deep q/a skill and skill selection

src/haiku/rag/a2a.py

@@ -228,10 +228,44 @@ def get_agent_skills() -> list[Skill]:
                 "Find information about Python best practices",
                 "Show me the full API documentation",
             ],
-        )
+        ),
+        Skill(
+            id="deep-qa",
+            name="Deep Question Answering",
+            description="Multi-step question decomposition and research for complex queries (can take a long time)",
+            tags=["question-answering", "research", "multi-agent", "complex-queries"],
+            input_modes=["application/json"],
+            output_modes=["application/json"],
+            examples=[
+                "What are the architectural patterns used in haiku.rag and how do they compare?",
+                "Analyze the trade-offs between the simple QA and research agents",
+                "What are all the configuration options and their effects?",
+            ],
+        ),
     ]
 
 
+def extract_skill_preference(task_history: list[Message]) -> str:
+    """Extract skill preference from task history metadata.
+
+    Args:
+        task_history: Task history messages
+
+    Returns:
+        Skill ID if found in metadata, otherwise "document-qa" (default)
+    """
+    for msg in task_history:
+        if msg.get("role") == "user":
+            for part in msg.get("parts", []):
+                if part.get("kind") == "data":
+                    metadata = part.get("metadata", {})
+                    if metadata.get("type") == "skill_preference":
+                        skill = part.get("data", {}).get("skill")
+                        if skill:
+                            return skill
+    return "document-qa"
+
+
 def extract_question_from_task(task_history: list[Message]) -> str | None:
     """Extract the user's question from task history.
 
@@ -340,12 +374,17 @@ def create_a2a_app(db_path: Path):
 
             await self.storage.update_task(task["id"], state="working")
 
-            # Extract the user's question
+            # Extract skill preference and question
-            question = extract_question_from_task(task.get("history", []))
+            task_history = task.get("history", [])
+            skill = extract_skill_preference(task_history)
+            question = extract_question_from_task(task_history)
+
             if not question:
                 await self.storage.update_task(task["id"], state="failed")
                 return
 
+            logger.info(f"Task {task['id']} using skill: {skill}")
+
             try:
                 # Load conversation context
                 context = await self.storage.load_context(task["context_id"]) or []

tests/test_a2a.py

@@ -4,6 +4,8 @@ import pytest
 
 from haiku.rag.a2a import (
     extract_question_from_task,
+    extract_skill_preference,
+    get_agent_skills,
     load_message_history,
     save_message_history,
 )
@@ -260,3 +262,92 @@ async def test_a2a_app_has_skills(temp_db_path):
         keyword in skill_text
         for keyword in ["search", "question", "answer", "document", "knowledge"]
     )
+
+
+def test_get_agent_skills():
+    """Test that agent skills include both document-qa and deep-qa."""
+    skills = get_agent_skills()
+
+    assert len(skills) == 2
+
+    skill_ids = [skill["id"] for skill in skills]
+    assert "document-qa" in skill_ids
+    assert "deep-qa" in skill_ids
+
+    # Check document-qa skill
+    doc_qa = next(s for s in skills if s["id"] == "document-qa")
+    assert "Document Question Answering" in doc_qa["name"]
+    assert "semantic search" in doc_qa["description"]
+    assert "question-answering" in doc_qa["tags"]
+
+    # Check deep-qa skill
+    deep_qa = next(s for s in skills if s["id"] == "deep-qa")
+    assert "Deep Question Answering" in deep_qa["name"]
+    assert "Multi-step" in deep_qa["description"]
+    assert "research" in deep_qa["tags"]
+
+
+@pytest.mark.asyncio
+async def test_extract_skill_preference_with_metadata():
+    """Test extracting skill preference from message metadata."""
+    from fasta2a.schema import DataPart
+
+    task_history: list[Message] = [
+        Message(
+            role="user",
+            parts=[
+                TextPart(kind="text", text="Complex question"),
+                DataPart(
+                    kind="data",
+                    data={"skill": "deep-qa"},
+                    metadata={"type": "skill_preference"},
+                ),
+            ],
+            kind="message",
+            message_id=str(uuid.uuid4()),
+        )
+    ]
+
+    skill = extract_skill_preference(task_history)
+    assert skill == "deep-qa"
+
+
+@pytest.mark.asyncio
+async def test_extract_skill_preference_default():
+    """Test that skill preference defaults to document-qa."""
+    task_history: list[Message] = [
+        Message(
+            role="user",
+            parts=[TextPart(kind="text", text="What is Python?")],
+            kind="message",
+            message_id=str(uuid.uuid4()),
+        )
+    ]
+
+    skill = extract_skill_preference(task_history)
+    assert skill == "document-qa"
+
+
+@pytest.mark.asyncio
+async def test_extract_skill_preference_no_skill_in_data():
+    """Test skill preference when DataPart exists but has no skill."""
+    from fasta2a.schema import DataPart
+
+    task_history: list[Message] = [
+        Message(
+            role="user",
+            parts=[
+                TextPart(kind="text", text="Question"),
+                DataPart(
+                    kind="data",
+                    data={"other": "value"},
+                    metadata={"type": "skill_preference"},
+                ),
+            ],
+            kind="message",
+            message_id=str(uuid.uuid4()),
+        )
+    ]
+
+    skill = extract_skill_preference(task_history)
+    assert skill == "document-qa"