diff --git a/.github/workflows/type-checker.yml b/.github/workflows/type-checker.yml
index 03a5841a0..7b0cbe2da 100644
--- a/.github/workflows/type-checker.yml
+++ b/.github/workflows/type-checker.yml
@@ -17,8 +17,6 @@ jobs:
     steps:
       - name: Checkout code
         uses: actions/checkout@v4
-        with:
-          fetch-depth: 0 # Fetch all history for proper diff
 
       - name: Restore global uv cache
         id: cache-restore
@@ -42,37 +40,8 @@ jobs:
       - name: Install dependencies
         run: uv sync --all-groups --all-extras
 
-      - name: Get changed Python files
-        id: changed-files
-        run: |
-          # Get the list of changed Python files compared to the base branch
-          echo "Fetching changed files..."
-          git diff --name-only --diff-filter=ACMRT origin/${{ github.base_ref }}...HEAD -- '*.py' > changed_files.txt
-
-          # Filter for files in src/ directory only (excluding tests/)
-          grep -E "^src/" changed_files.txt > filtered_changed_files.txt || true
-
-          # Check if there are any changed files
-          if [ -s filtered_changed_files.txt ]; then
-            echo "Changed Python files in src/:"
-            cat filtered_changed_files.txt
-            echo "has_changes=true" >> $GITHUB_OUTPUT
-            # Convert newlines to spaces for mypy command
-            echo "files=$(cat filtered_changed_files.txt | tr '\n' ' ')" >> $GITHUB_OUTPUT
-          else
-            echo "No Python files changed in src/"
-            echo "has_changes=false" >> $GITHUB_OUTPUT
-          fi
-
-      - name: Run type checks on changed files
-        if: steps.changed-files.outputs.has_changes == 'true'
-        run: |
-          echo "Running mypy on changed files with Python ${{ matrix.python-version }}..."
-          uv run mypy ${{ steps.changed-files.outputs.files }}
-
-      - name: No files to check
-        if: steps.changed-files.outputs.has_changes == 'false'
-        run: echo "No Python files in src/ were modified - skipping type checks"
+      - name: Run type checks
+        run: uv run mypy lib/crewai/src/crewai/
 
       - name: Save uv caches
         if: steps.cache-restore.outputs.cache-hit != 'true'
diff --git a/lib/crewai-tools/src/crewai_tools/tools/brave_search_tool/base.py b/lib/crewai-tools/src/crewai_tools/tools/brave_search_tool/base.py
index 58ee95ccc..cc6c4de96 100644
--- a/lib/crewai-tools/src/crewai_tools/tools/brave_search_tool/base.py
+++ b/lib/crewai-tools/src/crewai_tools/tools/brave_search_tool/base.py
@@ -240,10 +240,9 @@ class BraveSearchToolBase(BaseTool, ABC):
             # (e.g., 422 Unprocessable Entity, 400 Bad Request (OPTION_NOT_IN_PLAN))
             _raise_for_error(resp)
 
-        # All retries exhausted
-        if last_resp is not None:
-            _raise_for_error(last_resp)
-        return {}
+        # All retries exhausted — last_resp is always set when we reach here
+        _raise_for_error(last_resp or resp)
+        return {}  # unreachable; satisfies return type
 
     def _run(self, q: str | None = None, **params: Any) -> Any:
         # Allow positional usage: tool.run("latest Brave browser features")
diff --git a/lib/crewai/src/crewai/flow/human_feedback.py b/lib/crewai/src/crewai/flow/human_feedback.py
index 7add43f7a..9bace438e 100644
--- a/lib/crewai/src/crewai/flow/human_feedback.py
+++ b/lib/crewai/src/crewai/flow/human_feedback.py
@@ -374,10 +374,8 @@ def human_feedback(
         ) -> Any:
             """Recall past HITL lessons and use LLM to pre-review the output."""
             try:
-                from crewai.memory.unified_memory import Memory
-
                 mem = flow_instance.memory
-                if not isinstance(mem, Memory):
+                if mem is None:
                     return method_output
                 query = f"human feedback lessons for {func.__name__}: {method_output!s}"
                 matches = mem.recall(query, source=learn_source)
@@ -412,10 +410,8 @@ def human_feedback(
         ) -> None:
             """Extract generalizable lessons from output + feedback, store in memory."""
             try:
-                from crewai.memory.unified_memory import Memory
-
                 mem = flow_instance.memory
-                if not isinstance(mem, Memory):
+                if mem is None:
                     return
                 llm_inst = _resolve_llm_instance()
                 prompt = _get_hitl_prompt("hitl_distill_user").format(
@@ -448,7 +444,7 @@ def human_feedback(
                         ]
 
                 if lessons:
-                    mem.remember_many(lessons, source=learn_source)
+                    mem.remember_many(lessons, source=learn_source)  # type: ignore[union-attr]
             except Exception:  # noqa: S110
                 pass  # non-critical: don't fail the flow because lesson storage failed