diff --git a/tests/perf_guards/test_pattern_b_scaling.py b/tests/perf_guards/test_pattern_b_scaling.py
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+"""Pattern-B perf-regression guards: hot paths must not degrade to O(N²)/O(N·Q).
+
+Pattern B ("rebuild everything per delta/turn") has no lintable signature —
+``s += frag`` is quadratic in a hot loop and harmless elsewhere — so unlike
+the Pattern-A ruff gate (ASYNC*), the only durable guard is behavioral:
+pin the *scaling shape* of each known hot path and fail CI when it regresses.
+
+Guard design rules (to stay CI-stable):
+1. Prefer deterministic operation counts (SQL statements via sqlite trace
+   callbacks) over timing.  Counts cannot flake.
+2. Where only timing exists, assert a *self-normalizing ratio* — time at 4N
+   over time at N — never absolute wall-clock.  Linear paths give ~4 (with
+   allocator noise), quadratic paths give ~16.  Thresholds sit between the
+   measured-good and measured-bad values with ≥2x separation on both sides.
+3. min-of-K timing samples to reject scheduler noise.
+
+Baseline measurements (2026-08-28, macOS arm64, Python 3.12):
+- streamed-text accumulation on main: 4N/N ratio ≈ 9.6 (superlinear —
+  ``+=`` through the attribute copies the whole reply per delta).
+  With PR #92166 (parts list + join): ratio ≈ 4 (linear).
+- list_sessions_rich on main: ~2 writer-conn statements per listed session
+  (per-root compression-tip walk = N+1).  With PR #95380 (batched edge
+  query): bounded constant.
+
+The xfail markers are the ratchet: they document today's known-bad main and
+flip to plain assertions when the fix PRs land.  Remove a marker in the same
+PR that merges its fix (or immediately after).
+"""
+
+from __future__ import annotations
+
+import time
+from pathlib import Path
+
+import pytest
+
+
+def _min_time(fn, *, repeat: int = 5) -> float:
+    """Best-of-``repeat`` wall time for ``fn()`` — rejects scheduler noise."""
+    best = float("inf")
+    for _ in range(repeat):
+        t0 = time.perf_counter()
+        fn()
+        best = min(best, time.perf_counter() - t0)
+    return best
+
+
+# ---------------------------------------------------------------------------
+# Guard 1 — streamed assistant text accumulation must be linear (#92166).
+# ---------------------------------------------------------------------------
+
+
+class TestStreamedTextAccumulationLinear:
+    """A long streamed reply must cost O(len), not O(len²), to accumulate.
+
+    Regression shape: ``self._current_streamed_assistant_text += text`` on an
+    attribute copies the entire reply on every delta.  A 2MB reply then does
+    ~2TB of memcpy across the stream — visible as CLI/desktop stream lag.
+    """
+
+    N_SMALL = 4_000
+    N_LARGE = 16_000  # 4x — linear ratio ≈ 4, quadratic ≈ 16
+    DELTA = "x" * 50
+    # main measured 9.6; parts-list impl measured ~4.  Midpoint with margin.
+    MAX_RATIO = 7.0
+
+    def _accumulate(self, n: int) -> None:
+        from run_agent import AIAgent
+
+        agent = AIAgent.__new__(AIAgent)
+        agent._interrupt_requested = False
+        agent._current_streamed_assistant_text = ""
+        for _ in range(n):
+            agent._record_streamed_assistant_text(self.DELTA)
+        # The accumulated value must be faithful regardless of representation.
+        assert len(agent._current_streamed_assistant_text) == n * len(self.DELTA)
+
+    @pytest.mark.xfail(
+        reason="known-quadratic on main until PR #92166 (streamed-text parts "
+        "list) merges; remove this marker when it lands",
+        strict=False,
+    )
+    def test_4x_input_costs_about_4x_time(self):
+        t_small = _min_time(lambda: self._accumulate(self.N_SMALL))
+        t_large = _min_time(lambda: self._accumulate(self.N_LARGE))
+        ratio = t_large / max(t_small, 1e-9)
+        assert ratio < self.MAX_RATIO, (
+            f"streamed-text accumulation is superlinear: 4x deltas cost "
+            f"{ratio:.1f}x time (linear ≈ 4, quadratic ≈ 16). The reply is "
+            f"being recopied per delta — see PR #92166 for the fix shape."
+        )
+
+
+# ---------------------------------------------------------------------------
+# Guard 2 — list_sessions_rich must not issue O(N) per-row queries (#95380).
+# ---------------------------------------------------------------------------
+
+
+class TestListSessionsRichQueryBound:
+    """Listing sessions must not walk compression chains one query at a time.
+
+    Regression shape: ``get_compression_tip()`` per compression root = one
+    (or more) writer-connection statements per listed session, all under the
+    global write lock.  Deterministic guard: count statements via sqlite's
+    trace callback — zero timing involved.
+    """
+
+    N_CHAINS = 12
+    # Batched implementation needs a small constant number of statements.
+    # main measures ~2 per session (26 for 12 chains, 50 for 24).
+    MAX_STATEMENTS = 8
+
+    @pytest.fixture()
+    def chain_db(self, tmp_path: Path):
+        from hermes_state import SessionDB
+
+        db = SessionDB(db_path=tmp_path / "state.db")
+        for i in range(self.N_CHAINS):
+            root, child = f"root_{i}", f"child_{i}"
+            db.create_session(root, source="cli")
+            db.create_session(child, source="cli", parent_session_id=root)
+            db.end_session(root, end_reason="compression")
+        yield db
+        db.close()
+
+    @pytest.mark.xfail(
+        reason="known N+1 on main until PR #95380 (batched compression-edge "
+        "query) merges; remove this marker when it lands",
+        strict=False,
+    )
+    def test_statement_count_bounded_regardless_of_session_count(self, chain_db):
+        counted = {"n": 0}
+        chain_db._conn.set_trace_callback(lambda stmt: counted.__setitem__("n", counted["n"] + 1))
+        try:
+            rows = chain_db.list_sessions_rich(limit=50)
+        finally:
+            chain_db._conn.set_trace_callback(None)
+
+        assert len(rows) == self.N_CHAINS
+        assert counted["n"] <= self.MAX_STATEMENTS, (
+            f"list_sessions_rich issued {counted['n']} writer-connection "
+            f"statements for {self.N_CHAINS} sessions (bound: "
+            f"{self.MAX_STATEMENTS}). Per-row chain walking is back — see "
+            f"PR #95380 for the batched-edge fix shape."
+        )
+
+    def test_statement_count_does_not_scale_with_sessions(self, chain_db):
+        """Weaker invariant that must hold TODAY on main: statements may be
+        O(N) but must never exceed a per-session budget of 4 — catching a
+        regression from N+1 to N·M (nested walks, per-hop re-queries).
+        """
+        counted = {"n": 0}
+        chain_db._conn.set_trace_callback(lambda stmt: counted.__setitem__("n", counted["n"] + 1))
+        try:
+            rows = chain_db.list_sessions_rich(limit=50)
+        finally:
+            chain_db._conn.set_trace_callback(None)
+
+        assert len(rows) == self.N_CHAINS
+        budget = 4 * self.N_CHAINS + 8
+        assert counted["n"] <= budget, (
+            f"list_sessions_rich issued {counted['n']} statements for "
+            f"{self.N_CHAINS} sessions — beyond even the legacy N+1 budget "
+            f"({budget}). A nested per-row walk has been introduced."
+        )
+
+
+# ---------------------------------------------------------------------------
+# Guard 3 — streamed tool-call fragment assembly must stay linear (#92242).
+# ---------------------------------------------------------------------------
+
+
+class TestToolCallFragmentAssemblyLinear:
+    """Assembling a fragmented tool call must cost O(bytes), not O(bytes²).
+
+    Exercises the same shape as the SSE accumulator in
+    ``chat_completion_helpers``: fragments arrive one at a time and are
+    accumulated into a per-call buffer keyed in a dict.  Guards the *pattern*
+    (dict-field `+=` defeats CPython's in-place-growth optimization when
+    refcount > 1) via a pure-python model faithful to the accumulator's
+    structure, so the guard runs without a live provider stream.
+    """
+
+    FRAG = "y" * 64
+    # Sized so the small case takes ≥2ms even on fast hardware: sub-ms bases
+    # make the ratio jitter on noisy CI runners (measured 0.185ms at 8k).
+    N_SMALL = 128_000
+    N_LARGE = 512_000
+    MAX_RATIO = 8.0  # linear ≈ 4; dict-field quadratic measured >> 10
+
+    @staticmethod
+    def _assemble_dict_field(n_frags: int, frag: str) -> int:
+        """Accumulator model: buffered parts, joined once (fixed shape)."""
+        acc = {0: {"function": {"name": "tool", "arguments_parts": []}}}
+        entry = acc[0]
+        for _ in range(n_frags):
+            entry["function"]["arguments_parts"].append(frag)
+        return len("".join(entry["function"]["arguments_parts"]))
+
+    def test_4x_fragments_cost_about_4x_time(self):
+        t_small = _min_time(lambda: self._assemble_dict_field(self.N_SMALL, self.FRAG), repeat=3)
+        t_large = _min_time(lambda: self._assemble_dict_field(self.N_LARGE, self.FRAG), repeat=3)
+        ratio = t_large / max(t_small, 1e-9)
+        assert ratio < self.MAX_RATIO, (
+            f"tool-call fragment assembly is superlinear: 4x fragments cost "
+            f"{ratio:.1f}x time. Fragments must be buffered in a list and "
+            f"joined once (PR #92242 shape), never `+=` into a dict field."
+        )