refactor(cleanup): remove legacy agent classes and complete EvoAgent migration

Remove deprecated AnalystAgent, PMAgent, and RiskAgent classes.
All agent creation now goes through UnifiedAgentFactory creating EvoAgent instances.

- Delete backend/agents/analyst.py (169 lines)
- Delete backend/agents/portfolio_manager.py (420 lines)
- Delete backend/agents/risk_manager.py (139 lines)
- Update all imports to use EvoAgent exclusively
- Clean up unused imports across 25 files
- Update tests to work with simplified agent structure

Constraint: EvoAgent is now the single source of truth for all agent roles
Constraint: UnifiedAgentFactory handles runtime agent creation
Rejected: Keep legacy aliases | creates maintenance burden
Confidence: high
Scope-risk: moderate (affects agent instantiation paths)
Directive: All new agent features must be added to EvoAgent, not legacy classes
Not-tested: Kubernetes sandbox executor (marked with TODO)

backend/core/pipeline_runner.py

@@ -14,7 +14,7 @@ from contextlib import AsyncExitStack
 from pathlib import Path
 from typing import Any, Dict, List, Optional, Callable
 
-from backend.agents import AnalystAgent, EvoAgent, PMAgent, RiskAgent
+from backend.agents import EvoAgent
 from backend.agents.agent_workspace import load_agent_workspace_config
 from backend.agents.skills_manager import SkillsManager
 from backend.agents.toolkit_factory import create_agent_toolkit, load_agent_profiles
@@ -235,34 +235,21 @@ def _create_analyst_agent(
         active_skill_dirs=active_skill_dirs,
     )
 
-    use_evo_agent = analyst_type in _resolve_evo_agent_ids()
-
-    if use_evo_agent:
-        workspace_dir = skills_manager.get_agent_asset_dir(run_id, analyst_type)
-        agent_config = load_agent_workspace_config(workspace_dir / "agent.yaml")
-        agent = EvoAgent(
-            agent_id=analyst_type,
-            config_name=run_id,
-            workspace_dir=workspace_dir,
-            model=model,
-            formatter=formatter,
-            skills_manager=skills_manager,
-            prompt_files=agent_config.prompt_files,
-            long_term_memory=long_term_memory,
-        )
-        agent.toolkit = toolkit
-        setattr(agent, "workspace_id", run_id)
-        return agent
-
-    return AnalystAgent(
-        analyst_type=analyst_type,
-        toolkit=toolkit,
+    workspace_dir = skills_manager.get_agent_asset_dir(run_id, analyst_type)
+    agent_config = load_agent_workspace_config(workspace_dir / "agent.yaml")
+    agent = EvoAgent(
+        agent_id=analyst_type,
+        config_name=run_id,
+        workspace_dir=workspace_dir,
         model=model,
         formatter=formatter,
-        agent_id=analyst_type,
-        config={"config_name": run_id},
+        skills_manager=skills_manager,
+        prompt_files=agent_config.prompt_files,
         long_term_memory=long_term_memory,
     )
+    agent.toolkit = toolkit
+    setattr(agent, "workspace_id", run_id)
+    return agent
 
 
 def _create_risk_manager_agent(
@@ -607,7 +594,7 @@ async def run_pipeline(
                 trading_calendar="NYSE",
                 delay_between_days=0.5,
             )
-            trading_dates = backtest_scheduler.get_trading_dates()
+            backtest_scheduler.get_trading_dates()
 
             async def scheduler_callback_fn(callback):
                 await backtest_scheduler.start(callback)