update eval-driven-dev skill (#1434)

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* update eval driven dev

skills/eval-driven-dev/references/runnable-examples/standalone-function.md

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+# Runnable Example: Standalone Function (No Server)
+
+**When the app is a plain Python function or module** — no web framework, no server, no infrastructure.
+
+**Approach**: Import and call the function directly from `run()`. This is the simplest case.
+
+```python
+# pixie_qa/run_app.py
+from pydantic import BaseModel
+import pixie
+
+
+class AppArgs(BaseModel):
+    question: str
+
+
+class AppRunnable(pixie.Runnable[AppArgs]):
+    """Drives a standalone function for tracing and evaluation."""
+
+    @classmethod
+    def create(cls) -> "AppRunnable":
+        return cls()
+
+    async def run(self, args: AppArgs) -> None:
+        from myapp.agent import answer_question
+        await answer_question(args.question)
+```
+
+If the function is synchronous, wrap it with `asyncio.to_thread`:
+
+```python
+import asyncio
+
+async def run(self, args: AppArgs) -> None:
+    from myapp.agent import answer_question
+    await asyncio.to_thread(answer_question, args.question)
+```
+
+If the function depends on an external service (e.g., a vector store), the `wrap(purpose="input")` calls you added in Step 2a handle it automatically — the registry injects test data in eval mode.
+
+### When to use `setup()` / `teardown()`
+
+Most standalone functions don't need lifecycle methods. Use them only when the function requires a shared resource (e.g., a pre-loaded embedding model, a database connection):
+
+```python
+class AppRunnable(pixie.Runnable[AppArgs]):
+    _model: SomeModel
+
+    @classmethod
+    def create(cls) -> "AppRunnable":
+        return cls()
+
+    async def setup(self) -> None:
+        from myapp.models import load_model
+        self._model = load_model()
+
+    async def run(self, args: AppArgs) -> None:
+        from myapp.agent import answer_question
+        await answer_question(args.question, model=self._model)
+```