feat(#144): Implement agent profiles

- Add Capability enum (HIGH, MEDIUM, LOW) for agent difficulty levels
- Add AgentName enum for all 5 agents (opus, sonnet, haiku, glm, minimax)
- Implement AgentProfile data structure with validation
  - context_limit: max tokens for context window
  - cost_per_mtok: cost per million tokens (0 for self-hosted)
  - capabilities: list of difficulty levels the agent handles
  - best_for: description of optimal use cases
- Define profiles for all 5 agents with specifications:
  - Anthropic models (opus, sonnet, haiku): 200K context, various costs
  - Self-hosted models (glm, minimax): 128K context, free
- Implement get_agent_profile() function for profile lookup
- Add comprehensive test suite (37 tests, 100% coverage)
  - Profile data structure validation
  - All 5 predefined profiles exist and are correct
  - Capability enum and AgentName enum tests
  - Best_for validation and capability matching
  - Consistency checks across profiles

Fixes #144
Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>

apps/coordinator/src/models.py

@@ -6,6 +6,24 @@ from typing import Literal
 from pydantic import BaseModel, Field, field_validator
 
 
+class Capability(str, Enum):
+    """Agent capability levels."""
+
+    HIGH = "high"
+    MEDIUM = "medium"
+    LOW = "low"
+
+
+class AgentName(str, Enum):
+    """Available AI agents."""
+
+    OPUS = "opus"
+    SONNET = "sonnet"
+    HAIKU = "haiku"
+    GLM = "glm"
+    MINIMAX = "minimax"
+
+
 class ContextAction(str, Enum):
     """Actions to take based on context usage thresholds."""
 
@@ -108,3 +126,88 @@ class IssueMetadata(BaseModel):
         if v is None:
             return []
         return v
+
+
+class AgentProfile(BaseModel):
+    """Profile defining agent capabilities, costs, and context limits."""
+
+    name: AgentName = Field(description="Agent identifier")
+    context_limit: int = Field(
+        gt=0,
+        description="Maximum tokens for agent context window"
+    )
+    cost_per_mtok: float = Field(
+        ge=0.0,
+        description="Cost per million tokens (0 for self-hosted)"
+    )
+    capabilities: list[Capability] = Field(
+        min_length=1,
+        description="Difficulty levels this agent can handle"
+    )
+    best_for: str = Field(
+        min_length=1,
+        description="Optimal use cases for this agent"
+    )
+
+    @field_validator("best_for", mode="before")
+    @classmethod
+    def validate_best_for_not_empty(cls, v: str) -> str:
+        """Ensure best_for description is not empty."""
+        if not v or not v.strip():
+            raise ValueError("best_for description cannot be empty")
+        return v
+
+
+# Predefined agent profiles
+AGENT_PROFILES: dict[AgentName, AgentProfile] = {
+    AgentName.OPUS: AgentProfile(
+        name=AgentName.OPUS,
+        context_limit=200000,
+        cost_per_mtok=15.0,
+        capabilities=[Capability.HIGH, Capability.MEDIUM, Capability.LOW],
+        best_for="Complex reasoning, code generation, and multi-step problem solving"
+    ),
+    AgentName.SONNET: AgentProfile(
+        name=AgentName.SONNET,
+        context_limit=200000,
+        cost_per_mtok=3.0,
+        capabilities=[Capability.MEDIUM, Capability.LOW],
+        best_for="Balanced performance for general tasks and scripting"
+    ),
+    AgentName.HAIKU: AgentProfile(
+        name=AgentName.HAIKU,
+        context_limit=200000,
+        cost_per_mtok=0.8,
+        capabilities=[Capability.LOW],
+        best_for="Fast, cost-effective processing of simple tasks"
+    ),
+    AgentName.GLM: AgentProfile(
+        name=AgentName.GLM,
+        context_limit=128000,
+        cost_per_mtok=0.0,
+        capabilities=[Capability.MEDIUM, Capability.LOW],
+        best_for="Self-hosted open-source model for medium complexity tasks"
+    ),
+    AgentName.MINIMAX: AgentProfile(
+        name=AgentName.MINIMAX,
+        context_limit=128000,
+        cost_per_mtok=0.0,
+        capabilities=[Capability.LOW],
+        best_for="Self-hosted lightweight model for simple tasks and prototyping"
+    ),
+}
+
+
+def get_agent_profile(agent_name: AgentName) -> AgentProfile:
+    """Retrieve profile for a specific agent.
+
+    Args:
+        agent_name: Name of the agent
+
+    Returns:
+        AgentProfile for the requested agent
+
+    Raises:
+        KeyError: If agent_name is not defined
+    """
+    return AGENT_PROFILES[agent_name]