diff --git a/.agent/harness/llm.py b/.agent/harness/llm.py
index d2aecde..1050bb4 100644
--- a/.agent/harness/llm.py
+++ b/.agent/harness/llm.py
@@ -73,6 +73,7 @@ def _call_minimax(system, user, *, temperature, max_tokens, model):
         r = c.chat.completions.create(
             model=model,
             temperature=temperature,
+            max_completion_tokens=max_tokens,
             messages=[{"role": "system", "content": system},
                       {"role": "user", "content": user}],
         )
diff --git a/.agent/tools/test_learn_episodic_mirror.py b/.agent/tools/test_learn_episodic_mirror.py
index 808e3cc..fccfde5 100644
--- a/.agent/tools/test_learn_episodic_mirror.py
+++ b/.agent/tools/test_learn_episodic_mirror.py
@@ -24,12 +24,18 @@ def _load_learn(base_dir):
     """Load .agent/tools/learn.py with BASE/CANDIDATES pointed at base_dir.
 
     Sibling modules (text.word_set, cluster.pattern_id) are stubbed so the
-    test needs no part of the harness beyond learn.py itself.
+    test needs no part of the harness beyond learn.py itself. The stubs are
+    process-wide (sys.modules), so any previous entry for "text"/"cluster"
+    is saved and restored (or removed, if there was none) once exec_module
+    finishes -- otherwise a later test or import in the same process would
+    silently pick up these throwaway stand-ins instead of the real modules.
     """
+    previous_modules = {}
     for name, attrs in [
         ("text", {"word_set": lambda *a, **k: set()}),
         ("cluster", {"pattern_id": lambda claim, cond: "testcid" + str(abs(hash((claim, tuple(cond)))))[:6]}),
     ]:
+        previous_modules[name] = sys.modules.pop(name, None)
         m = types.ModuleType(name)
         for k, v in attrs.items():
             setattr(m, k, v)
@@ -38,7 +44,14 @@ def _load_learn(base_dir):
     module_path = Path(__file__).with_name("learn.py")
     spec = importlib.util.spec_from_file_location("learn_under_test", module_path)
     mod = importlib.util.module_from_spec(spec)
-    spec.loader.exec_module(mod)
+    try:
+        spec.loader.exec_module(mod)
+    finally:
+        for name, previous in previous_modules.items():
+            if previous is None:
+                sys.modules.pop(name, None)
+            else:
+                sys.modules[name] = previous
     mod.BASE = base_dir
     mod.CANDIDATES = os.path.join(base_dir, "memory", "candidates")
     os.makedirs(mod.CANDIDATES, exist_ok=True)
@@ -68,7 +81,7 @@ def test_stage_writes_one_episodic_mirror(self):
     def test_evidence_id_resolves_to_the_mirror(self):
         mod = _load_learn(self.tmp)
         cid, path = mod.stage("Serialize timestamps in UTC", ["timestamps", "utc"])
-        candidate = json.loads(Path(path).read_text())
+        candidate = json.loads(Path(path).read_text(encoding="utf-8"))
         evidence_ts = candidate["evidence_ids"][0]
         matching = [e for e in _episodic(self.tmp) if e["timestamp"] == evidence_ts]
         self.assertEqual(len(matching), 1)
diff --git a/tests/test_llm_provider.py b/tests/test_llm_provider.py
index 02fe0ab..8445072 100644
--- a/tests/test_llm_provider.py
+++ b/tests/test_llm_provider.py
@@ -102,6 +102,7 @@ def test_call_model_openai_wire_global(self):
         wire, kwargs = rec.calls[0]
         self.assertEqual(wire, "openai")
         self.assertEqual(kwargs["model"], "MiniMax-M3")
+        self.assertEqual(kwargs["max_completion_tokens"], 4096)
 
     def test_call_model_anthropic_wire_cn(self):
         os.environ["AGENT_PROVIDER"] = "minimax"