Initial project structure

Scaffold all modules, route stubs, data models, and config.
No logic implemented yet — all core methods raise NotImplementedError.
Establishes the full directory layout matching the architecture in CLAUDE.md.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

fellowship/core/orchestrator.py

@@ -0,0 +1,92 @@
+"""
+Orchestrator — stateless LLM call that selects the next speaker or ends the session.
+Called fresh each turn when turn_order is ORCHESTRATED.
+Output is a tool call only; any text is discarded.
+"""
+
+import logging
+from dataclasses import dataclass
+from typing import Literal, Optional, TYPE_CHECKING
+
+if TYPE_CHECKING:
+    from fellowship.core.session import Session
+
+logger = logging.getLogger(__name__)
+
+
+@dataclass
+class OrchestratorDecision:
+    action: Literal["select_speaker", "hold", "end_session"]
+    bot_name: Optional[str] = None    # set when action == "select_speaker"
+    reason: Optional[str] = None      # set when action == "end_session"
+
+
+# Tool definitions sent to the LLM with every orchestrator call
+ORCHESTRATOR_TOOLS = [
+    {
+        "type": "function",
+        "function": {
+            "name": "select_speaker",
+            "description": "Choose which bot should speak next.",
+            "parameters": {
+                "type": "object",
+                "properties": {
+                    "bot_name": {"type": "string", "description": "Name of the bot to speak next"},
+                },
+                "required": ["bot_name"],
+            },
+        },
+    },
+    {
+        "type": "function",
+        "function": {
+            "name": "hold",
+            "description": (
+                "Do not prompt any bot this turn. "
+                "Use when the conversation implies bots should stay silent."
+            ),
+            "parameters": {"type": "object", "properties": {}},
+        },
+    },
+    {
+        "type": "function",
+        "function": {
+            "name": "end_session",
+            "description": "End the session. Only use when the session goal has been reached.",
+            "parameters": {
+                "type": "object",
+                "properties": {
+                    "reason": {"type": "string", "description": "Why the session is ending"},
+                },
+                "required": ["reason"],
+            },
+        },
+    },
+]
+
+
+class Orchestrator:
+    def __init__(self, session: "Session") -> None:
+        self.session = session
+
+    async def decide(self) -> OrchestratorDecision:
+        """
+        Build the orchestrator prompt, call the LLM, parse the tool call response.
+        Any text output from the LLM is ignored — only the tool call matters.
+        """
+        raise NotImplementedError
+
+    def _build_system_prompt(self) -> str:
+        """
+        Build the orchestrator system prompt including:
+          - Its role and instructions
+          - Overview of how Fellowship works
+          - Full bot roster (names, roles, system prompts)
+          - Session goal (if set)
+          - Instruction to always respond with a tool call
+        """
+        raise NotImplementedError
+
+    def _parse_tool_call(self, response: dict) -> OrchestratorDecision:
+        """Parse the LLM tool call response into an OrchestratorDecision."""
+        raise NotImplementedError