feat(bias): implement ToolBiasEngine and integrate into ai_client orchestration loop

tests/test_bias_integration.py

@@ -0,0 +1,47 @@
+import pytest
+from src import ai_client
+from src.models import ToolPreset, Tool, BiasProfile
+from unittest.mock import MagicMock, patch
+
+def test_system_prompt_biasing():
+ # Setup
+ preset = ToolPreset(name="TestPreset", categories={
+  "General": [Tool(name="read_file", weight=5)]
+ })
+ bias = BiasProfile(name="TestBias", category_multipliers={"General": 1.5})
+ 
+ with patch("src.ai_client._active_tool_preset", preset):
+  with patch("src.ai_client._active_bias_profile", bias):
+   prompt = ai_client._get_combined_system_prompt()
+   
+   assert "Tooling Strategy" in prompt
+   assert "read_file" in prompt
+   assert "General" in prompt
+
+def test_tool_declaration_biasing_anthropic():
+ preset = ToolPreset(name="TestPreset", categories={
+  "General": [Tool(name="read_file", weight=5)]
+ })
+ 
+ with patch("src.ai_client._active_tool_preset", preset):
+  with patch("src.ai_client._agent_tools", {"read_file": True}):
+   # _get_anthropic_tools calls _build_anthropic_tools which should now use the bias engine
+   with patch("src.ai_client._CACHED_ANTHROPIC_TOOLS", None):
+    tools = ai_client._get_anthropic_tools()
+    
+    read_file_tool = next(t for t in tools if t["name"] == "read_file")
+    assert "[HIGH PRIORITY]" in read_file_tool["description"]
+
+@pytest.mark.asyncio
+async def test_set_tool_preset_with_objects():
+ # This tests that set_tool_preset correctly handles the new Tool objects
+ preset = ToolPreset(name="ObjTest", categories={
+  "General": [Tool(name="read_file", approval="auto")]
+ })
+ 
+ with patch("src.tool_presets.ToolPresetManager.load_all", return_value={"ObjTest": preset}):
+  ai_client.set_tool_preset("ObjTest")
+  
+  assert ai_client._agent_tools["read_file"] is True
+  assert ai_client._tool_approval_modes["read_file"] == "auto"
+  assert ai_client._active_tool_preset == preset

tests/test_tool_bias.py

@@ -0,0 +1,50 @@
+import pytest
+from src.tool_bias import ToolBiasEngine
+from src.models import ToolPreset, Tool, BiasProfile
+
+def test_apply_semantic_nudges():
+ engine = ToolBiasEngine()
+ preset = ToolPreset(name="test", categories={
+  "General": [
+   Tool(name="read_file", weight=5),
+   Tool(name="list_directory", weight=1)
+  ]
+ })
+ 
+ # Mock tool definitions (simplified MCP_TOOL_SPECS)
+ tool_defs = [
+  {"name": "read_file", "description": "Read file content.", "parameters": {"properties": {"path": {"description": "Path to file"}}}},
+  {"name": "list_directory", "description": "List dir.", "parameters": {"properties": {"path": {"description": "Path to dir"}}}}
+ ]
+ 
+ nudged = engine.apply_semantic_nudges(tool_defs, preset)
+ 
+ assert "[HIGH PRIORITY]" in nudged[0]["description"]
+ assert "[LOW PRIORITY]" in nudged[1]["description"]
+
+def test_parameter_bias_nudging():
+ engine = ToolBiasEngine()
+ preset = ToolPreset(name="test", categories={
+  "General": [
+   Tool(name="read_file", parameter_bias={"path": "PREFERRED"})
+  ]
+ })
+ 
+ tool_defs = [
+  {"name": "read_file", "description": "Read file.", "parameters": {"properties": {"path": {"description": "Path."}}, "required": ["path"]}}
+ ]
+ 
+ nudged = engine.apply_semantic_nudges(tool_defs, preset)
+ assert "[PREFERRED]" in nudged[0]["parameters"]["properties"]["path"]["description"]
+
+def test_generate_tooling_strategy():
+ engine = ToolBiasEngine()
+ preset = ToolPreset(name="test", categories={
+  "General": [Tool(name="read_file", weight=5)]
+ })
+ bias = BiasProfile(name="test", category_multipliers={"General": 2.0})
+ 
+ strategy = engine.generate_tooling_strategy(preset, bias)
+ assert "Tooling Strategy" in strategy
+ assert "read_file" in strategy
+ assert "General" in strategy