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

src/ai_client.py

@@ -31,6 +31,8 @@ from src import project_manager
 from src import file_cache
 from src import mcp_client
 from src import mma_prompts
+from src.tool_bias import ToolBiasEngine
+from src.models import ToolPreset, BiasProfile, Tool
 import anthropic
 from src.gemini_cli_adapter import GeminiCliAdapter as GeminiCliAdapter
 from google import genai
@@ -85,6 +87,10 @@ _minimax_history_lock: threading.Lock = threading.Lock()
 
 _send_lock: threading.Lock = threading.Lock()
 
+_BIAS_ENGINE = ToolBiasEngine()
+_active_tool_preset: Optional[ToolPreset] = None
+_active_bias_profile: Optional[BiasProfile] = None
+
 _gemini_cli_adapter: Optional[GeminiCliAdapter] = None
 
 # Injected by gui.py - called when AI wants to run a command.
@@ -139,10 +145,17 @@ def set_custom_system_prompt(prompt: str) -> None:
  global _custom_system_prompt
  _custom_system_prompt = prompt
 
-def _get_combined_system_prompt() -> str:
+def _get_combined_system_prompt(preset: Optional[ToolPreset] = None, bias: Optional[BiasProfile] = None) -> str:
+ if preset is None: preset = _active_tool_preset
+ if bias is None: bias = _active_bias_profile
+ base = _SYSTEM_PROMPT
  if _custom_system_prompt.strip():
-  return f"{_SYSTEM_PROMPT}\n\n[USER SYSTEM PROMPT]\n{_custom_system_prompt}"
- return _SYSTEM_PROMPT
+  base = f"{_SYSTEM_PROMPT}\n\n[USER SYSTEM PROMPT]\n{_custom_system_prompt}"
+ if preset and bias:
+  strategy = _BIAS_ENGINE.generate_tooling_strategy(preset, bias)
+  if strategy:
+   base += f"\n\n{strategy}"
+ return base
 
 from collections import deque
 
@@ -472,12 +485,13 @@ def set_agent_tools(tools: dict[str, bool]) -> None:
 
 def set_tool_preset(preset_name: Optional[str]) -> None:
  """Loads a tool preset and applies it via set_agent_tools."""
- global _agent_tools, _CACHED_ANTHROPIC_TOOLS, _tool_approval_modes
+ global _agent_tools, _CACHED_ANTHROPIC_TOOLS, _tool_approval_modes, _active_tool_preset
  _tool_approval_modes = {}
  if not preset_name or preset_name == "None":
   # Enable all tools if no preset
   _agent_tools = {name: True for name in mcp_client.TOOL_NAMES}
   _agent_tools[TOOL_NAME] = True
+  _active_tool_preset = None
  else:
   try:
    from src.tool_presets import ToolPresetManager
@@ -485,32 +499,49 @@ def set_tool_preset(preset_name: Optional[str]) -> None:
    presets = manager.load_all()
    if preset_name in presets:
     preset = presets[preset_name]
+    _active_tool_preset = preset
     new_tools = {name: False for name in mcp_client.TOOL_NAMES}
     new_tools[TOOL_NAME] = False
     for cat in preset.categories.values():
-     for tool_entry in cat:
-      if isinstance(tool_entry, dict) and "name" in tool_entry:
-       name = tool_entry["name"]
-       new_tools[name] = True
-       _tool_approval_modes[name] = tool_entry.get("mode", "ask")
+     for tool in cat:
+      name = tool.name
+      new_tools[name] = True
+      _tool_approval_modes[name] = tool.approval
     _agent_tools = new_tools
   except Exception as e:
    sys.stderr.write(f"[ERROR] Failed to set tool preset '{preset_name}': {e}\n")
    sys.stderr.flush()
  _CACHED_ANTHROPIC_TOOLS = None
 
+def set_bias_profile(profile_name: Optional[str]) -> None:
+ global _active_bias_profile
+ if not profile_name or profile_name == "None":
+  _active_bias_profile = None
+ else:
+  try:
+   from src.tool_presets import ToolPresetManager
+   manager = ToolPresetManager()
+   profiles = manager.load_all_bias_profiles()
+   if profile_name in profiles:
+    _active_bias_profile = profiles[profile_name]
+  except Exception as e:
+   sys.stderr.write(f"[ERROR] Failed to set bias profile '{profile_name}': {e}\n")
+   sys.stderr.flush()
+
+def get_bias_profile() -> Optional[str]:
+ return _active_bias_profile.name if _active_bias_profile else None
+
 def _build_anthropic_tools() -> list[dict[str, Any]]:
- mcp_tools: list[dict[str, Any]] = []
+ raw_tools: list[dict[str, Any]] = []
  for spec in mcp_client.MCP_TOOL_SPECS:
   if _agent_tools.get(spec["name"], True):
-   mcp_tools.append({
-     "name":        spec["name"],
+   raw_tools.append({
+     "name": spec["name"],
      "description": spec["description"],
      "input_schema": spec["parameters"],
     })
- tools_list = mcp_tools
  if _agent_tools.get(TOOL_NAME, True):
-  powershell_tool: dict[str, Any] = {
+  raw_tools.append({
    "name": TOOL_NAME,
    "description": (
     "Run a PowerShell script within the project base_dir. "
@@ -528,13 +559,13 @@ def _build_anthropic_tools() -> list[dict[str, Any]]:
      }
     },
     "required": ["script"]
-   },
-   "cache_control": {"type": "ephemeral"},
-  }
-  tools_list.append(powershell_tool)
- elif tools_list:
-  tools_list[-1]["cache_control"] = {"type": "ephemeral"}
- return tools_list
+   }
+  })
+ if _active_tool_preset:
+  _BIAS_ENGINE.apply_semantic_nudges(raw_tools, _active_tool_preset)
+ if raw_tools:
+  raw_tools[-1]["cache_control"] = {"type": "ephemeral"}
+ return raw_tools
 
 _CACHED_ANTHROPIC_TOOLS: Optional[list[dict[str, Any]]] = None
 
@@ -545,12 +576,42 @@ def _get_anthropic_tools() -> list[dict[str, Any]]:
  return _CACHED_ANTHROPIC_TOOLS
 
 def _gemini_tool_declaration() -> Optional[types.Tool]:
- declarations: list[types.FunctionDeclaration] = []
+ raw_tools: list[dict[str, Any]] = []
  for spec in mcp_client.MCP_TOOL_SPECS:
-  if not _agent_tools.get(spec["name"], True):
-   continue
+  if _agent_tools.get(spec["name"], True):
+   raw_tools.append({
+    "name": spec["name"],
+    "description": spec["description"],
+    "parameters": spec["parameters"]
+   })
+ if _agent_tools.get(TOOL_NAME, True):
+  raw_tools.append({
+   "name": TOOL_NAME,
+   "description": (
+    "Run a PowerShell script within the project base_dir. "
+    "Use this to create, edit, rename, or delete files and directories. "
+    "The working directory is set to base_dir automatically. "
+    "Always prefer targeted edits over full rewrites where possible. "
+    "stdout and stderr are returned to you as the result."
+   ),
+   "parameters": {
+    "type": "object",
+    "properties": {
+     "script": {
+      "type": "string",
+      "description": "The PowerShell script to execute."
+     }
+    },
+    "required": ["script"]
+   }
+  })
+ if _active_tool_preset:
+  _BIAS_ENGINE.apply_semantic_nudges(raw_tools, _active_tool_preset)
+ declarations: list[types.FunctionDeclaration] = []
+ for tool_def in raw_tools:
   props = {}
-  for pname, pdef in spec["parameters"].get("properties", {}).items():
+  params = tool_def.get("parameters", {})
+  for pname, pdef in params.get("properties", {}).items():
    ptype_str = pdef.get("type", "string").upper()
    ptype = getattr(types.Type, ptype_str, types.Type.STRING)
    props[pname] = types.Schema(
@@ -558,34 +619,14 @@ def _gemini_tool_declaration() -> Optional[types.Tool]:
     description=pdef.get("description", ""),
    )
   declarations.append(types.FunctionDeclaration(
-    name=spec["name"],
-    description=spec["description"],
-    parameters=types.Schema(
-     type=types.Type.OBJECT,
-     properties=props,
-     required=spec["parameters"].get("required", []),
-    ),
-   ))
- if _agent_tools.get(TOOL_NAME, True):
-  declarations.append(types.FunctionDeclaration(
-    name=TOOL_NAME,
-    description=(
-     "Run a PowerShell script within the project base_dir. "
-     "Use this to create, edit, rename, or delete files and directories. "
-     "The working directory is set to base_dir automatically. "
-     "stdout and stderr are returned to you as the result."
-    ),
-    parameters=types.Schema(
-     type=types.Type.OBJECT,
-     properties={
-      "script": types.Schema(
-       type=types.Type.STRING,
-       description="The PowerShell script to execute."
-      )
-     },
-     required=["script"]
-    ),
-   ))
+   name=tool_def["name"],
+   description=tool_def["description"],
+   parameters=types.Schema(
+    type=types.Type.OBJECT,
+    properties=props,
+    required=params.get("required", []),
+   ),
+  ))
  return types.Tool(function_declarations=declarations) if declarations else None
 
 async def _execute_tool_calls_concurrently(
@@ -772,43 +813,47 @@ def _build_file_diff_text(changed_items: list[dict[str, Any]]) -> str:
  return "\n\n---\n\n".join(parts)
 
 def _build_deepseek_tools() -> list[dict[str, Any]]:
- mcp_tools: list[dict[str, Any]] = []
+ raw_tools: list[dict[str, Any]] = []
  for spec in mcp_client.MCP_TOOL_SPECS:
   if _agent_tools.get(spec["name"], True):
-   mcp_tools.append({
-     "type": "function",
-     "function": {
-      "name":        spec["name"],
-      "description": spec["description"],
-      "parameters":  spec["parameters"],
-     }
-    })
- tools_list = mcp_tools
+   raw_tools.append({
+    "name": spec["name"],
+    "description": spec["description"],
+    "parameters": spec["parameters"]
+   })
  if _agent_tools.get(TOOL_NAME, True):
-  powershell_tool: dict[str, Any] = {
+  raw_tools.append({
+   "name": TOOL_NAME,
+   "description": (
+    "Run a PowerShell script within the project base_dir. "
+    "Use this to create, edit, rename, or delete files and directories. "
+    "The working directory is set to base_dir automatically. "
+    "Always prefer targeted edits over full rewrites where possible. "
+    "stdout and stderr are returned to you as the result."
+   ),
+   "parameters": {
+    "type": "object",
+    "properties": {
+     "script": {
+      "type": "string",
+      "description": "The PowerShell script to execute."
+     }
+    },
+    "required": ["script"]
+   }
+  })
+ if _active_tool_preset:
+  _BIAS_ENGINE.apply_semantic_nudges(raw_tools, _active_tool_preset)
+ tools_list: list[dict[str, Any]] = []
+ for tool_def in raw_tools:
+  tools_list.append({
    "type": "function",
    "function": {
-    "name": TOOL_NAME,
-    "description": (
-     "Run a PowerShell script within the project base_dir. "
-     "Use this to create, edit, rename, or delete files and directories. "
-     "The working directory is set to base_dir automatically. "
-     "Always prefer targeted edits over full rewrites where possible. "
-     "stdout and stderr are returned to you as the result."
-    ),
-    "parameters": {
-     "type": "object",
-     "properties": {
-      "script": {
-       "type": "string",
-       "description": "The PowerShell script to execute."
-      }
-     },
-     "required": ["script"]
-    }
+    "name": tool_def["name"],
+    "description": tool_def["description"],
+    "parameters": tool_def["parameters"],
    }
-  }
-  tools_list.append(powershell_tool)
+  })
  return tools_list
 
 _CACHED_DEEPSEEK_TOOLS: Optional[list[dict[str, Any]]] = None
@@ -2154,7 +2199,7 @@ def send(
 ) -> str:
  monitor = performance_monitor.get_monitor()
  if monitor.enabled: monitor.start_component("ai_client.send")
- _append_comms("OUT", "request", {"message": user_message, "system": _get_combined_system_prompt()})
+ _append_comms("OUT", "request", {"message": user_message, "system": _get_combined_system_prompt(_active_tool_preset, _active_bias_profile)})
  with _send_lock:
   if _provider == "gemini":
    res = _send_gemini(

src/tool_bias.py

@@ -0,0 +1,55 @@
+from typing import List, Dict, Any, Optional
+from src.models import Tool, ToolPreset, BiasProfile
+
+class ToolBiasEngine:
+ def apply_semantic_nudges(self, tool_definitions: List[Dict[str, Any]], preset: ToolPreset) -> List[Dict[str, Any]]:
+  weight_map = {
+   5: "[HIGH PRIORITY] ",
+   4: "[PREFERRED] ",
+   2: "[NOT RECOMMENDED] ",
+   1: "[LOW PRIORITY] "
+  }
+  
+  preset_tools: Dict[str, Tool] = {}
+  for cat_tools in preset.categories.values():
+   for t in cat_tools:
+    if isinstance(t, Tool):
+     preset_tools[t.name] = t
+  
+  for defn in tool_definitions:
+   name = defn.get("name")
+   if name in preset_tools:
+    tool = preset_tools[name]
+    prefix = weight_map.get(tool.weight, "")
+    if prefix:
+     defn["description"] = prefix + defn.get("description", "")
+    
+    if tool.parameter_bias:
+     params = defn.get("parameters") or defn.get("input_schema")
+     if params and "properties" in params:
+      props = params["properties"]
+      for p_name, bias in tool.parameter_bias.items():
+       if p_name in props:
+        p_desc = props[p_name].get("description", "")
+        props[p_name]["description"] = f"[{bias}] {p_desc}".strip()
+  
+  return tool_definitions
+
+ def generate_tooling_strategy(self, preset: ToolPreset, global_bias: BiasProfile) -> str:
+  lines = ["### Tooling Strategy"]
+  
+  preferred = []
+  for cat_tools in preset.categories.values():
+   for t in cat_tools:
+    if isinstance(t, Tool) and t.weight >= 4:
+     preferred.append(t.name)
+  
+  if preferred:
+   lines.append(f"Preferred tools: {', '.join(preferred)}.")
+  
+  if global_bias.category_multipliers:
+   lines.append("Category focus multipliers:")
+   for cat, mult in global_bias.category_multipliers.items():
+    lines.append(f"- {cat}: {mult}x")
+    
+  return "\n\n".join(lines)