEMETRY_API_KEY (string, 64-char hex)
+ * - MOSAIC_TELEMETRY_INSTANCE_ID (string, UUID)
+ * - MOSAIC_TELEMETRY_DRY_RUN (boolean, default: false)
+ *
+ * @example
+ * ```typescript
+ * // In any service (no need to import module — it's global):
+ * @Injectable()
+ * export class MyService {
+ *   constructor(private readonly telemetry: MosaicTelemetryService) {}
+ * }
+ * ```
+ */
+@Global()
+@Module({
+  imports: [ConfigModule, AuthModule],
+  controllers: [MosaicTelemetryController],
+  providers: [MosaicTelemetryService, PredictionService],
+  exports: [MosaicTelemetryService, PredictionService],
+})
+export class MosaicTelemetryModule {}

apps/api/src/mosaic-telemetry/mosaic-telemetry.service.spec.ts

@@ -0,0 +1,504 @@
+import { describe, it, expect, vi, beforeEach, afterEach } from "vitest";
+import { ConfigService } from "@nestjs/config";
+import { MOSAIC_TELEMETRY_ENV } from "./mosaic-telemetry.config";
+import type {
+  TaskCompletionEvent,
+  PredictionQuery,
+  PredictionResponse,
+} from "@mosaicstack/telemetry-client";
+import { TaskType, Complexity, Provider, Outcome } from "@mosaicstack/telemetry-client";
+
+// Track mock instances created during tests
+const mockStartFn = vi.fn();
+const mockStopFn = vi.fn().mockResolvedValue(undefined);
+const mockTrackFn = vi.fn();
+const mockGetPredictionFn = vi.fn().mockReturnValue(null);
+const mockRefreshPredictionsFn = vi.fn().mockResolvedValue(undefined);
+const mockBuildFn = vi.fn().mockReturnValue({ event_id: "test-event-id" });
+
+vi.mock("@mosaicstack/telemetry-client", async (importOriginal) => {
+  const actual = await importOriginal<typeof import("@mosaicstack/telemetry-client")>();
+
+  class MockTelemetryClient {
+    private _isRunning = false;
+
+    constructor(_config: unknown) {
+      // no-op
+    }
+
+    get eventBuilder() {
+      return { build: mockBuildFn };
+    }
+
+    start(): void {
+      this._isRunning = true;
+      mockStartFn();
+    }
+
+    async stop(): Promise<void> {
+      this._isRunning = false;
+      await mockStopFn();
+    }
+
+    track(event: unknown): void {
+      mockTrackFn(event);
+    }
+
+    getPrediction(query: unknown): unknown {
+      return mockGetPredictionFn(query);
+    }
+
+    async refreshPredictions(queries: unknown): Promise<void> {
+      await mockRefreshPredictionsFn(queries);
+    }
+
+    get queueSize(): number {
+      return 0;
+    }
+
+    get isRunning(): boolean {
+      return this._isRunning;
+    }
+  }
+
+  return {
+    ...actual,
+    TelemetryClient: MockTelemetryClient,
+  };
+});
+
+// Lazy-import the service after the mock is in place
+const { MosaicTelemetryService } = await import("./mosaic-telemetry.service");
+
+/**
+ * Create a ConfigService mock that returns environment values from the provided map.
+ */
+function createConfigService(envMap: Record<string, string | undefined> = {}): ConfigService {
+  const configService = {
+    get: vi.fn((key: string, defaultValue?: string): string => {
+      const value = envMap[key];
+      if (value !== undefined) {
+        return value;
+      }
+      return defaultValue ?? "";
+    }),
+  } as unknown as ConfigService;
+  return configService;
+}
+
+/**
+ * Default env config for an enabled telemetry service.
+ */
+const ENABLED_CONFIG: Record<string, string> = {
+  [MOSAIC_TELEMETRY_ENV.ENABLED]: "true",
+  [MOSAIC_TELEMETRY_ENV.SERVER_URL]: "https://tel.test.local",
+  [MOSAIC_TELEMETRY_ENV.API_KEY]: "a".repeat(64),
+  [MOSAIC_TELEMETRY_ENV.INSTANCE_ID]: "550e8400-e29b-41d4-a716-446655440000",
+  [MOSAIC_TELEMETRY_ENV.DRY_RUN]: "false",
+};
+
+/**
+ * Create a minimal TaskCompletionEvent for testing.
+ */
+function createTestEvent(): TaskCompletionEvent {
+  return {
+    schema_version: "1.0.0",
+    event_id: "test-event-123",
+    timestamp: new Date().toISOString(),
+    instance_id: "550e8400-e29b-41d4-a716-446655440000",
+    task_duration_ms: 5000,
+    task_type: TaskType.FEATURE,
+    complexity: Complexity.MEDIUM,
+    harness: "claude-code" as TaskCompletionEvent["harness"],
+    model: "claude-sonnet-4-20250514",
+    provider: Provider.ANTHROPIC,
+    estimated_input_tokens: 1000,
+    estimated_output_tokens: 500,
+    actual_input_tokens: 1100,
+    actual_output_tokens: 450,
+    estimated_cost_usd_micros: 5000,
+    actual_cost_usd_micros: 4800,
+    quality_gate_passed: true,
+    quality_gates_run: [],
+    quality_gates_failed: [],
+    context_compactions: 0,
+    context_rotations: 0,
+    context_utilization_final: 0.45,
+    outcome: Outcome.SUCCESS,
+    retry_count: 0,
+  };
+}
+
+describe("MosaicTelemetryService", () => {
+  let service: InstanceType<typeof MosaicTelemetryService>;
+
+  afterEach(async () => {
+    if (service) {
+      await service.onModuleDestroy();
+    }
+    vi.clearAllMocks();
+  });
+
+  describe("onModuleInit", () => {
+    it("should initialize the client when enabled with valid config", () => {
+      const configService = createConfigService(ENABLED_CONFIG);
+      service = new MosaicTelemetryService(configService);
+
+      service.onModuleInit();
+
+      expect(mockStartFn).toHaveBeenCalledOnce();
+      expect(service.isEnabled).toBe(true);
+    });
+
+    it("should not initialize client when disabled", () => {
+      const configService = createConfigService({
+        ...ENABLED_CONFIG,
+        [MOSAIC_TELEMETRY_ENV.ENABLED]: "false",
+      });
+      service = new MosaicTelemetryService(configService);
+
+      service.onModuleInit();
+
+      expect(mockStartFn).not.toHaveBeenCalled();
+      expect(service.isEnabled).toBe(false);
+    });
+
+    it("should disable when server URL is missing", () => {
+      const configService = createConfigService({
+        ...ENABLED_CONFIG,
+        [MOSAIC_TELEMETRY_ENV.SERVER_URL]: "",
+      });
+      service = new MosaicTelemetryService(configService);
+
+      service.onModuleInit();
+
+      expect(service.isEnabled).toBe(false);
+    });
+
+    it("should disable when API key is missing", () => {
+      const configService = createConfigService({
+        ...ENABLED_CONFIG,
+        [MOSAIC_TELEMETRY_ENV.API_KEY]: "",
+      });
+      service = new MosaicTelemetryService(configService);
+
+      service.onModuleInit();
+
+      expect(service.isEnabled).toBe(false);
+    });
+
+    it("should disable when instance ID is missing", () => {
+      const configService = createConfigService({
+        ...ENABLED_CONFIG,
+        [MOSAIC_TELEMETRY_ENV.INSTANCE_ID]: "",
+      });
+      service = new MosaicTelemetryService(configService);
+
+      service.onModuleInit();
+
+      expect(service.isEnabled).toBe(false);
+    });
+
+    it("should log dry-run mode when configured", () => {
+      const configService = createConfigService({
+        ...ENABLED_CONFIG,
+        [MOSAIC_TELEMETRY_ENV.DRY_RUN]: "true",
+      });
+      service = new MosaicTelemetryService(configService);
+
+      service.onModuleInit();
+
+      expect(mockStartFn).toHaveBeenCalledOnce();
+    });
+  });
+
+  describe("onModuleDestroy", () => {
+    it("should stop the client on shutdown", async () => {
+      const configService = createConfigService(ENABLED_CONFIG);
+      service = new MosaicTelemetryService(configService);
+      service.onModuleInit();
+
+      await service.onModuleDestroy();
+
+      expect(mockStopFn).toHaveBeenCalledOnce();
+    });
+
+    it("should not throw when client is not initialized (disabled)", async () => {
+      const configService = createConfigService({
+        ...ENABLED_CONFIG,
+        [MOSAIC_TELEMETRY_ENV.ENABLED]: "false",
+      });
+      service = new MosaicTelemetryService(configService);
+      service.onModuleInit();
+
+      await expect(service.onModuleDestroy()).resolves.not.toThrow();
+    });
+
+    it("should not throw when called multiple times", async () => {
+      const configService = createConfigService(ENABLED_CONFIG);
+      service = new MosaicTelemetryService(configService);
+      service.onModuleInit();
+
+      await service.onModuleDestroy();
+      await expect(service.onModuleDestroy()).resolves.not.toThrow();
+    });
+  });
+
+  describe("trackTaskCompletion", () => {
+    it("should queue event via client.track() when enabled", () => {
+      const configService = createConfigService(ENABLED_CONFIG);
+      service = new MosaicTelemetryService(configService);
+      service.onModuleInit();
+
+      const event = createTestEvent();
+      service.trackTaskCompletion(event);
+
+      expect(mockTrackFn).toHaveBeenCalledWith(event);
+    });
+
+    it("should be a no-op when disabled", () => {
+      const configService = createConfigService({
+        ...ENABLED_CONFIG,
+        [MOSAIC_TELEMETRY_ENV.ENABLED]: "false",
+      });
+      service = new MosaicTelemetryService(configService);
+      service.onModuleInit();
+
+      const event = createTestEvent();
+      service.trackTaskCompletion(event);
+
+      expect(mockTrackFn).not.toHaveBeenCalled();
+    });
+  });
+
+  describe("getPrediction", () => {
+    const testQuery: PredictionQuery = {
+      task_type: TaskType.FEATURE,
+      model: "claude-sonnet-4-20250514",
+      provider: Provider.ANTHROPIC,
+      complexity: Complexity.MEDIUM,
+    };
+
+    it("should return cached prediction when available", () => {
+      const mockPrediction: PredictionResponse = {
+        prediction: {
+          input_tokens: { p10: 100, p25: 200, median: 300, p75: 400, p90: 500 },
+          output_tokens: { p10: 50, p25: 100, median: 150, p75: 200, p90: 250 },
+          cost_usd_micros: { median: 5000 },
+          duration_ms: { median: 10000 },
+          correction_factors: { input: 1.0, output: 1.0 },
+          quality: { gate_pass_rate: 0.95, success_rate: 0.9 },
+        },
+        metadata: {
+          sample_size: 100,
+          fallback_level: 0,
+          confidence: "high",
+          last_updated: new Date().toISOString(),
+          cache_hit: true,
+        },
+      };
+
+      const configService = createConfigService(ENABLED_CONFIG);
+      service = new MosaicTelemetryService(configService);
+      service.onModuleInit();
+
+      mockGetPredictionFn.mockReturnValueOnce(mockPrediction);
+
+      const result = service.getPrediction(testQuery);
+
+      expect(result).toEqual(mockPrediction);
+      expect(mockGetPredictionFn).toHaveBeenCalledWith(testQuery);
+    });
+
+    it("should return null when disabled", () => {
+      const configService = createConfigService({
+        ...ENABLED_CONFIG,
+        [MOSAIC_TELEMETRY_ENV.ENABLED]: "false",
+      });
+      service = new MosaicTelemetryService(configService);
+      service.onModuleInit();
+
+      const result = service.getPrediction(testQuery);
+
+      expect(result).toBeNull();
+    });
+
+    it("should return null when no cached prediction exists", () => {
+      const configService = createConfigService(ENABLED_CONFIG);
+      service = new MosaicTelemetryService(configService);
+      service.onModuleInit();
+
+      mockGetPredictionFn.mockReturnValueOnce(null);
+
+      const result = service.getPrediction(testQuery);
+
+      expect(result).toBeNull();
+    });
+  });
+
+  describe("refreshPredictions", () => {
+    const testQueries: PredictionQuery[] = [
+      {
+        task_type: TaskType.FEATURE,
+        model: "claude-sonnet-4-20250514",
+        provider: Provider.ANTHROPIC,
+        complexity: Complexity.MEDIUM,
+      },
+    ];
+
+    it("should call client.refreshPredictions when enabled", async () => {
+      const configService = createConfigService(ENABLED_CONFIG);
+      service = new MosaicTelemetryService(configService);
+      service.onModuleInit();
+
+      await service.refreshPredictions(testQueries);
+
+      expect(mockRefreshPredictionsFn).toHaveBeenCalledWith(testQueries);
+    });
+
+    it("should be a no-op when disabled", async () => {
+      const configService = createConfigService({
+        ...ENABLED_CONFIG,
+        [MOSAIC_TELEMETRY_ENV.ENABLED]: "false",
+      });
+      service = new MosaicTelemetryService(configService);
+      service.onModuleInit();
+
+      await service.refreshPredictions(testQueries);
+
+      expect(mockRefreshPredictionsFn).not.toHaveBeenCalled();
+    });
+  });
+
+  describe("eventBuilder", () => {
+    it("should return EventBuilder when enabled", () => {
+      const configService = createConfigService(ENABLED_CONFIG);
+      service = new MosaicTelemetryService(configService);
+      service.onModuleInit();
+
+      const builder = service.eventBuilder;
+
+      expect(builder).toBeDefined();
+      expect(builder).not.toBeNull();
+      expect(typeof builder?.build).toBe("function");
+    });
+
+    it("should return null when disabled", () => {
+      const configService = createConfigService({
+        ...ENABLED_CONFIG,
+        [MOSAIC_TELEMETRY_ENV.ENABLED]: "false",
+      });
+      service = new MosaicTelemetryService(configService);
+      service.onModuleInit();
+
+      const builder = service.eventBuilder;
+
+      expect(builder).toBeNull();
+    });
+  });
+
+  describe("isEnabled", () => {
+    it("should return true when client is running", () => {
+      const configService = createConfigService(ENABLED_CONFIG);
+      service = new MosaicTelemetryService(configService);
+      service.onModuleInit();
+
+      expect(service.isEnabled).toBe(true);
+    });
+
+    it("should return false when disabled", () => {
+      const configService = createConfigService({
+        ...ENABLED_CONFIG,
+        [MOSAIC_TELEMETRY_ENV.ENABLED]: "false",
+      });
+      service = new MosaicTelemetryService(configService);
+      service.onModuleInit();
+
+      expect(service.isEnabled).toBe(false);
+    });
+  });
+
+  describe("queueSize", () => {
+    it("should return 0 when disabled", () => {
+      const configService = createConfigService({
+        ...ENABLED_CONFIG,
+        [MOSAIC_TELEMETRY_ENV.ENABLED]: "false",
+      });
+      service = new MosaicTelemetryService(configService);
+      service.onModuleInit();
+
+      expect(service.queueSize).toBe(0);
+    });
+
+    it("should delegate to client.queueSize when enabled", () => {
+      const configService = createConfigService(ENABLED_CONFIG);
+      service = new MosaicTelemetryService(configService);
+      service.onModuleInit();
+
+      expect(service.queueSize).toBe(0);
+    });
+  });
+
+  describe("disabled mode (comprehensive)", () => {
+    beforeEach(() => {
+      const configService = createConfigService({
+        ...ENABLED_CONFIG,
+        [MOSAIC_TELEMETRY_ENV.ENABLED]: "false",
+      });
+      service = new MosaicTelemetryService(configService);
+      service.onModuleInit();
+    });
+
+    it("should not make any HTTP calls when disabled", () => {
+      const event = createTestEvent();
+      service.trackTaskCompletion(event);
+
+      expect(mockTrackFn).not.toHaveBeenCalled();
+      expect(mockStartFn).not.toHaveBeenCalled();
+    });
+
+    it("should safely handle all method calls when disabled", async () => {
+      expect(() => service.trackTaskCompletion(createTestEvent())).not.toThrow();
+      expect(
+        service.getPrediction({
+          task_type: TaskType.FEATURE,
+          model: "test",
+          provider: Provider.ANTHROPIC,
+          complexity: Complexity.LOW,
+        })
+      ).toBeNull();
+      await expect(service.refreshPredictions([])).resolves.not.toThrow();
+      expect(service.eventBuilder).toBeNull();
+      expect(service.isEnabled).toBe(false);
+      expect(service.queueSize).toBe(0);
+    });
+  });
+
+  describe("dry-run mode", () => {
+    it("should create client in dry-run mode", () => {
+      const configService = createConfigService({
+        ...ENABLED_CONFIG,
+        [MOSAIC_TELEMETRY_ENV.DRY_RUN]: "true",
+      });
+      service = new MosaicTelemetryService(configService);
+      service.onModuleInit();
+
+      expect(mockStartFn).toHaveBeenCalledOnce();
+      expect(service.isEnabled).toBe(true);
+    });
+
+    it("should accept events in dry-run mode", () => {
+      const configService = createConfigService({
+        ...ENABLED_CONFIG,
+        [MOSAIC_TELEMETRY_ENV.DRY_RUN]: "true",
+      });
+      service = new MosaicTelemetryService(configService);
+      service.onModuleInit();
+
+      const event = createTestEvent();
+      service.trackTaskCompletion(event);
+
+      expect(mockTrackFn).toHaveBeenCalledWith(event);
+    });
+  });
+});

apps/api/src/mosaic-telemetry/mosaic-telemetry.service.ts

@@ -0,0 +1,164 @@
+import { Injectable, Logger, OnModuleInit, OnModuleDestroy } from "@nestjs/common";
+import { ConfigService } from "@nestjs/config";
+import {
+  TelemetryClient,
+  type TaskCompletionEvent,
+  type PredictionQuery,
+  type PredictionResponse,
+  type EventBuilder,
+} from "@mosaicstack/telemetry-client";
+import {
+  loadMosaicTelemetryConfig,
+  toSdkConfig,
+  type MosaicTelemetryModuleConfig,
+} from "./mosaic-telemetry.config";
+
+/**
+ * NestJS service wrapping the @mosaicstack/telemetry-client SDK.
+ *
+ * Provides convenience methods for tracking task completions and reading
+ * crowd-sourced predictions. When telemetry is disabled via
+ * MOSAIC_TELEMETRY_ENABLED=false, all methods are safe no-ops.
+ *
+ * This service is provided globally by MosaicTelemetryModule — any service
+ * can inject it without importing the module explicitly.
+ *
+ * @example
+ * ```typescript
+ * @Injectable()
+ * export class TasksService {
+ *   constructor(private readonly telemetry: MosaicTelemetryService) {}
+ *
+ *   async completeTask(taskId: string): Promise<void> {
+ *     // ... complete the task ...
+ *     const event = this.telemetry.eventBuilder.build({ ... });
+ *     this.telemetry.trackTaskCompletion(event);
+ *   }
+ * }
+ * ```
+ */
+@Injectable()
+export class MosaicTelemetryService implements OnModuleInit, OnModuleDestroy {
+  private readonly logger = new Logger(MosaicTelemetryService.name);
+  private client: TelemetryClient | null = null;
+  private config: MosaicTelemetryModuleConfig | null = null;
+
+  constructor(private readonly configService: ConfigService) {}
+
+  /**
+   * Initialize the telemetry client on module startup.
+   * Reads configuration from environment variables and starts background submission.
+   */
+  onModuleInit(): void {
+    this.config = loadMosaicTelemetryConfig(this.configService);
+
+    if (!this.config.enabled) {
+      this.logger.log("Mosaic Telemetry is disabled");
+      return;
+    }
+
+    if (!this.config.serverUrl || !this.config.apiKey || !this.config.instanceId) {
+      this.logger.warn(
+        "Mosaic Telemetry is enabled but missing configuration " +
+          "(MOSAIC_TELEMETRY_SERVER_URL, MOSAIC_TELEMETRY_API_KEY, or MOSAIC_TELEMETRY_INSTANCE_ID). " +
+          "Telemetry will remain disabled."
+      );
+      this.config = { ...this.config, enabled: false };
+      return;
+    }
+
+    const sdkConfig = toSdkConfig(this.config, (error: Error) => {
+      this.logger.error(`Telemetry client error: ${error.message}`, error.stack);
+    });
+
+    this.client = new TelemetryClient(sdkConfig);
+    this.client.start();
+
+    const mode = this.config.dryRun ? "dry-run" : "live";
+    this.logger.log(`Mosaic Telemetry client started (${mode}) -> ${this.config.serverUrl}`);
+  }
+
+  /**
+   * Stop the telemetry client on module shutdown.
+   * Flushes any remaining queued events before stopping.
+   */
+  async onModuleDestroy(): Promise<void> {
+    if (this.client) {
+      this.logger.log("Stopping Mosaic Telemetry client...");
+      await this.client.stop();
+      this.client = null;
+      this.logger.log("Mosaic Telemetry client stopped");
+    }
+  }
+
+  /**
+   * Queue a task completion event for batch submission.
+   * No-op when telemetry is disabled.
+   *
+   * @param event - The task completion event to track
+   */
+  trackTaskCompletion(event: TaskCompletionEvent): void {
+    if (!this.client) {
+      return;
+    }
+    this.client.track(event);
+  }
+
+  /**
+   * Get a cached prediction for the given query.
+   * Returns null when telemetry is disabled or if not cached/expired.
+   *
+   * @param query - The prediction query parameters
+   * @returns Cached prediction response, or null
+   */
+  getPrediction(query: PredictionQuery): PredictionResponse | null {
+    if (!this.client) {
+      return null;
+    }
+    return this.client.getPrediction(query);
+  }
+
+  /**
+   * Force-refresh predictions from the telemetry server.
+   * No-op when telemetry is disabled.
+   *
+   * @param queries - Array of prediction queries to refresh
+   */
+  async refreshPredictions(queries: PredictionQuery[]): Promise<void> {
+    if (!this.client) {
+      return;
+    }
+    await this.client.refreshPredictions(queries);
+  }
+
+  /**
+   * Get the EventBuilder for constructing TaskCompletionEvent objects.
+   * Returns null when telemetry is disabled.
+   *
+   * @returns EventBuilder instance, or null if disabled
+   */
+  get eventBuilder(): EventBuilder | null {
+    if (!this.client) {
+      return null;
+    }
+    return this.client.eventBuilder;
+  }
+
+  /**
+   * Whether the telemetry client is currently active and running.
+   */
+  get isEnabled(): boolean {
+    return this.client?.isRunning ?? false;
+  }
+
+  /**
+   * Number of events currently queued for submission.
+   * Returns 0 when telemetry is disabled.
+   */
+  get queueSize(): number {
+    if (!this.client) {
+      return 0;
+    }
+    return this.client.queueSize;
+  }
+}

apps/api/src/mosaic-telemetry/prediction.service.spec.ts

@@ -0,0 +1,297 @@
+import { describe, it, expect, beforeEach, vi } from "vitest";
+import { Test, TestingModule } from "@nestjs/testing";
+import { TaskType, Complexity, Provider } from "@mosaicstack/telemetry-client";
+import type { PredictionResponse, PredictionQuery } from "@mosaicstack/telemetry-client";
+import { MosaicTelemetryService } from "./mosaic-telemetry.service";
+import { PredictionService } from "./prediction.service";
+
+describe("PredictionService", () => {
+  let service: PredictionService;
+  let mockTelemetryService: {
+    isEnabled: boolean;
+    getPrediction: ReturnType<typeof vi.fn>;
+    refreshPredictions: ReturnType<typeof vi.fn>;
+  };
+
+  const mockPredictionResponse: PredictionResponse = {
+    prediction: {
+      input_tokens: {
+        p10: 50,
+        p25: 80,
+        median: 120,
+        p75: 200,
+        p90: 350,
+      },
+      output_tokens: {
+        p10: 100,
+        p25: 150,
+        median: 250,
+        p75: 400,
+        p90: 600,
+      },
+      cost_usd_micros: {
+        p10: 500,
+        p25: 800,
+        median: 1200,
+        p75: 2000,
+        p90: 3500,
+      },
+      duration_ms: {
+        p10: 200,
+        p25: 400,
+        median: 800,
+        p75: 1500,
+        p90: 3000,
+      },
+      correction_factors: {
+        input: 1.0,
+        output: 1.0,
+      },
+      quality: {
+        gate_pass_rate: 0.95,
+        success_rate: 0.92,
+      },
+    },
+    metadata: {
+      sample_size: 150,
+      fallback_level: 0,
+      confidence: "high",
+      last_updated: "2026-02-15T00:00:00Z",
+      cache_hit: true,
+    },
+  };
+
+  const nullPredictionResponse: PredictionResponse = {
+    prediction: null,
+    metadata: {
+      sample_size: 0,
+      fallback_level: 3,
+      confidence: "none",
+      last_updated: null,
+      cache_hit: false,
+    },
+  };
+
+  beforeEach(async () => {
+    mockTelemetryService = {
+      isEnabled: true,
+      getPrediction: vi.fn().mockReturnValue(mockPredictionResponse),
+      refreshPredictions: vi.fn().mockResolvedValue(undefined),
+    };
+
+    const module: TestingModule = await Test.createTestingModule({
+      providers: [
+        PredictionService,
+        {
+          provide: MosaicTelemetryService,
+          useValue: mockTelemetryService,
+        },
+      ],
+    }).compile();
+
+    service = module.get<PredictionService>(PredictionService);
+  });
+
+  it("should be defined", () => {
+    expect(service).toBeDefined();
+  });
+
+  // ---------- getEstimate ----------
+
+  describe("getEstimate", () => {
+    it("should return prediction response for valid query", () => {
+      const result = service.getEstimate(
+        TaskType.IMPLEMENTATION,
+        "claude-sonnet-4-5",
+        Provider.ANTHROPIC,
+        Complexity.LOW
+      );
+
+      expect(result).toEqual(mockPredictionResponse);
+      expect(mockTelemetryService.getPrediction).toHaveBeenCalledWith({
+        task_type: TaskType.IMPLEMENTATION,
+        model: "claude-sonnet-4-5",
+        provider: Provider.ANTHROPIC,
+        complexity: Complexity.LOW,
+      });
+    });
+
+    it("should pass correct query parameters to telemetry service", () => {
+      service.getEstimate(TaskType.CODE_REVIEW, "gpt-4o", Provider.OPENAI, Complexity.HIGH);
+
+      expect(mockTelemetryService.getPrediction).toHaveBeenCalledWith({
+        task_type: TaskType.CODE_REVIEW,
+        model: "gpt-4o",
+        provider: Provider.OPENAI,
+        complexity: Complexity.HIGH,
+      });
+    });
+
+    it("should return null when telemetry returns null", () => {
+      mockTelemetryService.getPrediction.mockReturnValue(null);
+
+      const result = service.getEstimate(
+        TaskType.IMPLEMENTATION,
+        "claude-sonnet-4-5",
+        Provider.ANTHROPIC,
+        Complexity.LOW
+      );
+
+      expect(result).toBeNull();
+    });
+
+    it("should return null prediction response when confidence is none", () => {
+      mockTelemetryService.getPrediction.mockReturnValue(nullPredictionResponse);
+
+      const result = service.getEstimate(
+        TaskType.IMPLEMENTATION,
+        "unknown-model",
+        Provider.UNKNOWN,
+        Complexity.LOW
+      );
+
+      expect(result).toEqual(nullPredictionResponse);
+      expect(result?.metadata.confidence).toBe("none");
+    });
+
+    it("should return null and not throw when getPrediction throws", () => {
+      mockTelemetryService.getPrediction.mockImplementation(() => {
+        throw new Error("Prediction fetch failed");
+      });
+
+      const result = service.getEstimate(
+        TaskType.IMPLEMENTATION,
+        "claude-sonnet-4-5",
+        Provider.ANTHROPIC,
+        Complexity.LOW
+      );
+
+      expect(result).toBeNull();
+    });
+
+    it("should handle non-Error thrown objects gracefully", () => {
+      mockTelemetryService.getPrediction.mockImplementation(() => {
+        throw "string error";
+      });
+
+      const result = service.getEstimate(
+        TaskType.IMPLEMENTATION,
+        "claude-sonnet-4-5",
+        Provider.ANTHROPIC,
+        Complexity.LOW
+      );
+
+      expect(result).toBeNull();
+    });
+  });
+
+  // ---------- refreshCommonPredictions ----------
+
+  describe("refreshCommonPredictions", () => {
+    it("should call refreshPredictions with multiple query combinations", async () => {
+      await service.refreshCommonPredictions();
+
+      expect(mockTelemetryService.refreshPredictions).toHaveBeenCalledTimes(1);
+
+      const queries: PredictionQuery[] = mockTelemetryService.refreshPredictions.mock.calls[0][0];
+
+      // Should have queries for cross-product of models, task types, and complexities
+      expect(queries.length).toBeGreaterThan(0);
+
+      // Verify all queries have valid structure
+      for (const query of queries) {
+        expect(query).toHaveProperty("task_type");
+        expect(query).toHaveProperty("model");
+        expect(query).toHaveProperty("provider");
+        expect(query).toHaveProperty("complexity");
+      }
+    });
+
+    it("should include Anthropic model predictions", async () => {
+      await service.refreshCommonPredictions();
+
+      const queries: PredictionQuery[] = mockTelemetryService.refreshPredictions.mock.calls[0][0];
+
+      const anthropicQueries = queries.filter(
+        (q: PredictionQuery) => q.provider === Provider.ANTHROPIC
+      );
+      expect(anthropicQueries.length).toBeGreaterThan(0);
+    });
+
+    it("should include OpenAI model predictions", async () => {
+      await service.refreshCommonPredictions();
+
+      const queries: PredictionQuery[] = mockTelemetryService.refreshPredictions.mock.calls[0][0];
+
+      const openaiQueries = queries.filter((q: PredictionQuery) => q.provider === Provider.OPENAI);
+      expect(openaiQueries.length).toBeGreaterThan(0);
+    });
+
+    it("should not call refreshPredictions when telemetry is disabled", async () => {
+      mockTelemetryService.isEnabled = false;
+
+      await service.refreshCommonPredictions();
+
+      expect(mockTelemetryService.refreshPredictions).not.toHaveBeenCalled();
+    });
+
+    it("should not throw when refreshPredictions rejects", async () => {
+      mockTelemetryService.refreshPredictions.mockRejectedValue(new Error("Server unreachable"));
+
+      // Should not throw
+      await expect(service.refreshCommonPredictions()).resolves.not.toThrow();
+    });
+
+    it("should include common task types in queries", async () => {
+      await service.refreshCommonPredictions();
+
+      const queries: PredictionQuery[] = mockTelemetryService.refreshPredictions.mock.calls[0][0];
+
+      const taskTypes = new Set(queries.map((q: PredictionQuery) => q.task_type));
+
+      expect(taskTypes.has(TaskType.IMPLEMENTATION)).toBe(true);
+      expect(taskTypes.has(TaskType.PLANNING)).toBe(true);
+      expect(taskTypes.has(TaskType.CODE_REVIEW)).toBe(true);
+    });
+
+    it("should include common complexity levels in queries", async () => {
+      await service.refreshCommonPredictions();
+
+      const queries: PredictionQuery[] = mockTelemetryService.refreshPredictions.mock.calls[0][0];
+
+      const complexities = new Set(queries.map((q: PredictionQuery) => q.complexity));
+
+      expect(complexities.has(Complexity.LOW)).toBe(true);
+      expect(complexities.has(Complexity.MEDIUM)).toBe(true);
+    });
+  });
+
+  // ---------- onModuleInit ----------
+
+  describe("onModuleInit", () => {
+    it("should trigger refreshCommonPredictions on init when telemetry is enabled", () => {
+      // refreshPredictions is async, but onModuleInit fires it and forgets
+      service.onModuleInit();
+
+      // Give the promise microtask a chance to execute
+      expect(mockTelemetryService.isEnabled).toBe(true);
+      // refreshPredictions will be called asynchronously
+    });
+
+    it("should not refresh when telemetry is disabled", () => {
+      mockTelemetryService.isEnabled = false;
+
+      service.onModuleInit();
+
+      // refreshPredictions should not be called since we returned early
+      expect(mockTelemetryService.refreshPredictions).not.toHaveBeenCalled();
+    });
+
+    it("should not throw when refresh fails on init", () => {
+      mockTelemetryService.refreshPredictions.mockRejectedValue(new Error("Connection refused"));
+
+      // Should not throw
+      expect(() => service.onModuleInit()).not.toThrow();
+    });
+  });
+});

apps/api/src/mosaic-telemetry/prediction.service.ts

@@ -0,0 +1,161 @@
+import { Injectable, Logger, OnModuleInit } from "@nestjs/common";
+import {
+  TaskType,
+  Complexity,
+  Provider,
+  type PredictionQuery,
+  type PredictionResponse,
+} from "@mosaicstack/telemetry-client";
+import { MosaicTelemetryService } from "./mosaic-telemetry.service";
+
+/**
+ * Common model-provider combinations used for pre-fetching predictions.
+ * These represent the most frequently used LLM configurations.
+ */
+const COMMON_MODELS: { model: string; provider: Provider }[] = [
+  { model: "claude-sonnet-4-5", provider: Provider.ANTHROPIC },
+  { model: "claude-opus-4", provider: Provider.ANTHROPIC },
+  { model: "claude-haiku-4-5", provider: Provider.ANTHROPIC },
+  { model: "gpt-4o", provider: Provider.OPENAI },
+  { model: "gpt-4o-mini", provider: Provider.OPENAI },
+];
+
+/**
+ * Common task types to pre-fetch predictions for.
+ */
+const COMMON_TASK_TYPES: TaskType[] = [
+  TaskType.IMPLEMENTATION,
+  TaskType.PLANNING,
+  TaskType.CODE_REVIEW,
+];
+
+/**
+ * Common complexity levels to pre-fetch predictions for.
+ */
+const COMMON_COMPLEXITIES: Complexity[] = [Complexity.LOW, Complexity.MEDIUM];
+
+/**
+ * PredictionService
+ *
+ * Provides pre-task cost and token estimates using crowd-sourced prediction data
+ * from the Mosaic Telemetry server. Predictions are cached by the underlying SDK
+ * with a 6-hour TTL.
+ *
+ * This service is intentionally non-blocking: if predictions are unavailable
+ * (telemetry disabled, server unreachable, no data), all methods return null
+ * without throwing errors. Task execution should never be blocked by prediction
+ * failures.
+ *
+ * @example
+ * ```typescript
+ * const estimate = this.predictionService.getEstimate(
+ *   TaskType.IMPLEMENTATION,
+ *   "claude-sonnet-4-5",
+ *   Provider.ANTHROPIC,
+ *   Complexity.LOW,
+ * );
+ * if (estimate?.prediction) {
+ *   console.log(`Estimated cost: ${estimate.prediction.cost_usd_micros}`);
+ * }
+ * ```
+ */
+@Injectable()
+export class PredictionService implements OnModuleInit {
+  private readonly logger = new Logger(PredictionService.name);
+
+  constructor(private readonly telemetry: MosaicTelemetryService) {}
+
+  /**
+   * Refresh common predictions on startup.
+   * Runs asynchronously and never blocks module initialization.
+   */
+  onModuleInit(): void {
+    if (!this.telemetry.isEnabled) {
+      this.logger.log("Telemetry disabled - skipping prediction refresh");
+      return;
+    }
+
+    // Fire-and-forget: refresh in the background
+    this.refreshCommonPredictions().catch((error: unknown) => {
+      const msg = error instanceof Error ? error.message : String(error);
+      this.logger.warn(`Failed to refresh common predictions on startup: ${msg}`);
+    });
+  }
+
+  /**
+   * Get a cost/token estimate for a given task configuration.
+   *
+   * Returns the cached prediction from the SDK, or null if:
+   * - Telemetry is disabled
+   * - No prediction data exists for this combination
+   * - The prediction has expired
+   *
+   * @param taskType - The type of task to estimate
+   * @param model - The model name (e.g. "claude-sonnet-4-5")
+   * @param provider - The provider enum value
+   * @param complexity - The complexity level
+   * @returns Prediction response with estimates and confidence, or null
+   */
+  getEstimate(
+    taskType: TaskType,
+    model: string,
+    provider: Provider,
+    complexity: Complexity
+  ): PredictionResponse | null {
+    try {
+      const query: PredictionQuery = {
+        task_type: taskType,
+        model,
+        provider,
+        complexity,
+      };
+
+      return this.telemetry.getPrediction(query);
+    } catch (error: unknown) {
+      const msg = error instanceof Error ? error.message : String(error);
+      this.logger.warn(`Failed to get prediction estimate: ${msg}`);
+      return null;
+    }
+  }
+
+  /**
+   * Refresh predictions for commonly used (taskType, model, provider, complexity) combinations.
+   *
+   * Generates the cross-product of common models, task types, and complexities,
+   * then batch-refreshes them from the telemetry server. The SDK caches the
+   * results with a 6-hour TTL.
+   *
+   * This method is safe to call at any time. If telemetry is disabled or the
+   * server is unreachable, it completes without error.
+   */
+  async refreshCommonPredictions(): Promise<void> {
+    if (!this.telemetry.isEnabled) {
+      return;
+    }
+
+    const queries: PredictionQuery[] = [];
+
+    for (const { model, provider } of COMMON_MODELS) {
+      for (const taskType of COMMON_TASK_TYPES) {
+        for (const complexity of COMMON_COMPLEXITIES) {
+          queries.push({
+            task_type: taskType,
+            model,
+            provider,
+            complexity,
+          });
+        }
+      }
+    }
+
+    this.logger.log(`Refreshing ${String(queries.length)} common prediction queries...`);
+
+    try {
+      await this.telemetry.refreshPredictions(queries);
+      this.logger.log(`Successfully refreshed ${String(queries.length)} predictions`);
+    } catch (error: unknown) {
+      const msg = error instanceof Error ? error.message : String(error);
+      this.logger.warn(`Failed to refresh predictions: ${msg}`);
+    }
+  }
+}