Ship gated eye polish, fabric levels, and collection UI refresh.

Topology MCP adds pull/compact/bundle/suggest-hubs with a no-template skill path; API gains fabric level and NE collection policy; web list pages get paging and denser collect/network workflows.

Co-authored-by: Cursor <cursoragent@cursor.com>

packages/netx-topology-mcp/tests/test_suggest_sink_hubs.py

@@ -0,0 +1,146 @@
+"""Tests for suggestSinkHubs batch ranking."""
+
+from __future__ import annotations
+
+from netx_topology_mcp.layout_ops.suggest_sink_hubs import (
+    pick_batch,
+    suggest_sink_hub_batches,
+)
+from netx_topology_mcp.layout_structure import analyze_graph_structure
+
+
+def _star_graph():
+    # CN portals + TJP-like agg hub with 3 EN stubs + small GENA hub with 1 stub
+    nodes = [
+        {"fabric_node_id": "cn1", "name": "X-CN1-Y", "level": 1, "x": 0, "y": 0},
+        {"fabric_node_id": "cn2", "name": "X-CN2-Y", "level": 1, "x": 100, "y": 0},
+        {"fabric_node_id": "tjp", "name": "X-TJP-AN1-Y", "level": 2, "x": 50, "y": 100},
+        {"fabric_node_id": "e1", "name": "X-E1-EN1-Y", "level": 3, "x": 0, "y": 200},
+        {"fabric_node_id": "e2", "name": "X-E2-EN1-Y", "level": 3, "x": 50, "y": 200},
+        {"fabric_node_id": "e3", "name": "X-E3-EN1-Y", "level": 3, "x": 100, "y": 200},
+        {"fabric_node_id": "gena", "name": "X-GENA-AN1-Y", "level": 2, "x": 200, "y": 100},
+        {"fabric_node_id": "e4", "name": "X-E4-EN1-Y", "level": 3, "x": 200, "y": 200},
+    ]
+    edges = [
+        {"a_node_id": "cn1", "b_node_id": "cn2"},
+        {"a_node_id": "cn1", "b_node_id": "tjp"},
+        {"a_node_id": "cn2", "b_node_id": "tjp"},
+        {"a_node_id": "tjp", "b_node_id": "e1"},
+        {"a_node_id": "tjp", "b_node_id": "e2"},
+        {"a_node_id": "tjp", "b_node_id": "e3"},
+        {"a_node_id": "cn2", "b_node_id": "gena"},
+        {"a_node_id": "gena", "b_node_id": "e4"},
+    ]
+    return nodes, edges
+
+
+def test_suggest_ranks_largest_territory_first() -> None:
+    nodes, edges = _star_graph()
+    struct = analyze_graph_structure(nodes, edges, hub_top_k=10)
+    src = {n["fabric_node_id"] for n in nodes}
+    report = suggest_sink_hub_batches(
+        hubs=struct["hubs"],
+        soft_blocks=struct["soft_blocks"],
+        source_ids=src,
+        sink_ids=set(),
+        dual_units=struct.get("dual_units"),
+        min_territory=1,
+        top_n=5,
+    )
+    assert report["ok"] is True
+    assert report["batch_count"] >= 1
+    top = report["batches"][0]
+    # TJP should beat GENA; CN portals must not lead
+    assert top["hub_id"] == "tjp"
+    assert "cn1" not in top["fabric_node_ids"]
+    assert "cn2" not in top["fabric_node_ids"]
+    assert set(top["fabric_node_ids"]) >= {"tjp", "e1", "e2", "e3"}
+
+
+def test_suggest_drops_ids_already_on_sink() -> None:
+    nodes, edges = _star_graph()
+    struct = analyze_graph_structure(nodes, edges, hub_top_k=10)
+    src = {n["fabric_node_id"] for n in nodes}
+    report = suggest_sink_hub_batches(
+        hubs=struct["hubs"],
+        soft_blocks=struct["soft_blocks"],
+        source_ids=src,
+        sink_ids={"e1", "e2"},
+        exclude_ids={"cn1", "cn2"},
+        min_territory=1,
+        top_n=5,
+    )
+    top = pick_batch(report, 1)
+    assert top is not None
+    assert top["hub_id"] == "tjp"
+    assert "e1" not in top["fabric_node_ids"]
+    assert "e2" not in top["fabric_node_ids"]
+    assert "e3" in top["fabric_node_ids"]
+
+
+def test_suggest_skips_portal_as_hub_leader() -> None:
+    nodes, edges = _star_graph()
+    struct = analyze_graph_structure(nodes, edges, hub_top_k=10)
+    src = {n["fabric_node_id"] for n in nodes}
+    report = suggest_sink_hub_batches(
+        hubs=struct["hubs"],
+        soft_blocks=struct["soft_blocks"],
+        source_ids=src,
+        exclude_ids={"tjp"},  # force skip TJP as leader id
+        dual_units={"units": [{"portal_a": "cn1", "portal_b": "cn2"}]},
+        min_territory=1,
+        top_n=5,
+    )
+    hubs = [b["hub_id"] for b in report["batches"]]
+    assert "cn1" not in hubs and "cn2" not in hubs
+    # Excluded hub may still emit stub-only batch (hub id not in move list)
+    tjp_batch = next((b for b in report["batches"] if b["hub_id"] == "tjp"), None)
+    assert tjp_batch is not None
+    assert "tjp" not in tjp_batch["fabric_node_ids"]
+    assert set(tjp_batch["fabric_node_ids"]) >= {"e1", "e2", "e3"}
+
+
+def test_suggest_moves_stubs_under_sunk_hub() -> None:
+    nodes, edges = _star_graph()
+    struct = analyze_graph_structure(nodes, edges, hub_top_k=10)
+    src = {n["fabric_node_id"] for n in nodes}
+    report = suggest_sink_hub_batches(
+        hubs=struct["hubs"],
+        soft_blocks=struct["soft_blocks"],
+        source_ids=src,
+        sink_ids={"tjp", "e1", "e2"},  # hub already on sink
+        exclude_ids={"cn1", "cn2"},
+        min_territory=1,
+        top_n=5,
+    )
+    tjp = next((b for b in report["batches"] if b["hub_id"] == "tjp"), None)
+    assert tjp is not None
+    assert tjp["already_on_sink"] is True
+    assert tjp["fabric_node_ids"] == ["e3"]
+
+
+def test_suggest_orphan_leftovers_batch() -> None:
+    nodes, edges = _star_graph()
+    # Add disconnected orphans on source
+    nodes = list(nodes) + [
+        {"fabric_node_id": "iso1", "name": "X-ISO1-EN1-Y", "level": 3, "x": 900, "y": 900},
+        {"fabric_node_id": "iso2", "name": "X-ISO2-EN1-Y", "level": 3, "x": 950, "y": 950},
+    ]
+    struct = analyze_graph_structure(nodes, edges, hub_top_k=10)
+    src = {n["fabric_node_id"] for n in nodes}
+    # Everything except orphans already on sink
+    sink = src - {"iso1", "iso2"}
+    report = suggest_sink_hub_batches(
+        hubs=struct["hubs"],
+        soft_blocks=struct["soft_blocks"],
+        source_ids=src,
+        sink_ids=sink,
+        exclude_ids={"cn1", "cn2"},
+        min_territory=0,
+        top_n=8,
+    )
+    assert report["orphan_n"] == 2
+    orphan = next((b for b in report["batches"] if b.get("orphan")), None)
+    assert orphan is not None
+    assert set(orphan["fabric_node_ids"]) == {"iso1", "iso2"}
+    assert orphan["block_method"] == "orphan_leftovers"