@@ -1,4 +1,4 @@
-.PHONY: demo test lint clean bench-leakage bench-baseline
+.PHONY: demo test lint clean bench-leakage bench-baseline bench-hidden-active
 
 PYTHON := $(shell [ -f .venv/bin/python ] && echo .venv/bin/python || echo python3)
 PYTEST  := $(shell [ -f .venv/bin/pytest ] && echo .venv/bin/pytest || echo pytest)
@@ -32,5 +32,12 @@ bench-baseline:
 		--positives examples/known_reference/demo_known_amps.csv \
 		--out outputs/bench_baseline_report.json
 
+bench-hidden-active:
+	PYTHONPATH=src $(PYTHON) -m openamp_foundry.cli bench baseline \
+		--candidates examples/benchmark/mixed_candidates.csv \
+		--positives examples/benchmark/active_labels.csv \
+		--k 5 10 20 \
+		--out outputs/bench_hidden_active_report.json
+
 clean:
 	rm -rf outputs/*.jsonl outputs/*.md outputs/*.json outputs/evidence .pytest_cache .ruff_cache
@@ -0,0 +1,6 @@
+id,sequence,source
+BM-POS-001,KWKLFKKIGAVLKVL,benchmark_positive
+BM-POS-002,GIGKFLHSAKKFGKAFVGEIMNS,benchmark_positive
+BM-POS-003,GLFDIVKKVVGALGSL,benchmark_positive
+BM-POS-004,RRWWLRVIAGLLKKVLS,benchmark_positive
+BM-POS-005,KLLLKWLKKVLKA,benchmark_positive
@@ -0,0 +1,21 @@
+id,sequence,source
+BM-POS-001,KWKLFKKIGAVLKVL,benchmark_positive
+BM-POS-002,GIGKFLHSAKKFGKAFVGEIMNS,benchmark_positive
+BM-POS-003,GLFDIVKKVVGALGSL,benchmark_positive
+BM-POS-004,RRWWLRVIAGLLKKVLS,benchmark_positive
+BM-POS-005,KLLLKWLKKVLKA,benchmark_positive
+BM-NEG-001,AAAAAAAAAAAA,benchmark_negative
+BM-NEG-002,GGGGGGGGGGGG,benchmark_negative
+BM-NEG-003,DEDEDEDEDEDE,benchmark_negative
+BM-NEG-004,SSSSSSSSSSS,benchmark_negative
+BM-NEG-005,EEEEEEEEEEEE,benchmark_negative
+BM-NEG-006,PPPPPPPPPPPP,benchmark_negative
+BM-NEG-007,NNNNNNNNNNN,benchmark_negative
+BM-NEG-008,QQQQQQQQQQQQ,benchmark_negative
+BM-NEG-009,TTTTTTTTTTTT,benchmark_negative
+BM-NEG-010,AAGGAAGGAAGG,benchmark_negative
+BM-NEG-011,SSTTSSTTSSTT,benchmark_negative
+BM-NEG-012,EDEDEDEDEDED,benchmark_negative
+BM-NEG-013,GGGAAAGGGAAA,benchmark_negative
+BM-NEG-014,QQNNQQNNQQNN,benchmark_negative
+BM-NEG-015,SSSSTTTTSSSS,benchmark_negative
@@ -0,0 +1,144 @@
+"""Tests for hidden-active recovery benchmark.
+
+These tests verify that the pipeline recovers known-active AMPs better than
+a random ranker when mixed with non-active sequences. This is a key Phase 2
+requirement per AGENTS.md.
+
+No biological activity is implied or proven by these results.
+The benchmark only tests whether physicochemical features of known AMPs
+correlate with higher ensemble scores than simple non-AMP sequences.
+"""
+from __future__ import annotations
+
+import json
+
+import pytest
+
+from openamp_foundry.benchmark.evaluate import (
+    benchmark_summary,
+    enrichment_factor,
+    recall_at_k,
+)
+from openamp_foundry.cli import main
+from openamp_foundry.data.loaders import load_candidates_csv
+from openamp_foundry.pipeline import score_candidates
+from openamp_foundry.selection.pareto import rank_candidates
+
+
+MIXED_CANDIDATES = "examples/benchmark/mixed_candidates.csv"
+ACTIVE_LABELS = "examples/benchmark/active_labels.csv"
+
+POSITIVE_IDS = {
+    "BM-POS-001",
+    "BM-POS-002",
+    "BM-POS-003",
+    "BM-POS-004",
+    "BM-POS-005",
+}
+
+
+class TestHiddenActiveRecovery:
+    def test_all_positives_rank_in_top_half(self):
+        scored, _ = score_candidates(MIXED_CANDIDATES)
+        ranked = rank_candidates(scored)
+        n = len(ranked)
+        top_half_ids = {item.candidate.candidate_id for item in ranked[: n // 2]}
+        for pid in POSITIVE_IDS:
+            assert pid in top_half_ids, f"{pid} not in top half"
+
+    def test_recall_at_5_equals_1(self):
+        """All 5 positives should appear in top-5 of 20 candidates."""
+        scored, _ = score_candidates(MIXED_CANDIDATES)
+        rc = recall_at_k(scored, POSITIVE_IDS, k=5)
+        assert rc == 1.0, f"Expected recall@5=1.0, got {rc}"
+
+    def test_enrichment_factor_at_5_exceeds_2(self):
+        """Pipeline should achieve at least 2× enrichment vs random at k=5."""
+        scored, _ = score_candidates(MIXED_CANDIDATES)
+        ef = enrichment_factor(scored, POSITIVE_IDS, k=5)
+        assert ef >= 2.0, f"Enrichment factor {ef} below minimum of 2.0"
+
+    def test_pipeline_verdict_outperforms_random(self):
+        scored, _ = score_candidates(MIXED_CANDIDATES)
+        summary = benchmark_summary(scored, POSITIVE_IDS, ks=[5])
+        assert summary["verdict"] == "pipeline outperforms random"
+
+    def test_negatives_score_lower_than_positives_on_average(self):
+        scored, _ = score_candidates(MIXED_CANDIDATES)
+        pos_scores = [
+            s.scores["ensemble"]
+            for s in scored
+            if s.candidate.candidate_id in POSITIVE_IDS
+        ]
+        neg_scores = [
+            s.scores["ensemble"]
+            for s in scored
+            if s.candidate.candidate_id not in POSITIVE_IDS
+        ]
+        assert pos_scores
+        assert neg_scores
+        assert sum(pos_scores) / len(pos_scores) > sum(neg_scores) / len(neg_scores)
+
+    def test_bench_baseline_cli_shows_enrichment(self, tmp_path, capsys):
+        out = str(tmp_path / "bench_report.json")
+        ret = main([
+            "bench", "baseline",
+            "--candidates", MIXED_CANDIDATES,
+            "--positives", ACTIVE_LABELS,
+            "--k", "5",
+            "--out", out,
+        ])
+        assert ret == 0
+        data = json.loads((tmp_path / "bench_report.json").read_text())
+        k5_result = next(r for r in data["results"] if r["k"] == 5)
+        assert k5_result["enrichment_factor"] >= 2.0
+        assert data["verdict"] == "pipeline outperforms random"
+
+    def test_benchmark_summary_disclaimer_present(self):
+        scored, _ = score_candidates(MIXED_CANDIDATES)
+        summary = benchmark_summary(scored, POSITIVE_IDS, ks=[5])
+        assert "disclaimer" in summary
+        assert len(summary["disclaimer"]) > 20
+
+    def test_known_active_amps_outrank_all_repeat_sequences(self):
+        """Biologically implausible repeat sequences should rank below AMP-like ones."""
+        scored, _ = score_candidates(MIXED_CANDIDATES)
+        ranked = rank_candidates(scored)
+        ranked_ids = [s.candidate.candidate_id for s in ranked]
+
+        # All positives should appear before all-same-AA negatives
+        for pos_id in POSITIVE_IDS:
+            pos_rank = ranked_ids.index(pos_id)
+            for neg_id in ["BM-NEG-001", "BM-NEG-002", "BM-NEG-004"]:
+                neg_rank = ranked_ids.index(neg_id)
+                assert pos_rank < neg_rank, (
+                    f"{pos_id} (rank {pos_rank}) should outrank {neg_id} (rank {neg_rank})"
+                )
+
+
+class TestBenchmarkDataIntegrity:
+    def test_benchmark_csvs_exist(self):
+        from pathlib import Path
+        assert Path(MIXED_CANDIDATES).exists()
+        assert Path(ACTIVE_LABELS).exists()
+
+    def test_all_positive_ids_in_mixed_candidates(self):
+        mixed = load_candidates_csv(MIXED_CANDIDATES)
+        mixed_ids = {c.candidate_id for c in mixed}
+        for pid in POSITIVE_IDS:
+            assert pid in mixed_ids, f"Positive {pid} missing from mixed candidates"
+
+    def test_mixed_has_both_positives_and_negatives(self):
+        mixed = load_candidates_csv(MIXED_CANDIDATES)
+        ids = {c.candidate_id for c in mixed}
+        positive_overlap = ids & POSITIVE_IDS
+        negative_only = ids - POSITIVE_IDS
+        assert len(positive_overlap) >= 3
+        assert len(negative_only) >= 5
+
+    def test_active_labels_are_subset_of_mixed(self):
+        mixed = load_candidates_csv(MIXED_CANDIDATES)
+        active = load_candidates_csv(ACTIVE_LABELS)
+        mixed_ids = {c.candidate_id for c in mixed}
+        for a in active:
+            assert a.candidate_id in mixed_ids