diff --git a/apps/memos-local-plugin/core/pipeline/deps.ts b/apps/memos-local-plugin/core/pipeline/deps.ts
index c4d3dd413..8a0772119 100644
--- a/apps/memos-local-plugin/core/pipeline/deps.ts
+++ b/apps/memos-local-plugin/core/pipeline/deps.ts
@@ -222,7 +222,13 @@ export function buildPipelineSubscribers(
     episodesRepo: adaptEpisodesRepo(deps.repos.episodes),
     embedder: deps.embedder,
     llm: bgLlm,
-    reflectLlm: bgReflectLlm,
+    // Issue #2148: capture batch reflection emits JSON, so it must use
+    // the main model rather than the potentially thinking-enabled
+    // skill-evolver model. Keep the background wrapper so capture also
+    // participates in the shared concurrency limit. `bgReflectLlm`
+    // remains read-only evaluator metadata below; the original
+    // `deps.reflectLlm` is also exposed to the Overview health card.
+    reflectLlm: bgLlm,
     bus: buses.capture,
     cfg: algorithm.capture,
     now: deps.now,
diff --git a/apps/memos-local-plugin/tests/unit/pipeline/capture-reflect-llm-wiring.test.ts b/apps/memos-local-plugin/tests/unit/pipeline/capture-reflect-llm-wiring.test.ts
new file mode 100644
index 000000000..3eede9e1c
--- /dev/null
+++ b/apps/memos-local-plugin/tests/unit/pipeline/capture-reflect-llm-wiring.test.ts
@@ -0,0 +1,192 @@
+/**
+ * Regression test for issue #2148 —
+ * `captureRunner` must receive the main `llm` for its batch-reflection
+ * pass, NOT `reflectLlm` (skill-evolver).
+ *
+ * Background: batch reflection is a JSON-output task. When the operator
+ * configures a stronger, thinking-enabled model under `skillEvolver.*`
+ * and leaves `llm.enableThinking=false`, wiring `reflectLlm` (skill-
+ * evolver) into the capture pipeline makes reflection produce
+ * `<think>...</think>` blocks that break JSON parsing. The skill-evolver
+ * model is intended for skill crystallization, not capture reflection.
+ *
+ * This test locks the wiring at the pipeline layer: no matter what the
+ * caller sets on `deps.reflectLlm`, `buildPipelineSubscribers` must pass
+ * the same rate-limited main-LLM client to both capture-runner slots.
+ */
+
+import { afterEach, beforeEach, describe, expect, it, vi } from "vitest";
+
+import type {
+  LlmCallOptions,
+  LlmClient,
+  LlmClientStats,
+  LlmMessage,
+  LlmProviderName,
+} from "../../../core/llm/types.js";
+
+const captureRunnerCalls: Array<{
+  llm: LlmClient | null;
+  reflectLlm: LlmClient | null;
+}> = [];
+
+vi.mock("../../../core/capture/index.js", async () => {
+  const actual = await vi.importActual<
+    typeof import("../../../core/capture/index.js")
+  >("../../../core/capture/index.js");
+  return {
+    ...actual,
+    createCaptureRunner: (deps: {
+      llm: LlmClient | null;
+      reflectLlm: LlmClient | null;
+      [k: string]: unknown;
+    }) => {
+      captureRunnerCalls.push({ llm: deps.llm, reflectLlm: deps.reflectLlm });
+      return actual.createCaptureRunner(
+        deps as Parameters<typeof actual.createCaptureRunner>[0],
+      );
+    },
+  };
+});
+
+import {
+  buildPipelineBuses,
+  buildPipelineSession,
+  buildPipelineSubscribers,
+  extractAlgorithmConfig,
+  type PipelineDeps,
+} from "../../../core/pipeline/index.js";
+import { DEFAULT_CONFIG } from "../../../core/config/defaults.js";
+import { resolveHome } from "../../../core/config/paths.js";
+import { rootLogger } from "../../../core/logger/index.js";
+import { makeTmpDb, type TmpDbHandle } from "../../helpers/tmp-db.js";
+import { fakeEmbedder } from "../../helpers/fake-embedder.js";
+
+function fakeLlmClient(name: string): LlmClient {
+  return {
+    provider: "local_only" as LlmProviderName,
+    model: name,
+    canStream: false,
+    async complete(_messages: LlmMessage[] | string, _opts?: LlmCallOptions) {
+      return {
+        text: "{}",
+        provider: "local_only" as LlmProviderName,
+        model: name,
+        servedBy: "local_only" as LlmProviderName,
+        durationMs: 0,
+      };
+    },
+    async completeJson<T>() {
+      return {
+        value: {} as T,
+        raw: "{}",
+        provider: "local_only" as LlmProviderName,
+        model: name,
+        servedBy: "local_only" as LlmProviderName,
+        durationMs: 0,
+      };
+    },
+    async *stream() {
+      yield { delta: "", done: true };
+    },
+    stats(): LlmClientStats {
+      return {
+        requests: 0,
+        hostFallbacks: 0,
+        failures: 0,
+        retries: 0,
+        totalPromptTokens: 0,
+        totalCompletionTokens: 0,
+        lastOkAt: null,
+        lastError: null,
+        lastStatus: null,
+      };
+    },
+    resetStats() {},
+    async close() {},
+  };
+}
+
+let dbHandle: TmpDbHandle | null = null;
+
+function buildDepsWithDistinctLlms(
+  h: TmpDbHandle,
+  lightweight: boolean,
+): PipelineDeps {
+  return {
+    agent: "openclaw",
+    home: resolveHome("openclaw", "/tmp/memos-issue-2148-test"),
+    config: {
+      ...DEFAULT_CONFIG,
+      algorithm: {
+        ...DEFAULT_CONFIG.algorithm,
+        lightweightMemory: {
+          ...DEFAULT_CONFIG.algorithm.lightweightMemory,
+          enabled: lightweight,
+        },
+      },
+    },
+    db: h.db,
+    repos: h.repos,
+    llm: fakeLlmClient("main-llm"),
+    reflectLlm: fakeLlmClient("skill-evolver-llm"),
+    l3Llm: fakeLlmClient("l3-llm"),
+    embedder: fakeEmbedder({ dimensions: 384 }),
+    log: rootLogger.child({ channel: "test.issue-2148" }),
+    namespace: { agentKind: "openclaw", profileId: "main" },
+    now: () => 1_700_000_000_000,
+  };
+}
+
+beforeEach(() => {
+  dbHandle = makeTmpDb();
+  captureRunnerCalls.length = 0;
+});
+
+afterEach(() => {
+  dbHandle?.cleanup();
+  dbHandle = null;
+});
+
+describe("pipeline/deps captureRunner wiring (issue #2148)", () => {
+  it("passes the main llm — not reflectLlm — as the capture runner's reflectLlm slot (normal mode)", () => {
+    const buses = buildPipelineBuses();
+    const deps = buildDepsWithDistinctLlms(dbHandle!, false);
+    const algorithm = extractAlgorithmConfig(deps);
+    const session = buildPipelineSession(deps, buses.session);
+    buildPipelineSubscribers(deps, buses, algorithm, session);
+
+    expect(captureRunnerCalls).toHaveLength(1);
+    const call = captureRunnerCalls[0];
+
+    // Both slots use the same rate-limited main-model client.
+    expect(call.llm?.model).toBe("main-llm");
+    expect(call.reflectLlm).toBe(call.llm);
+
+    // Regression guard: even though `deps.reflectLlm` is a distinct
+    // skill-evolver model (with e.g. enableThinking=true in real use),
+    // the capture pipeline must ignore it and use the main llm — batch
+    // reflection is a JSON-output task and cannot tolerate thinking
+    // tags. See issue #2148.
+    expect(call.reflectLlm?.model).toBe("main-llm");
+    expect(call.reflectLlm?.model).not.toBe("skill-evolver-llm");
+  });
+
+  it("passes the main llm as reflectLlm even in lightweight mode", () => {
+    // Lightweight mode still constructs the capture runner (it's what
+    // handles the lite/lightweight capture paths); the reflect pass is
+    // gated separately. The wiring guard must hold either way so a
+    // future flip of the flag can't reintroduce the bug.
+    const buses = buildPipelineBuses();
+    const deps = buildDepsWithDistinctLlms(dbHandle!, true);
+    const algorithm = extractAlgorithmConfig(deps);
+    const session = buildPipelineSession(deps, buses.session);
+    buildPipelineSubscribers(deps, buses, algorithm, session);
+
+    expect(captureRunnerCalls).toHaveLength(1);
+    const call = captureRunnerCalls[0];
+    expect(call.llm?.model).toBe("main-llm");
+    expect(call.reflectLlm).toBe(call.llm);
+    expect(call.reflectLlm?.model).toBe("main-llm");
+  });
+});