feat(agent-runtime): add LLM-driven AI Planner with dual-provider tool calling

Replaces the stub Planner's fixed describe_screen/[] behavior with a real
decision-maker: AIPlanner uses native tool/function calling (Anthropic or
OpenAI, pluggable via AI_PLANNER_PROVIDER) to select exactly one grounded
action per turn, with an explicit finish_task(success, reason) tool for
completion/failure instead of an ambiguous "no tool call" signal. Default
disabled (AI_PLANNER_ENABLED=false) and additive; TaskRunner falls back to
the existing stub Planner unchanged when disabled.

Amends CONSTITUTION.md's Perception Boundary with one narrow exception:
only the AI Planner may receive the current step's raw screenshot bytes
alongside Scene, for vision-grounded coordinate grounding. Also fixes a
latent gap in TaskRunner.run(): observe/plan exceptions are now caught per
iteration and turned into a failed task with a failure_reason, instead of
propagating uncaught.

openspec change: ai-planner-runtime.

Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>

runtime/planner_prompts.py

@@ -0,0 +1,42 @@
+from __future__ import annotations
+
+import json
+from typing import Any
+
+PLANNER_SYSTEM_PROMPT = """You are the planning brain of a mobile device automation agent.
+
+Each turn you are given a goal, the current screen as a structured Scene (a
+list of UI elements with id, type, text, and pixel bounds), and — when
+available — a screenshot of the same screen and a short history of recent
+actions and their outcomes.
+
+You must call exactly one tool per turn:
+- One of `tap`, `swipe`, `input_text`, `launch_app`, `terminate_app` to make
+  progress toward the goal.
+- `finish_task` when the goal has been reached, or when it cannot be reached
+  and no further action would help.
+
+Ground every coordinate you choose in the Scene element bounds (and the
+screenshot, if provided) for the current turn only — never reuse coordinates
+from history, since the screen may have changed. Only call `finish_task` with
+`success=True` when the current Scene shows the goal has actually been
+reached. Call it with `success=False` and a clear `reason` if you are stuck,
+repeating the same action without progress, or the goal is not achievable.
+"""
+
+
+def planner_user_prompt(
+    *,
+    goal: str,
+    scene_json: dict[str, Any],
+    history_summary: list[dict[str, Any]],
+) -> str:
+    return (
+        "Goal:\n"
+        f"{goal}\n\n"
+        "Current Scene (JSON):\n"
+        f"{json.dumps(scene_json, ensure_ascii=False, sort_keys=True)}\n\n"
+        "Recent history, oldest first (JSON):\n"
+        f"{json.dumps(history_summary, ensure_ascii=False, sort_keys=True)}\n\n"
+        "Call exactly one tool for this turn."
+    )