Give Hermes recognitions, not just photos: faces(), tracking ids, discovery

Hermes asked for structured detections instead of a bare JPEG. faces() returns the
faces in view with no photo: a persistent track id, bbox, detection confidence, how
long the person has been in view, and identity {name, similarity} or null, never a
made-up name. look() returns that same JSON as text plus the photo (send_image can
skip it); list_people() gives names and counts; robot://status and two prompts make
the server discoverable, where list_resources and list_prompts were empty. The
detector now tracks faces across frames (FaceTracker) and publishes the track id and
the identity as a second hypothesis.

Deliberately not built: embeddings in responses, age/gender attributes, auto-updating
face data, and a remote enroll tool (a prompt could make the robot call anyone "Kyle").

Checked end to end: a real Hermes turn on the local ornith model called faces() (0.03 s,
no image) and answered that Kyle was there at 0.78 similarity. Also: the camera is
calibrated (18 of 24 views, 0.296 px, outlier rejection added) and the calibration is
kept in pi/calibration and restored by the installer.

Co-Authored-By: Claude Sonnet 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01AFN8nRRCiDiMN7ChBpHJhs

ros/hermes_mcp/test/test_node.py

@@ -0,0 +1,16 @@
+import pytest
+
+rclpy = pytest.importorskip('rclpy')
+
+
+def test_the_node_constructs_without_a_token_and_does_not_serve(monkeypatch):
+    """Declaring a parameter twice raises at construction, and nothing else exercises the node."""
+    monkeypatch.delenv('ROBOT_MCP_TOKEN', raising=False)
+    from hermes_mcp.mcp_node import McpNode
+    rclpy.init()
+    try:
+        node = McpNode()
+        assert node.activity is None            # no token: not serving, no heartbeat
+        node.destroy_node()
+    finally:
+        rclpy.shutdown()