feat(tracker): add alpha calibration and dynamic pricing

Add TOPLOC honest-noise calibration storage/dispatch and validator divergence reporting for AH-021.

Add opt-in HuggingFace marketplace pricing refresh, price-change history, CLI flags, and AH-023 tracking docs.

Verification: .venv/bin/python -m pytest tests/ -q -k 'not integration' => 346 passed, 2 skipped, 1 deselected; compileall packages tests passed; focused AH-021/AH-023 tests 32 passed.

tests/test_toploc_audit.py

@@ -2,10 +2,15 @@
 
 from __future__ import annotations
 
+from collections import namedtuple
 from types import SimpleNamespace
 
 from meshnet_validator import ToplocAuditConfig, ValidatorProcess
-from meshnet_validator.audit import build_activation_proofs, verify_activation_proofs
+from meshnet_validator.audit import (
+    build_activation_proofs,
+    verify_activation_proofs,
+    verify_activation_proofs_detailed,
+)
 
 
 class FakeToploc:
@@ -199,3 +204,70 @@ def test_validator_rejects_swapped_precision_toploc_claim():
     assert len(receipts) == 1
     assert contracts.registry.slashes[0]["wallet_address"] == "wallet-bad"
     assert "TOPLOC activation proof mismatch" in contracts.registry.slashes[0]["reason"]
+
+
+# AH-021: verify_activation_proofs_detailed surfaces the raw divergence
+# metric a calibration corpus needs, instead of only a pass/fail bool.
+
+ChunkResult = namedtuple("ChunkResult", ["exp_intersections", "mant_err_mean", "mant_err_median"])
+
+
+class FakeToplocWithChunkResults:
+    """Mimics the real `toploc` library: verify returns per-chunk results,
+    not a bool, so `bool(result)` alone (the AH-021 gap #1 bug) is always
+    true for any non-empty response regardless of divergence."""
+
+    def build_proofs_base64(self, activations, *, decode_batching_size, topk, skip_prefill):
+        return {"activations": activations}
+
+    def verify_proofs_base64(self, activations, proofs, *, decode_batching_size, topk, skip_prefill):
+        return [
+            ChunkResult(exp_intersections=8, mant_err_mean=0.01, mant_err_median=0.008),
+            ChunkResult(exp_intersections=6, mant_err_mean=0.03, mant_err_median=0.02),
+        ]
+
+
+def test_verify_activation_proofs_detailed_aggregates_per_chunk_divergence():
+    fake_toploc = FakeToplocWithChunkResults()
+    activations = [[1.0, 2.0], [3.0, 4.0]]
+    config = ToplocAuditConfig(topk=2, decode_batching_size=16)
+    claim = build_activation_proofs(activations, config=config, backend=fake_toploc)
+
+    result = verify_activation_proofs_detailed(activations, claim, config=config, backend=fake_toploc)
+
+    assert result.passed is True  # non-empty list is truthy, same as legacy behavior
+    assert result.chunk_count == 2
+    assert result.exp_intersections == 6  # worst-case (min) across chunks
+    assert result.mant_err_mean == 0.02  # mean of per-chunk means
+    assert result.mant_err_median == 0.014  # mean of per-chunk medians
+
+    # verify_activation_proofs still returns just the bool for existing callers.
+    assert verify_activation_proofs(activations, claim, config=config, backend=fake_toploc) is True
+
+
+def test_verify_activation_proofs_detailed_no_metric_from_plain_bool_backend():
+    fake_toploc = FakeToploc()
+    activations = [[1.0, 2.0, 3.0], [4.0, 5.0, 6.0]]
+    config = ToplocAuditConfig(topk=2, decode_batching_size=16)
+    claim = build_activation_proofs(activations, config=config, backend=fake_toploc)
+
+    result = verify_activation_proofs_detailed(activations, claim, config=config, backend=fake_toploc)
+
+    assert result.passed is True
+    assert result.chunk_count == 0
+    assert result.exp_intersections is None
+    assert result.mant_err_mean is None
+    assert result.mant_err_median is None
+
+
+def test_verify_activation_proofs_detailed_rejects_config_mismatch_without_calling_backend():
+    fake_toploc = FakeToplocWithChunkResults()
+    activations = [[1.0, 2.0]]
+    canonical = ToplocAuditConfig(dtype="bfloat16", quantization="bfloat16", topk=2, decode_batching_size=16)
+    swapped = ToplocAuditConfig(dtype="bfloat16", quantization="int8", topk=2, decode_batching_size=16)
+    claim = build_activation_proofs(activations, config=swapped, backend=fake_toploc)
+
+    result = verify_activation_proofs_detailed(activations, claim, config=canonical, backend=fake_toploc)
+
+    assert result.passed is False
+    assert result.chunk_count == 0