diff --git a/.gitignore b/.gitignore
index 710de0b..813e34e 100644
--- a/.gitignore
+++ b/.gitignore
@@ -34,3 +34,5 @@ credentials
 .cache/
 # claim checker output (local)
 claims_report.md
+spec_coverage_report.md
+voice_report.md
diff --git a/scripts/docs/check_claims.py b/scripts/docs/check_claims.py
index 04635ed..9c07a43 100644
--- a/scripts/docs/check_claims.py
+++ b/scripts/docs/check_claims.py
@@ -17,24 +17,18 @@ Exit code 1 when any claim is contradicted or has no source, so the script can g
 from __future__ import annotations
 
 import argparse
-import hashlib
-import json
-import os
 import re
 import sys
-import time
-import urllib.error
-import urllib.request
 from dataclasses import dataclass, field
 from pathlib import Path
 
+sys.path.insert(0, str(Path(__file__).resolve().parents[1] / "jev"))
+from client import MODEL, api_key, system_one
+
 ROOT = Path(__file__).resolve().parents[2]
-API_URL = "https://api.typesafe.ai/v1/systemone"
-MODEL = "jev-latest"
 AUTO_ACCEPT = 0.8  # cookbook default; evaluate on our own claims before trusting it
 TOP_K = 3
 DEFAULT_SOURCES = ["docs/validation", "docs/known_unknowns.md", "SIMURGARRAY_FUNCTIONAL_SPEC.md"]
-CACHE = ROOT / ".cache" / "claims"
 
 RELATION = {
     "type": "choice",
@@ -255,33 +249,6 @@ def build_request(claim: Claim, cands: list[Passage]) -> dict[str, object]:
     return {"model": MODEL, "state": state, "questions": questions}
 
 
-def call_api(payload: dict[str, object], key: str, retries: int = 5) -> dict[str, object]:
-    body = json.dumps(payload).encode()
-    digest = hashlib.sha256(body).hexdigest()
-    cached = CACHE / f"{digest}.json"
-    if cached.exists():
-        return json.loads(cached.read_text())  # type: ignore[no-any-return]
-    headers = {
-        "Authorization": f"Bearer {key}",
-        "Content-Type": "application/json",
-        "User-Agent": "simurgarray-claims/1",
-    }
-    req = urllib.request.Request(API_URL, data=body, method="POST", headers=headers)
-    for attempt in range(retries):
-        try:
-            with urllib.request.urlopen(req, timeout=60) as r:
-                res = json.loads(r.read())
-            CACHE.mkdir(parents=True, exist_ok=True)
-            cached.write_text(json.dumps(res))
-            return res  # type: ignore[no-any-return]
-        except urllib.error.HTTPError as e:
-            if e.code in (429, 529) and attempt < retries - 1:
-                time.sleep(2**attempt)
-                continue
-            raise RuntimeError(f"TypeSafe API error {e.code}: {e.read()[:200]!r}") from e
-    raise RuntimeError("TypeSafe API: retries exhausted")
-
-
 def verdict(answers: dict[str, dict[str, object]], threshold: float = AUTO_ACCEPT) -> tuple[str, str | None, float]:
     """Combine per-section answers: any confident 'supports' wins; else a confident 'contradicts'; else a confident
     'says_nothing' from every section; anything else goes to a person."""
@@ -306,15 +273,6 @@ def verdict(answers: dict[str, dict[str, object]], threshold: float = AUTO_ACCEP
 # ------------------------------------------------------------------ report
 
 
-def _key_from_file(path: Path) -> str:
-    """``TYPESAFE_API_KEY=...`` from a private local file (never from the repository)."""
-    if path.exists():
-        for ln in path.read_text().splitlines():
-            if ln.startswith("TYPESAFE_API_KEY="):
-                return ln.split("=", 1)[1].strip()
-    return ""
-
-
 def main(argv: list[str] | None = None) -> int:
     ap = argparse.ArgumentParser(description=__doc__.split("\n\n")[0])
     ap.add_argument("files", nargs="+", type=Path, help="texts to check (markdown or plain text)")
@@ -323,7 +281,7 @@ def main(argv: list[str] | None = None) -> int:
     ap.add_argument("--threshold", type=float, default=AUTO_ACCEPT)
     ap.add_argument("--dry-run", action="store_true", help="extract claims and evidence, no API calls")
     a = ap.parse_args(argv)
-    key = os.environ.get("TYPESAFE_API_KEY", "") or _key_from_file(Path.home() / ".config" / "typesafe" / "credentials")
+    key = api_key()
     if not a.dry_run and not key:
         print("TYPESAFE_API_KEY is not set (use --dry-run to check extraction without the API).", file=sys.stderr)
         return 2
@@ -338,8 +296,8 @@ def main(argv: list[str] | None = None) -> int:
             if a.dry_run:
                 rows.append(("planned", c, cands[0], 0.0, f"{len(cands)} candidate(s)"))
                 continue
-            res = call_api(build_request(c, cands), key)
-            answers = res["answers"]  # type: ignore[index]
+            req = build_request(c, cands)
+            answers = system_one(req["state"], req["questions"], key)  # type: ignore[arg-type]
             v, qid, conf = verdict(answers, a.threshold)  # type: ignore[arg-type]
             src = cands[int(qid[1:])] if qid else cands[0]
             probs = ", ".join(f"{q}: {answers[q]['choice']} {answers[q]['confidence']:.2f}" for q in answers)  # type: ignore[index]
diff --git a/scripts/jev/__init__.py b/scripts/jev/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/scripts/jev/client.py b/scripts/jev/client.py
new file mode 100644
index 0000000..cc3a6ab
--- /dev/null
+++ b/scripts/jev/client.py
@@ -0,0 +1,86 @@
+"""Minimal client for TypeSafe System One (Jev), shared by the project's maintenance tools in ``scripts/``.
+
+Only the standard library: one POST per request to https://api.typesafe.ai/v1/systemone, retries with exponential
+backoff on 429 and 529, and a content addressed cache in ``.cache/jev`` so unchanged questions are never paid twice.
+The API key comes from ``TYPESAFE_API_KEY`` or ``~/.config/typesafe/credentials`` (``TYPESAFE_API_KEY=...``, mode
+600) and never enters the repository. These tools send documentation, test code, issue text and public abstracts;
+they are never used inside the ``simurg`` analysis commands, which stay offline.
+"""
+
+from __future__ import annotations
+
+import hashlib
+import json
+import os
+import time
+import urllib.error
+import urllib.request
+from pathlib import Path
+from typing import Any
+
+ROOT = Path(__file__).resolve().parents[2]
+API_URL = "https://api.typesafe.ai/v1/systemone"
+MODEL = "jev-latest"
+CACHE = ROOT / ".cache" / "jev"
+KEY_FILE = Path.home() / ".config" / "typesafe" / "credentials"
+
+Question = dict[str, Any]
+Answers = dict[str, dict[str, Any]]
+
+
+def api_key() -> str:
+    """The key from the environment, else from the private credentials file; empty when absent."""
+    key = os.environ.get("TYPESAFE_API_KEY", "")
+    if not key and KEY_FILE.exists():
+        for ln in KEY_FILE.read_text().splitlines():
+            if ln.startswith("TYPESAFE_API_KEY="):
+                key = ln.split("=", 1)[1].strip()
+    return key
+
+
+def noul(instructions: str, true: str | None = None, false: str | None = None) -> Question:
+    q: Question = {"type": "noul", "instructions": instructions}
+    if true and false:
+        q["criteria"] = {"true": true, "false": false}
+    return q
+
+
+def choice(instructions: str, criteria: dict[str, str | None]) -> Question:
+    return {"type": "choice", "instructions": instructions, "criteria": criteria}
+
+
+def score(instructions: str, levels: list[str]) -> Question:
+    """``levels`` from the low end of the scale to the high end (2 to 10 concrete situations)."""
+    return {"type": "score", "instructions": instructions, "criteria": levels}
+
+
+def system_one(state: Any, questions: dict[str, Question], key: str | None = None, retries: int = 5) -> Answers:
+    """Ask ``questions`` about ``state`` in one request; returns the ``answers`` map (cached by request content)."""
+    payload = {"model": MODEL, "state": state, "questions": questions}
+    body = json.dumps(payload, sort_keys=True).encode()
+    cached = CACHE / f"{hashlib.sha256(body).hexdigest()}.json"
+    if cached.exists():
+        return json.loads(cached.read_text())["answers"]  # type: ignore[no-any-return]
+    key = key or api_key()
+    if not key:
+        raise RuntimeError("TYPESAFE_API_KEY is not set (environment or ~/.config/typesafe/credentials)")
+    headers = {"Authorization": f"Bearer {key}", "Content-Type": "application/json", "User-Agent": "simurgarray-jev/1"}
+    req = urllib.request.Request(API_URL, data=body, method="POST", headers=headers)
+    for attempt in range(retries):
+        try:
+            with urllib.request.urlopen(req, timeout=90) as r:
+                res = json.loads(r.read())
+            CACHE.mkdir(parents=True, exist_ok=True)
+            cached.write_text(json.dumps(res))
+            return res["answers"]  # type: ignore[no-any-return]
+        except urllib.error.HTTPError as e:
+            if e.code in (429, 529) and attempt < retries - 1:
+                time.sleep(2**attempt)
+                continue
+            raise RuntimeError(f"TypeSafe API error {e.code}: {e.read()[:300]!r}") from e
+        except (urllib.error.URLError, TimeoutError) as e:
+            if attempt < retries - 1:
+                time.sleep(2**attempt)
+                continue
+            raise RuntimeError(f"TypeSafe API unreachable: {e}") from e
+    raise RuntimeError("TypeSafe API: retries exhausted")
diff --git a/scripts/jev/nightly_triage.py b/scripts/jev/nightly_triage.py
new file mode 100644
index 0000000..5316930
--- /dev/null
+++ b/scripts/jev/nightly_triage.py
@@ -0,0 +1,132 @@
+"""Triage of a failed nightly run: which known finding explains each failing step, if any?
+
+Code collects the evidence of every step that did not pass (its verdict and counts, the fields of the compare
+summary that differ with their first example rows, or the failing lines of the run log) and the 30 or so entries of
+docs/known_unknowns.md. Jev answers three questions per step in one request:
+
+* which known finding explains the failure, an environment problem (memory, disk, network, missing data), or a new
+  issue (Choice);
+* does it look like a behaviour change introduced by recent code (Noul);
+* how severe is it, from metadata only to a crash (Score).
+
+Only new issues and likely regressions need a person. The evidence comes from public test data (the GSA demo and the
+1000 Genomes Omni2.5 subset).
+
+    python scripts/jev/nightly_triage.py data/nightly/2026-10-01     # writes triage.md in that folder
+"""
+
+from __future__ import annotations
+
+import argparse
+import gzip
+import json
+import re
+import sys
+from pathlib import Path
+from typing import Any
+
+sys.path.insert(0, str(Path(__file__).resolve().parent))
+from client import ROOT, choice, noul, score, system_one
+
+KNOWN = ROOT / "docs" / "known_unknowns.md"
+SEVERITY = [
+    "Only metadata, timestamps or report formatting differ; every computed value is the same",
+    "Small numeric differences in some values, genotype calls unchanged",
+    "Genotype calls, file contents or counts differ for some samples or loci",
+    "A step crashed or produced no output",
+]
+
+
+def known_findings(text: str) -> dict[str, str]:
+    """``K-NNN -> 'topic: finding'`` from the table of docs/known_unknowns.md."""
+    out: dict[str, str] = {}
+    for ln in text.splitlines():
+        m = re.match(r"\|\s*(K-\d+)\s*\|[^|]*\|\s*([^|]*)\|\s*([^|]*)\|", ln)
+        if m:
+            out[m.group(1)] = f"{m.group(2).strip()}: {m.group(3).strip()}"[:420]
+    return out
+
+
+def _log_lines(log: Path, n: int = 30) -> list[str]:
+    if not log.exists():
+        return []
+    keep = [ln for ln in log.read_text(errors="replace").splitlines()
+            if re.search(r"FAILED|ERROR|Error|Traceback|Killed|MemAvailable|No space|exit [1-9]", ln)]  # fmt: skip
+    return keep[-n:]
+
+
+def evidence(base: Path, name: str, step: dict[str, Any]) -> dict[str, Any]:
+    ev: dict[str, Any] = {"step": name, "result": {k: v for k, v in step.items() if k not in ("report", "seconds")}}
+    rep = step.get("report") or (step.get("regression") or {}).get("report")
+    if rep:
+        folder = (base / rep).parent
+        s = folder / "summary.json"
+        if s.exists():
+            summ = json.loads(s.read_text())
+            fields = {f: {"tolerance": d.get("tolerance"), "discrepancies": d.get("discrepancies")}
+                      for f, d in summ.get("fields", {}).items() if d.get("discrepancies")}  # fmt: skip
+            ev["differing_fields"] = fields
+            ev["notes"] = summ.get("notes", [])[:10]
+            tsv = folder / "discrepancies.tsv.gz"
+            if tsv.exists():
+                with gzip.open(tsv, "rt") as fh:
+                    ev["first_rows"] = [ln.rstrip("\n")[:300] for _, ln in zip(range(16), fh, strict=False)]
+    if "differing_fields" not in ev and (step.get("verdict") in ("FAIL", "ERROR") or "error" in step):
+        ev["log"] = _log_lines(base / "run.log")  # the shared log only when the step left no compare evidence
+    return ev
+
+
+def triage_step(ev: dict[str, Any], findings: dict[str, str]) -> dict[str, Any]:
+    criteria: dict[str, str | None] = dict(findings)
+    criteria["environment"] = ("The run itself failed: out of memory, disk full, network, missing data or tools, a "
+                               "killed or timed out process")  # fmt: skip
+    criteria["new_issue"] = "None of the known findings or environment problems explains it: a new difference"
+    qs = {
+        "match": choice("Which known finding explains `failure`, if any?", criteria),
+        "regression": noul(
+            "Does `failure` look like a behaviour change introduced by recent code (outputs changed), rather than a "
+            "known quirk or an environment problem?"
+        ),
+        "severity": score("How severe is `failure`?", SEVERITY),
+    }
+    ans = system_one({"failure": ev}, qs)
+    m = ans["match"]
+    return {
+        "match": m["choice"],
+        "match_confidence": round(float(m["confidence"]), 2),
+        "regression": round(float(ans["regression"]["noul"]), 2),
+        "severity": round(float(ans["severity"]["score"]), 2),
+        "needs_person": m["choice"] == "new_issue"
+        or float(ans["regression"]["noul"]) >= 0.5
+        or float(m["confidence"]) < 0.6,
+    }
+
+
+def triage(base: Path) -> dict[str, Any]:
+    night = json.loads((base / "summary.json").read_text())
+    findings = known_findings(KNOWN.read_text(encoding="utf-8"))
+    out: dict[str, Any] = {}
+    for name, step in night["steps"].items():
+        if step.get("verdict") in ("PASS", "SKIPPED"):
+            continue
+        out[name] = triage_step(evidence(base, name, step), findings)
+    lines = [f"# Nightly triage {night['date']}", ""]
+    for name, t in out.items():
+        who = "a person should look" if t["needs_person"] else "explained"
+        lines.append(f"* **{name}**: {t['match']} (confidence {t['match_confidence']}), regression p "
+                     f"{t['regression']}, severity {t['severity']} of 3: {who}")  # fmt: skip
+    (base / "triage.md").write_text("\n".join(lines) + "\n")
+    return out
+
+
+def main(argv: list[str] | None = None) -> int:
+    ap = argparse.ArgumentParser(description=__doc__.split("\n\n")[0])
+    ap.add_argument("night", type=Path, help="folder of one night, for example data/nightly/2026-10-01")
+    a = ap.parse_args(argv)
+    res = triage(a.night)
+    print(json.dumps(res, indent=1) if res else "every step passed; nothing to triage")
+    return 0
+
+
+if __name__ == "__main__":
+    sys.exit(main())
diff --git a/scripts/jev/spec_coverage.py b/scripts/jev/spec_coverage.py
new file mode 100644
index 0000000..e88c6bd
--- /dev/null
+++ b/scripts/jev/spec_coverage.py
@@ -0,0 +1,238 @@
+"""Which functional spec items have a test? Gaps between SIMURGARRAY_FUNCTIONAL_SPEC.md and tests/.
+
+1. Code parses the spec items (``- **CLI-021** ...`` up to the next item or heading) and every test function.
+2. An item cited by ID in a test file counts as covered by citation.
+3. For the other items, code ranks test functions by word overlap (BM25) and keeps the best three; Jev answers one
+   yes/no question per candidate: does this test check what the item requires?
+4. The report lists, per prefix, the items covered by citation, covered by judgment, maybe covered and uncovered.
+
+Open questions (OQ) and scope statements (SCOPE) are not behaviours and are skipped.
+
+    python scripts/jev/spec_coverage.py                  # writes spec_coverage_report.md
+    python scripts/jev/spec_coverage.py --dry-run        # parsing and candidates only, no API calls
+"""
+
+from __future__ import annotations
+
+import argparse
+import ast
+import math
+import re
+import sys
+from collections import Counter
+from dataclasses import dataclass
+from pathlib import Path
+
+sys.path.insert(0, str(Path(__file__).resolve().parent))
+from client import ROOT, noul, system_one
+
+SPEC = ROOT / "SIMURGARRAY_FUNCTIONAL_SPEC.md"
+TESTS = ROOT / "tests"
+SKIP_PREFIXES = {"OQ", "SCOPE"}
+COVERED, MAYBE = 0.8, 0.5
+_ITEM = re.compile(r"^- \*\*([A-Z]+)-(\d+)\*\*\s*(`[^`]*`)?\s*(.*)")
+_ID = re.compile(r"\b([A-Z]{2,5})-(\d{3})\b")
+_WORD = re.compile(r"[a-z][a-z0-9_]{2,}")
+STOP = frozenset(
+    {
+        "the",
+        "and",
+        "for",
+        "with",
+        "from",
+        "that",
+        "this",
+        "are",
+        "not",
+        "any",
+        "all",
+        "its",
+        "into",
+        "each",
+        "when",
+        "then",
+        "than",
+        "per",
+        "but",
+        "has",
+        "have",
+        "was",
+        "which",
+        "their",
+        "them",
+        "they",
+        "one",
+        "two",
+        "set",
+        "get",
+        "use",
+        "used",
+        "uses",
+        "test",
+        "tests",
+        "should",
+        "must",
+        "may",
+        "can",
+    }
+)
+
+
+@dataclass
+class Item:
+    id: str
+    prefix: str
+    tag: str
+    text: str
+
+
+@dataclass
+class TestFn:
+    path: str
+    line: int
+    name: str
+    text: str
+
+
+def parse_spec(text: str) -> list[Item]:
+    items: list[Item] = []
+    cur: Item | None = None
+    for ln in text.splitlines():
+        m = _ITEM.match(ln)
+        if m or ln.startswith("#"):
+            if cur:
+                items.append(cur)
+            cur = None
+            if m:
+                cur = Item(f"{m.group(1)}-{m.group(2)}", m.group(1), (m.group(3) or "").strip("`"), m.group(4))
+            continue
+        if cur and len(cur.text) < 1800:
+            cur.text += "\n" + ln
+    if cur:
+        items.append(cur)
+    return [i for i in items if i.prefix not in SKIP_PREFIXES]
+
+
+def parse_tests(root: Path) -> list[TestFn]:
+    """Every ``test_*`` function: name, docstring and source (truncated), with the module docstring as context."""
+    out: list[TestFn] = []
+    for f in sorted(root.rglob("test_*.py")):
+        src = f.read_text(encoding="utf-8")
+        tree = ast.parse(src)
+        mod_doc = (ast.get_docstring(tree) or "").split("\n")[0]
+        for node in ast.walk(tree):
+            if isinstance(node, ast.FunctionDef | ast.AsyncFunctionDef) and node.name.startswith("test_"):
+                body = ast.get_source_segment(src, node) or ""
+                text = f"# {f.relative_to(ROOT)} ({mod_doc})\n{body}"[:1600]
+                out.append(TestFn(str(f.relative_to(ROOT)), node.lineno, node.name, text))
+    return out
+
+
+def cited_ids(root: Path) -> dict[str, set[str]]:
+    """Spec IDs mentioned anywhere in each test file."""
+    out: dict[str, set[str]] = {}
+    for f in sorted(root.rglob("*.py")):
+        for m in _ID.finditer(f.read_text(encoding="utf-8")):
+            out.setdefault(f"{m.group(1)}-{m.group(2)}", set()).add(str(f.relative_to(ROOT)))
+    return out
+
+
+def _tokens(s: str) -> list[str]:
+    return [w for w in _WORD.findall(s.lower().replace("-", "_")) if w not in STOP]
+
+
+class Bm25:
+    def __init__(self, docs: list[str], k1: float = 1.4, b: float = 0.75) -> None:
+        self.toks = [Counter(_tokens(d)) for d in docs]
+        self.len = [sum(t.values()) for t in self.toks]
+        self.avg = sum(self.len) / max(len(self.len), 1)
+        df = Counter(w for t in self.toks for w in t)
+        n = len(docs)
+        self.idf = {w: math.log(1 + (n - c + 0.5) / (c + 0.5)) for w, c in df.items()}
+        self.k1, self.b = k1, b
+
+    def top(self, query: str, k: int) -> list[int]:
+        q = set(_tokens(query))
+        scores = []
+        for i, t in enumerate(self.toks):
+            s = 0.0
+            for w in q & t.keys():
+                tf = t[w]
+                s += self.idf[w] * tf * (self.k1 + 1) / (tf + self.k1 * (1 - self.b + self.b * self.len[i] / self.avg))
+            scores.append((s, i))
+        scores.sort(reverse=True)
+        return [i for s, i in scores[:k] if s > 0]
+
+
+QUESTION = (
+    "Does the test function in `tests[{i}]` check the behaviour that `requirement` specifies? Read the test's "
+    "assertions: a test that only touches the same area without asserting this behaviour does not count."
+)
+
+
+def judge(item: Item, cands: list[TestFn]) -> list[float]:
+    state = {"requirement": f"{item.id} ({item.tag}): {item.text.strip()}", "tests": [c.text for c in cands]}
+    qs = {
+        f"t{i}": noul(
+            QUESTION.format(i=i),
+            true="The test exercises this behaviour and asserts on its outcome",
+            false="The test checks something else, or only touches the area",
+        )
+        for i in range(len(cands))
+    }
+    ans = system_one(state, qs)
+    return [float(ans[f"t{i}"]["noul"]) for i in range(len(cands))]
+
+
+def main(argv: list[str] | None = None) -> int:
+    ap = argparse.ArgumentParser(description=__doc__.split("\n\n")[0])
+    ap.add_argument("--out", type=Path, default=ROOT / "spec_coverage_report.md")
+    ap.add_argument("--dry-run", action="store_true")
+    ap.add_argument("--prefix", nargs="*", help="only these prefixes, for example CLI OUT")
+    a = ap.parse_args(argv)
+    items = parse_spec(SPEC.read_text(encoding="utf-8"))
+    if a.prefix:
+        items = [i for i in items if i.prefix in a.prefix]
+    tests = parse_tests(TESTS)
+    cited = cited_ids(TESTS)
+    bm = Bm25([t.text for t in tests])
+    rows: list[tuple[Item, str, float, TestFn | None, str]] = []
+    for it in items:
+        if it.id in cited:
+            rows.append((it, "cited", 1.0, None, ", ".join(sorted(cited[it.id]))))
+            continue
+        cands = [tests[i] for i in bm.top(f"{it.id} {it.text}", 5)]
+        if not cands:
+            rows.append((it, "uncovered", 0.0, None, "no candidate test"))
+            continue
+        if a.dry_run:
+            rows.append((it, "planned", 0.0, cands[0], f"{len(cands)} candidates"))
+            continue
+        ps = judge(it, cands)
+        best = max(range(len(ps)), key=lambda k: ps[k])
+        status = "covered" if ps[best] >= COVERED else "maybe" if ps[best] >= MAYBE else "uncovered"
+        rows.append((it, status, ps[best], cands[best], ""))
+    order = ["uncovered", "maybe", "covered", "cited", "planned"]
+    lines = ["# Spec coverage by tests", ""]
+    tot = Counter(r[1] for r in rows)
+    lines.append(f"{len(rows)} items: " + " · ".join(f"{k} {tot[k]}" for k in order if tot[k]))
+    lines += ["", "| Prefix | Items | cited | covered | maybe | uncovered |", "|---|---|---|---|---|---|"]
+    for pfx in sorted({r[0].prefix for r in rows}):
+        c = Counter(r[1] for r in rows if r[0].prefix == pfx)
+        lines.append(f"| {pfx} | {sum(c.values())} | {c['cited']} | {c['covered']} | {c['maybe']} | {c['uncovered']} |")
+    for st in order:
+        sel = [r for r in rows if r[1] == st and st != "cited"]
+        if not sel:
+            continue
+        lines += ["", f"## {st} ({len(sel)})", ""]
+        for it, _, p, t, extra in sel:
+            first = it.text.strip().split("\n")[0][:140]
+            where = f" · best test `{t.path}:{t.line}` {t.name} (p {p:.2f})" if t else ""
+            lines.append(f"* **{it.id}** `{it.tag}` {first}{where}{(' · ' + extra) if extra else ''}")
+    a.out.write_text("\n".join(lines) + "\n")
+    print(f"{len(rows)} items: " + ", ".join(f"{k} {tot[k]}" for k in order if tot[k]) + f" → {a.out}")
+    return 0
+
+
+if __name__ == "__main__":
+    sys.exit(main())
diff --git a/scripts/jev/voice_check.py b/scripts/jev/voice_check.py
new file mode 100644
index 0000000..79b9224
--- /dev/null
+++ b/scripts/jev/voice_check.py
@@ -0,0 +1,152 @@
+"""Check public texts against the brand voice in branding/README.md: plain, exact, every claim next to its limitation.
+
+Code checks the mechanical rules (em and en dashes in prose, banned marketing words). For every paragraph of at least
+15 words, Jev answers three questions in one request: does the paragraph claim something about SimurgArray without
+any limitation or condition (Noul), does it use promotional exaggeration (Noul), and how plain is the tone (Score,
+four concrete levels). The tool marks paragraphs to look at; it never rewrites them.
+
+    python scripts/jev/voice_check.py README.md blog/*.md my_post.txt     # writes voice_report.md
+    python scripts/jev/voice_check.py --rules-only blog/*.md              # mechanical rules only, no API calls
+"""
+
+from __future__ import annotations
+
+import argparse
+import re
+import sys
+from dataclasses import dataclass, field
+from pathlib import Path
+
+sys.path.insert(0, str(Path(__file__).resolve().parent))
+from client import ROOT, noul, score, system_one
+
+BANNED = ["revolutionary", "cutting edge", "cutting-edge", "ai powered", "ai-powered", "next generation",
+          "next-generation", "seamless", "seamlessly", "unlock", "game changer", "game-changing", "best in class",
+          "world class", "blazing"]  # fmt: skip
+LIMIT_T, HYPE_T, TONE_T = 0.7, 0.6, 1.5
+TONE_LEVELS = [
+    "Plain and exact: short sentences, concrete facts or numbers, no salesmanship",
+    "Mostly plain, with an occasional vague or enthusiastic phrase",
+    "Noticeably promotional or vague: several adjectives or benefits stated without specifics",
+    "Marketing copy: superlatives, buzzwords and promises dominate",
+]
+
+
+@dataclass
+class Para:
+    path: str
+    line: int
+    heading: str
+    text: str
+    issues: list[str] = field(default_factory=list)
+
+
+def paragraphs(path: Path, text: str) -> list[Para]:
+    """Prose paragraphs and bullets; code blocks, tables, headings and front matter lines are skipped."""
+    out: list[Para] = []
+    heading, buf, start, in_code = "", [], 0, False
+
+    def flush() -> None:
+        if buf:
+            out.append(Para(str(path), start, heading, " ".join(buf)))
+            buf.clear()
+
+    for i, raw in enumerate([*text.splitlines(), ""], 1):
+        ln = raw.rstrip()
+        if ln.lstrip().startswith("```"):
+            flush()
+            in_code = not in_code
+            continue
+        if in_code:
+            continue
+        if not ln.strip() or ln.lstrip().startswith("|") or ln.startswith("#"):
+            flush()
+            if ln.startswith("#"):
+                heading = ln.lstrip("#").strip()
+            continue
+        m = re.match(r"\s*([*>-]|\d+\.)\s+", ln)
+        if m:
+            flush()
+            ln = ln[m.end() :]
+        if ln.lstrip().startswith("<"):  # raw HTML blocks (banners, badges) are layout, not prose
+            continue
+        if not buf:
+            start = i
+        buf.append(ln.strip())
+    return out
+
+
+def mechanical(p: Para) -> list[str]:
+    prose = re.sub(r"`[^`]*`|https?://\S+|\([^)]*\.(md|png|jpg|svg)\)", "", p.text)
+    prose = re.sub(r"\"[^\"]*\"|\u201c[^\u201d]*\u201d", "", prose)  # quoted words are examples, not usage
+    if re.match(r"\s*(Never|No|Do not)\b", prose):
+        prose = ""
+    issues = []
+    if re.search("[—–]", prose):
+        issues.append("em or en dash in prose")
+    low = prose.lower()
+    found = [w for w in BANNED if re.search(rf"\b{re.escape(w)}\b", low)]
+    if found:
+        issues.append("banned words: " + ", ".join(found))
+    return issues
+
+
+QUESTIONS = {
+    "no_limit": noul(
+        "Does `paragraph` claim that SimurgArray achieves, guarantees or provides something (accuracy, speed, "
+        "compatibility, safety, a benefit) without stating any limitation, condition, number or caveat in the same "
+        "paragraph?",
+        true="A capability or benefit is asserted with nothing that bounds it",
+        false="There is no such claim, or the claim comes with a number, condition or limitation",
+    ),
+    "hype": noul(
+        "Does `paragraph` use promotional exaggeration: superlatives, buzzwords or unqualified promises instead of "
+        "plain description?",
+        true="Contains marketing language or overstatement",
+        false="Plain description, even if enthusiastic in a modest way",
+    ),
+    "tone": score("How plain and exact is the tone of `paragraph`?", TONE_LEVELS),
+}
+
+
+def judge(p: Para, doc: str) -> dict[str, float]:
+    ans = system_one({"document": doc, "section": p.heading, "paragraph": p.text}, QUESTIONS)
+    return {"no_limit": float(ans["no_limit"]["noul"]), "hype": float(ans["hype"]["noul"]),
+            "tone": float(ans["tone"]["score"])}  # fmt: skip
+
+
+def main(argv: list[str] | None = None) -> int:
+    ap = argparse.ArgumentParser(description=__doc__.split("\n\n")[0])
+    ap.add_argument("files", nargs="+", type=Path)
+    ap.add_argument("--out", type=Path, default=ROOT / "voice_report.md")
+    ap.add_argument("--rules-only", action="store_true", help="mechanical rules only, no API calls")
+    a = ap.parse_args(argv)
+    flagged: list[tuple[Para, dict[str, float]]] = []
+    n = 0
+    for f in a.files:
+        doc = f.name
+        for p in paragraphs(f, f.read_text(encoding="utf-8")):
+            p.issues = mechanical(p)
+            vals: dict[str, float] = {}
+            if not a.rules_only and len(p.text.split()) >= 15:
+                n += 1
+                vals = judge(p, doc)
+                if vals["no_limit"] >= LIMIT_T:
+                    p.issues.append(f"claim without a limitation (p {vals['no_limit']:.2f})")
+                if vals["hype"] >= HYPE_T:
+                    p.issues.append(f"promotional language (p {vals['hype']:.2f})")
+                if vals["tone"] >= TONE_T:
+                    p.issues.append(f"tone {vals['tone']:.1f} of 3")
+            if p.issues:
+                flagged.append((p, vals))
+    lines = ["# Voice check", "", f"{n} paragraphs judged, {len(flagged)} flagged.", ""]
+    for p, _ in flagged:
+        lines.append(f"* `{p.path}:{p.line}` ({p.heading}) **{'; '.join(p.issues)}**")
+        lines.append(f"  > {p.text[:400]}")
+    a.out.write_text("\n".join(lines) + "\n")
+    print(f"{n} paragraphs judged, {len(flagged)} flagged → {a.out}")
+    return 0
+
+
+if __name__ == "__main__":
+    sys.exit(main())
diff --git a/scripts/nightly.py b/scripts/nightly.py
index 0bde8c4..3179b04 100644
--- a/scripts/nightly.py
+++ b/scripts/nightly.py
@@ -175,6 +175,23 @@ def render(night: dict[str, Any]) -> str:
         "<table><tr><th>step</th><th>verdict</th><th>seconds</th><th>details</th><th></th></tr>"
         + "".join(rows)
         + "</table>"
+        + _triage_html(night.get("triage"))
+    )
+
+
+def _triage_html(tri: dict[str, Any] | None) -> str:
+    if not tri:
+        return ""
+    if "error" in tri:
+        return f"<p>Triage failed: {html.escape(str(tri['error']))}</p>"
+    rows = "".join(
+        f"<tr><td>{html.escape(k)}</td><td>{html.escape(str(t['match']))}</td><td>{t['match_confidence']}</td>"
+        f"<td>{t['regression']}</td><td>{t['severity']}</td><td>{'yes' if t['needs_person'] else 'no'}</td></tr>"
+        for k, t in tri.items()
+    )
+    return (
+        "<h2>Triage</h2><table><tr><th>step</th><th>explained by</th><th>confidence</th><th>regression p</th>"
+        f"<th>severity (0 to 3)</th><th>needs a person</th></tr>{rows}</table>"
     )
 
 
@@ -209,6 +226,17 @@ def main() -> int:
     overall = "PASS" if all(s.get("verdict") in ("PASS", "SKIPPED") for s in steps.values()) else "FAIL"
     night = {"date": day, "version": version, "overall": overall, "seconds": round(time.time() - t0), "steps": steps}
     (base / "summary.json").write_text(json.dumps(night, indent=2) + "\n")
+    if overall != "PASS":  # which known finding explains each failing step (scripts/jev, needs the TypeSafe key)
+        try:
+            sys.path.insert(0, str(ROOT / "scripts" / "jev"))
+            from client import api_key
+            from nightly_triage import triage
+
+            if api_key():
+                night["triage"] = triage(base)
+                (base / "summary.json").write_text(json.dumps(night, indent=2) + "\n")
+        except Exception as e:  # triage is advice; it must never break the nightly run
+            night["triage"] = {"error": f"{type(e).__name__}: {e}"}
     (base / "index.html").write_text(render(night))
     # large intermediates are not kept (reports and summaries are)
     for heavy in ("gsa_gtc/gt/samples", "gsa_vcf/vcf", "omni_gtc/gt/samples"):
diff --git a/tests/unit/test_jev_tools.py b/tests/unit/test_jev_tools.py
new file mode 100644
index 0000000..53851a0
--- /dev/null
+++ b/tests/unit/test_jev_tools.py
@@ -0,0 +1,78 @@
+"""Maintenance tools in scripts/jev: everything except the API calls."""
+
+from __future__ import annotations
+
+import gzip
+import importlib.util
+import json
+import sys
+from pathlib import Path
+from types import ModuleType
+
+ROOT = Path(__file__).resolve().parents[2]
+JEV = ROOT / "scripts" / "jev"
+
+
+def _load(name: str) -> ModuleType:
+    if str(JEV) not in sys.path:
+        sys.path.insert(0, str(JEV))
+    spec = importlib.util.spec_from_file_location(name, JEV / f"{name}.py")
+    assert spec is not None and spec.loader is not None
+    mod = importlib.util.module_from_spec(spec)
+    sys.modules[name] = mod
+    spec.loader.exec_module(mod)
+    return mod
+
+
+client = _load("client")
+cov = _load("spec_coverage")
+voice = _load("voice_check")
+tri = _load("nightly_triage")
+
+
+def test_client_builders() -> None:
+    assert client.noul("x?", true="a", false="b") == {"type": "noul", "instructions": "x?",
+                                                      "criteria": {"true": "a", "false": "b"}}  # fmt: skip
+    assert client.choice("pick", {"a": "A"})["type"] == "choice"
+    assert client.score("how", ["low", "high"])["criteria"] == ["low", "high"]
+
+
+def test_spec_parsing_skips_open_questions() -> None:
+    text = (
+        "## 14 CLI\n- **CLI-005** `§14 · P1` **Option precedence.**\nCLI flags beat config files.\n"
+        "- **OQ-001** `§20` Is this needed?\n## 15 Outputs\n- **OUT-031** `§9 · P6` VCF records are sorted.\n"
+    )
+    items = cov.parse_spec(text)
+    assert [i.id for i in items] == ["CLI-005", "OUT-031"]
+    assert items[0].tag == "§14 · P1" and "config files" in items[0].text
+
+
+def test_bm25_prefers_matching_test() -> None:
+    bm = cov.Bm25(["def test_vcf_sorted(): records sorted by position", "def test_idat_header(): magic bytes"])
+    assert bm.top("VCF records are sorted by position", 1) == [0]
+
+
+def test_voice_rules() -> None:
+    paras = voice.paragraphs(Path("x.md"), "# H\n\nA seamless — revolutionary tool.\n\n```\nnot prose\n```\n")
+    assert len(paras) == 1 and paras[0].heading == "H"
+    issues = voice.mechanical(paras[0])
+    assert "em or en dash in prose" in issues and any("seamless" in i for i in issues)
+    quoted = voice.Para("x.md", 1, "", 'Never write "revolutionary" or "seamless".')
+    assert voice.mechanical(quoted) == []
+
+
+def test_known_findings_and_evidence(tmp_path: Path) -> None:
+    kf = tri.known_findings("| K-014 | 2026-09-28 | NaN sign | NaNs take the platform's sign. | resolved |\n")
+    assert kf == {"K-014": "NaN sign: NaNs take the platform's sign."}
+    (tmp_path / "s" / "compare").mkdir(parents=True)
+    (tmp_path / "s" / "compare" / "summary.json").write_text(
+        json.dumps({"fields": {"GT": {"tolerance": "exact", "discrepancies": 2}, "X": {"discrepancies": 0}}})
+    )
+    with gzip.open(tmp_path / "s" / "compare" / "discrepancies.tsv.gz", "wt") as fh:
+        fh.write("pair\tfield\n1\tGT\n")
+    (tmp_path / "run.log").write_text("pi_run: MemAvailable 500 MiB < 800 MiB -- stopping the job\n")
+    ev = tri.evidence(tmp_path, "s", {"verdict": "FAIL", "report": "s/compare/dashboard.html"})
+    assert ev["differing_fields"] == {"GT": {"tolerance": "exact", "discrepancies": 2}}
+    assert ev["first_rows"][1] == "1\tGT" and "log" not in ev  # another step's log line must not leak in
+    ev2 = tri.evidence(tmp_path, "t", {"verdict": "ERROR", "error": "exit 137"})
+    assert ev2["log"] == ["pi_run: MemAvailable 500 MiB < 800 MiB -- stopping the job"]