diff --git a/docs/docs/cli/llm-eval-tags.md b/docs/docs/cli/llm-eval-tags.md
index dd48296..9192922 100644
--- a/docs/docs/cli/llm-eval-tags.md
+++ b/docs/docs/cli/llm-eval-tags.md
@@ -23,8 +23,11 @@ Usage: stack llm eval-tags [OPTIONS]
 │ --limit                 INTEGER  Score only the first N golden entries.      │
 │                                  [default: 0]                                │
 │ --top                   INTEGER  [default: 8]                                │
-│ --max-tags              INTEGER  [default: 4]                                │
-│ --min-confidence        FLOAT    [default: 0.0]                              │
+│ --max-tags              INTEGER  [default: 3]                                │
+│ --min-confidence        FLOAT    [default: 0.6]                              │
+│ --dump                  TEXT     With --live: write every comment's          │
+│                                  shortlist, verdicts and confidences to this │
+│                                  JSON file.                                  │
 │ --help                           Show this message and exit.                 │
 ╰──────────────────────────────────────────────────────────────────────────────╯
 ```
diff --git a/src/cli/llm.py b/src/cli/llm.py
index fd5ebfa..eea5ccc 100644
--- a/src/cli/llm.py
+++ b/src/cli/llm.py
@@ -359,8 +359,8 @@ def eval_tags(
         0, "--limit", help="Score only the first N golden entries."
     ),
     top: int = typer.Option(8, "--top"),
-    max_tags: int = typer.Option(4, "--max-tags"),
-    min_confidence: float = typer.Option(0.0, "--min-confidence"),
+    max_tags: int = typer.Option(3, "--max-tags"),
+    min_confidence: float = typer.Option(0.60, "--min-confidence"),
     dump: str = typer.Option(
         "",
         "--dump",
diff --git a/src/llm/tagger.py b/src/llm/tagger.py
index 1bfa3bf..f19bc96 100644
--- a/src/llm/tagger.py
+++ b/src/llm/tagger.py
@@ -5,8 +5,9 @@ For one comment the chain is: its already-indexed chunks (text + vector,
 against every theme card (``llm.vocab.Theme.card`` embedded once per run)
 → the ``top`` themes shortlisted, each with the chunk that scored it →
 one yes/no judgement per candidate on the largest live host, with that
-chunk as the evidence → up to ``max_tags`` accepted themes, confidence =
-the shortlist similarity. Nothing outside ``{yes, no}`` counts as ``no``.
+chunk as the evidence → up to ``max_tags`` accepted themes whose shortlist similarity clears
+``min_confidence`` (defaults 3 and 0.60 — the settings that pass the
+golden gate, #577), confidence = that similarity. Nothing outside ``{yes, no}`` counts as ``no``.
 
 State lives on the bib item (``extra_json["llm_tags"]``: vocab version,
 model, content hash, the accepted tags with confidence and evidence
@@ -148,8 +149,8 @@ def tag_comment(
     card_vecs: Mapping[str, Vector],
     judge: Judge,
     top: int = 8,
-    max_tags: int = 4,
-    min_confidence: float = 0.0,
+    max_tags: int = 3,
+    min_confidence: float = 0.60,
 ) -> TagResult:
     cands = shortlist(chunk_vecs, card_vecs, top=top)
     judged: dict[str, bool | None] = {}
@@ -252,8 +253,8 @@ def run(
     force: bool = False,
     dry_run: bool = False,
     top: int = 8,
-    max_tags: int = 4,
-    min_confidence: float = 0.0,
+    max_tags: int = 3,
+    min_confidence: float = 0.60,
     progress: Callable[[str, TagResult | None, str], None] | None = None,
 ) -> dict[str, int]:
     """Tag every comment in *docket* (newest first); resumable via the