Phase F F10: Negative-result archive completeness checker

Makefile

@@ -621,6 +621,12 @@ validate-rejection-events:
 		--out-json outputs/rejection_events_validation.json \
 		--out-md outputs/rejection_events_validation.md
 
+check-negative-archive-completeness:
+	PYTHONPATH=src $(PYTHON) scripts/check_negative_archive_completeness.py \
+		--input examples/negative_result_archive_example.json \
+		--out-json outputs/negative_archive_completeness_report.json \
+		--out-md outputs/negative_archive_completeness_report.md
+
 negative-result-dashboard:
 	PYTHONPATH=src $(PYTHON) scripts/negative_result_dashboard.py \
 		--input examples/negative_result_dashboard_example.json \

docs/evidence/METRICS_CURRENT.md

@@ -5,7 +5,9 @@ Machine-readable snapshot: `outputs/metrics_snapshot.json` regenerated with `mak
 > **Purpose:** One authoritative table of current pipeline metrics. If any doc disagrees
 > with this file, this file wins. Updated whenever benchmark/benchmark config changes.
 >
-> **Last updated:** 2026-07-09 (Phase F F9 — negative-result dashboard — v0.5.79)
+> **Last updated:** 2026-07-09 (Phase F F10 — negative-result archive completeness checker — v0.5.80)
+> **New in v0.5.80:** Negative-result archive completeness checker (F10) — CLI (`scripts/check_negative_archive_completeness.py`) that reads a JSON archive of negative-result entries and checks each entry against completeness criteria: all required fields present, no duplicate candidate_ids, each entry has at least one content field (assay_result, score_safety, reviewer_notes, or reason_detail), date format valid YYYY-MM-DD, and optional intake_report_id references are well-formed. Outputs a structured completeness report as JSON and Markdown with summary, per-check results, and per-entry pass/fail. Schema (`schemas/negative_result_archive_completeness.schema.json`). Example file (`examples/negative_result_archive_example.json`) with 4 toy entries. 35 tests. 2919 total.
+>
 > **New in v0.5.79:** Negative-result dashboard (F9) — CLI (`scripts/negative_result_dashboard.py`) that reads a collection of negative-result entries from a JSON file and produces a structured dashboard with summary statistics (by category, by pipeline version), score distributions (activity, safety, novelty, ensemble), per-category cross-analysis, and pipeline insights (most common failure category, recalibration opportunities). Outputs JSON + Markdown. Example file (`examples/negative_result_dashboard_example.json`) with 15 toy entries across all 6 failure categories. Schema (`schemas/negative_result_dashboard.schema.json`). `make negative-result-dashboard` target. 33 tests. 2883 total.
 >
 > **New in v0.5.79:** Bulk rejection-event validator (F8) — CLI (`scripts/validate_rejection_events.py`) that reads a JSON list of rejection events, validates each `rejection_code` against the rejection taxonomy (`examples/rejection_taxonomy_example.json`), checks required fields (candidate_id, rejection_code, date, pipeline_version), and outputs a PASS/FAIL validation report with per-event errors, rejection-code distribution, and Markdown summary. Example file (`examples/rejection_events_example.json`) with 6 toy events. `make validate-rejection-events` target. 26 tests. 2849 total.

docs/research/ROADMAP.md

@@ -1,5 +1,56 @@
 # Roadmap
 
+## v0.5.80 — Loop 80: Phase F F10 — Negative-Result Archive Completeness Checker ✓ (2026-07-09)
+
+CLI that reads a JSON archive of negative-result entries and checks each entry
+against completeness criteria: required fields, duplicate candidate_ids, content
+field presence, date format validity, and intake_report_id format. Prevents
+cherry-picking by ensuring incomplete or poorly documented entries are detected
+before analysis or reporting.
+
+Changes:
+- `scripts/check_negative_archive_completeness.py` (F10) — Standalone CLI that
+  loads negative-result entries (list or dict with `entries` key), checks each
+  entry for: required fields present, no duplicate candidate_ids, at least one
+  content field (assay_result, score_safety, reviewer_notes, or reason_detail),
+  valid YYYY-MM-DD date format, and well-formed intake_report_id (INT-YYYY-NNN).
+  Produces structured JSON + Markdown report with per-check and per-entry pass/fail.
+  Exit 0 on all pass, 1 on any failure, 2 on input errors.
+- `schemas/negative_result_archive_completeness.schema.json` (F10) — JSON Schema
+  Draft 2020-12 for the completeness report output. Validates report_metadata,
+  summary (total_entries, pass/fail count, pass_rate), 5 checks (required_fields,
+  duplicate_candidate_ids, has_content_fields, date_format,
+  intake_report_id_references) each with pass boolean and details array,
+  per_entry_results array, and _caveat.
+- `examples/negative_result_archive_example.json` (F10) — Toy example with 4
+  entries (lab_inactive, lab_toxic, control_failure, synthesis_failure) across
+  4 pipeline versions, including one entry with intake_report_id reference.
+  Clearly marked EXAMPLE — NOT REAL DATA.
+- `tests/evidence/test_negative_archive_completeness.py` — 35 tests covering:
+  valid entries pass all checks, missing required field, duplicate candidate_id,
+  missing content fields, invalid date format, invalid calendar date, invalid
+  intake_report_id format, valid intake_report_id, mixed good/bad entries, empty
+  string required field, reason_detail as content, report structure (5 keys),
+  per-entry results matching count, empty entry handling, missing file, markdown
+  sections (title, summary, check results, caveat, errors), example file loading
+  and round-trip, all load_entries error modes, CLI exit codes (0, 1, 2), and
+  JSON/Markdown output writing.
+- `Makefile` — Added `check-negative-archive-completeness` target.
+- `docs/evidence/METRICS_CURRENT.md` — v0.5.80 F10 changelog. Test count: 2919.
+- `tests/test_test_count_regression.py` — baseline updated to 2919.
+
+Honest boundaries:
+- Checks structural and formatting criteria only — a PASS does not confirm
+  biological accuracy, pipeline correctness, or data authenticity.
+- Missing content fields may reflect genuine data absence (e.g., unreviewed
+  entries) rather than record-keeping errors.
+- The intake_report_id format check validates pattern, not referential
+  integrity — a well-formed ID may reference a non-existent intake report.
+- Duplicate candidate_id detection flags structural duplicates; it cannot
+  distinguish accidental duplicates from intentional re-entry of the same
+  candidate under different conditions.
+- All conclusions about entry quality require qualified human review.
+
 ## v0.5.79 — Loop 79: Phase F F9 — Negative-Result Dashboard ✓ (2026-07-09)
 
 CLI that reads a collection of negative-result entries from a JSON file and

examples/negative_result_archive_example.json

@@ -0,0 +1,56 @@
+{
+  "schema": "EXAMPLE — NOT REAL DATA. For demonstration only.",
+  "description": "Toy negative-result archive entries for completeness checker demonstration. All candidates, sequences, scores, and reasons are synthetic and must not be treated as real experimental results.",
+  "pipeline_version": "v0.5.80",
+  "entries": [
+    {
+      "entry_id": 1,
+      "date": "2026-06-01",
+      "candidate_id": "ARCHIVE-001",
+      "sequence": "RRIRIIRRIRIIRRI",
+      "reason_category": "lab_inactive",
+      "reason_detail": "MIC > 128 ug/mL against E. coli.",
+      "pipeline_version": "v0.5.70",
+      "source_batch": "wave0.5",
+      "assay_result": ">128",
+      "score_activity": 0.82,
+      "score_safety": 0.35,
+      "reviewer_notes": "Confirmed inactive across 3 replicates."
+    },
+    {
+      "entry_id": 2,
+      "date": "2026-06-03",
+      "candidate_id": "ARCHIVE-002",
+      "sequence": "KLAKLAKKLAKLAK",
+      "reason_category": "lab_toxic",
+      "reason_detail": "HC50 = 8 ug/mL. High hemolysis risk.",
+      "pipeline_version": "v0.5.71",
+      "source_batch": "wave0.5",
+      "score_safety": 0.30,
+      "score_activity": 0.90
+    },
+    {
+      "entry_id": 3,
+      "date": "2026-06-05",
+      "candidate_id": "ARCHIVE-003",
+      "sequence": "GIGKFLHSAKKWGKAFVGEIMNS",
+      "reason_category": "control_failure",
+      "reason_detail": "Positive control failed. MIC for polymyxin B exceeded expected range.",
+      "pipeline_version": "v0.5.72",
+      "source_batch": "wave0.5",
+      "intake_report_id": "INT-2026-001",
+      "score_activity": 0.75,
+      "score_safety": 0.88
+    },
+    {
+      "entry_id": 4,
+      "date": "2026-06-10",
+      "candidate_id": "ARCHIVE-004",
+      "sequence": "RWQWRWQWRWQWRW",
+      "reason_category": "synthesis_failure",
+      "reason_detail": "Crude purity 62%, below 80% threshold. Synthesis failed after 3 attempts.",
+      "pipeline_version": "v0.5.73",
+      "source_batch": "wave0.5"
+    }
+  ]
+}

schemas/negative_result_archive_completeness.schema.json

@@ -0,0 +1,90 @@
+{
+  "$schema": "https://json-schema.org/draft/2020-12/schema",
+  "title": "Negative-Result Archive Completeness Report",
+  "description": "Schema for the structured completeness report produced by scripts/check_negative_archive_completeness.py.",
+  "type": "object",
+  "required": ["report_metadata", "summary", "checks", "per_entry_results", "_caveat"],
+  "properties": {
+    "report_metadata": {
+      "type": "object",
+      "required": ["generated_at", "pipeline_version", "source_file", "total_entries"],
+      "properties": {
+        "generated_at": {"type": "string", "format": "date-time"},
+        "pipeline_version": {"type": "string"},
+        "source_file": {"type": "string"},
+        "total_entries": {"type": "integer", "minimum": 0}
+      }
+    },
+    "summary": {
+      "type": "object",
+      "required": ["total_entries", "pass_count", "fail_count", "pass_rate"],
+      "properties": {
+        "total_entries": {"type": "integer", "minimum": 0},
+        "pass_count": {"type": "integer", "minimum": 0},
+        "fail_count": {"type": "integer", "minimum": 0},
+        "pass_rate": {"type": "string"}
+      }
+    },
+    "checks": {
+      "type": "object",
+      "required": ["required_fields", "duplicate_candidate_ids", "has_content_fields", "date_format", "intake_report_id_references"],
+      "properties": {
+        "required_fields": {
+          "type": "object",
+          "required": ["pass", "details"],
+          "properties": {
+            "pass": {"type": "boolean"},
+            "details": {"type": "array", "items": {"type": "string"}}
+          }
+        },
+        "duplicate_candidate_ids": {
+          "type": "object",
+          "required": ["pass", "details"],
+          "properties": {
+            "pass": {"type": "boolean"},
+            "details": {"type": "array", "items": {"type": "string"}}
+          }
+        },
+        "has_content_fields": {
+          "type": "object",
+          "required": ["pass", "details"],
+          "properties": {
+            "pass": {"type": "boolean"},
+            "details": {"type": "array", "items": {"type": "string"}}
+          }
+        },
+        "date_format": {
+          "type": "object",
+          "required": ["pass", "details"],
+          "properties": {
+            "pass": {"type": "boolean"},
+            "details": {"type": "array", "items": {"type": "string"}}
+          }
+        },
+        "intake_report_id_references": {
+          "type": "object",
+          "required": ["pass", "details"],
+          "properties": {
+            "pass": {"type": "boolean"},
+            "details": {"type": "array", "items": {"type": "string"}}
+          }
+        }
+      }
+    },
+    "per_entry_results": {
+      "type": "array",
+      "items": {
+        "type": "object",
+        "required": ["entry_id", "candidate_id", "checks", "errors", "pass"],
+        "properties": {
+          "entry_id": {"type": ["integer", "string"]},
+          "candidate_id": {"type": "string"},
+          "checks": {"type": "object"},
+          "errors": {"type": "array", "items": {"type": "string"}},
+          "pass": {"type": "boolean"}
+        }
+      }
+    },
+    "_caveat": {"type": "string"}
+  }
+}