Pre-Action Grounding Guard

guardrail scans text for prompt-injection and loop_guard detects stuck loops — but neither validates a coordinate action before it is dispatched. An agent loop executes whatever the model returns with no bounds or target check, so a hallucinated (9999, -5) click fires into nothing and a 5-pixel-off click misses the button. validate_action adds the “detect misaligned actions before execution” guard: reject clicks outside the screen and snap a near-miss coordinate onto the nearest known element’s centre.

Pure-stdlib geometry over plain element dicts (x / y / width / height), so it is fully unit-testable. Imports no PySide6.

Headless API

from je_auto_control import validate_action, snap_to_element, in_bounds

check = validate_action(model_action, screen_size=(1920, 1080), targets=elements)
if not check["ok"]:
    print("rejected:", check["reason"])         # e.g. "out of bounds"
else:
    x, y = check["snapped"] or (model_action["x"], model_action["y"])
    click(x, y)                                  # snapped onto the real button

in_bounds(x, y, screen_size) is the screen-bounds predicate; snap_to_element returns the centre of the element at (or nearest within max_dist of) a point, or None; validate_action combines them, returning {ok, reason, snapped} — rejecting out-of-bounds coordinates and snapping near-misses when targets are supplied. Actions without a coordinate always pass.

Executor command

AC_validate_action (action / screen / targets → {ok, reason, snapped}; screen defaults to the live screen). It is exposed as the MCP tool ac_validate_action and as a Script Builder command under Native UI.