Lift drill into evals/ at 013fcb8b7dbefd6d3fa4653493e5d2ec8e7f985b

rsync of obra/drill@013fcb8b7d into superpowers/evals/, excluding
.git/, .venv/, results/, .env/, __pycache__/, *.egg-info/,
.private-journal/.

The drill repo is unaffected by this commit; archival is a separate
manual step after this PR merges.

Source SHA recorded at evals/.drill-source-sha for divergence
detection.

evals/drill/actor.py

@@ -0,0 +1,81 @@
+"""Actor LLM: simulates a user driving an agent session."""
+
+from __future__ import annotations
+
+from dataclasses import dataclass
+from pathlib import Path
+from typing import Any
+
+import anthropic
+from jinja2 import Template
+
+ACTOR_TOOL: dict[str, Any] = {
+    "name": "terminal_action",
+    "description": "Send an action to the terminal session.",
+    "input_schema": {
+        "type": "object",
+        "properties": {
+            "action": {
+                "type": "string",
+                "enum": ["type", "done", "stuck", "key"],
+                "description": "The action to take.",
+            },
+            "text": {
+                "type": "string",
+                "description": "Text to type (only for 'type' action).",
+            },
+            "key": {
+                "type": "string",
+                "description": "Special key to send (only for 'key' action, e.g., 'ctrl-c').",
+            },
+        },
+        "required": ["action"],
+    },
+}
+
+
+@dataclass
+class ActorAction:
+    action: str
+    text: str | None = None
+    key: str | None = None
+
+    @classmethod
+    def from_tool_result(cls, data: dict[str, Any]) -> ActorAction:
+        return cls(action=data["action"], text=data.get("text"), key=data.get("key"))
+
+
+class Actor:
+    def __init__(self, model: str = "claude-sonnet-4-6", temperature: float = 0.7) -> None:
+        self.model = model
+        self.temperature = temperature
+        self.captures: list[str] = []
+        self._system_prompt: str = ""
+        self._client: anthropic.Anthropic = anthropic.Anthropic()
+
+    def build_system_prompt(self, posture: str, intents: list[str]) -> str:
+        template_path = Path(__file__).parent.parent / "prompts" / "actor.md"
+        template = Template(template_path.read_text())
+        self._system_prompt = template.render(posture=posture, intents=intents)
+        return self._system_prompt
+
+    def append_capture(self, terminal_output: str) -> None:
+        self.captures.append(terminal_output)
+
+    def build_messages(self) -> list[dict[str, str]]:
+        return [{"role": "user", "content": capture} for capture in self.captures]
+
+    def decide(self) -> ActorAction:
+        response = self._client.messages.create(
+            model=self.model,
+            max_tokens=1024,
+            temperature=self.temperature,
+            system=self._system_prompt,
+            tools=[ACTOR_TOOL],  # ty: ignore[invalid-argument-type]
+            tool_choice={"type": "tool", "name": "terminal_action"},
+            messages=self.build_messages(),  # ty: ignore[invalid-argument-type]
+        )
+        for block in response.content:
+            if block.type == "tool_use":
+                return ActorAction.from_tool_result(block.input)
+        raise RuntimeError("Actor did not return a tool_use block")