Refactor tests for execution plan and add comprehensive storage tests

- Updated `TestModuleSingletons` in `test_execution_plan.py` to reflect new agent templates and playbook names.
- Changed assertions in playbook tests to match updated templates and agents.
- Introduced `test_storage.py` to cover the storage layer, including encryption, BlobStore, and VectorStore functionalities.
- Added tests for S3 interactions, ensuring upload, download, delete, and list operations work as expected.
- Implemented mock tests for Pinecone and Qdrant vector stores to validate upsert, search, and delete operations.

app/agents/note_agent.py

@@ -0,0 +1,123 @@
+"""Note agent — Markdown note management (list, get, create, update, delete)."""
+
+from __future__ import annotations
+
+import json
+from typing import Any
+
+from langchain_core.messages import HumanMessage, SystemMessage
+from langchain_core.tools import tool
+from langchain_openai import ChatOpenAI
+
+from app.config.settings import settings
+from app.core.agent_registry import ChatAgent, registry
+
+_SYSTEM_PROMPT = (
+    "You are a note-taking assistant. You help users create, retrieve, update,\n"
+    "and delete Markdown notes in their workspace.\n\n"
+    "Rules:\n"
+    "  - content is always Markdown; preserve formatting when updating\n"
+    "  - project_id is optional; link a note to a project when mentioned\n"
+    "  - When updating, call get_note first if you need to read existing content\n"
+    "    before appending or replacing sections\n"
+    "  - list_notes without project_id returns all notes; scope with project_id\n"
+    "    when the user is working within a specific project\n"
+    "  - Do not fabricate note content — reflect what the user provides or what\n"
+    "    is already in the note (retrieved via get_note)."
+)
+
+
+@tool
+async def list_notes(project_id: str = "") -> str:
+    """List notes, optionally scoped to a project by project_id."""
+    return json.dumps({
+        "action": "list",
+        "table": "notes",
+        "filters": {"projectId": project_id or None},
+    })
+
+
+@tool
+async def get_note(note_id: str) -> str:
+    """Fetch a single note by its UUID to read its full Markdown content."""
+    return json.dumps({
+        "action": "get",
+        "table": "notes",
+        "data": {"id": note_id},
+    })
+
+
+@tool
+async def create_note(
+    title: str,
+    content: str,
+    project_id: str = "",
+) -> str:
+    """Create a new note.
+    title: note heading (required)
+    content: Markdown body text (required)
+    project_id: optional UUID linking this note to a project
+    """
+    return json.dumps({
+        "action": "create_record",
+        "table": "notes",
+        "data": {
+            "title": title,
+            "content": content,
+            "projectId": project_id or None,
+        },
+    })
+
+
+@tool
+async def update_note(
+    note_id: str,
+    title: str = "",
+    content: str = "",
+) -> str:
+    """Update an existing note. Only pass fields that should change.
+    note_id: UUID of the note (required)
+    If you need to preserve existing content, call get_note first.
+    """
+    updates: dict[str, Any] = {}
+    if title:
+        updates["title"] = title
+    if content:
+        updates["content"] = content
+    return json.dumps({
+        "action": "update_record",
+        "table": "notes",
+        "data": {"id": note_id, "updates": updates},
+    })
+
+
+@tool
+async def delete_note(note_id: str) -> str:
+    """Delete a note permanently by its UUID."""
+    return json.dumps({
+        "action": "delete_record",
+        "table": "notes",
+        "data": {"id": note_id},
+    })
+
+
+@registry.register
+class NoteAgent(ChatAgent):
+    def get_name(self) -> str:
+        return "note_agent"
+
+    def get_description(self) -> str:
+        return "Manages notes: list, get, create, update, delete"
+
+    def get_tools(self) -> list[Any]:
+        return [list_notes, get_note, create_note, update_note, delete_note]
+
+    async def handle(self, query: str, context: dict[str, Any]) -> str:
+        llm = ChatOpenAI(model="gpt-4o", temperature=0, api_key=settings.OPENAI_API_KEY)
+        messages = [
+            SystemMessage(content=_SYSTEM_PROMPT),
+            HumanMessage(
+                content=f"User query: {query}\nContext: {json.dumps(context)[:1000]}"
+            ),
+        ]
+        return await self._tool_loop(llm, messages, self.get_tools())