fix(llm): tag and eval-tags read one set of tagger parameters

stack llm tag defaulted to --min-confidence 0.0 while eval-tags scored
at 0.60, so a run without flags was not the configuration that was
gated. [llm].tag_top / tag_max_tags / tag_min_confidence now default
both commands (unchanged values: 8 / 3 / 0.60).

src/cli/llm.py

@@ -283,15 +283,17 @@ def tag(
         False, "--dry-run", help="Compute and print, write nothing."
     ),
     top: int = typer.Option(
-        8, "--top", help="Themes shortlisted per comment before judging."
+        None,
+        "--top",
+        help="Themes shortlisted per comment before judging [llm].tag_top.",
     ),
     max_tags: int = typer.Option(
-        3, "--max-tags", help="Most themes written per comment."
+        None, "--max-tags", help="Most themes written per comment [llm].tag_max_tags."
     ),
     min_confidence: float = typer.Option(
-        0.0,
+        None,
         "--min-confidence",
-        help="Shortlist similarity below which a judged yes is not written.",
+        help="Shortlist similarity a judged yes must reach [llm].tag_min_confidence.",
     ),
     verbose: bool = typer.Option(
         False, "--verbose", help="Print every comment's tags."
@@ -306,6 +308,11 @@ def tag(
     from llm.tagger import run as run_tagging
 
     cfg = llm_config.load()
+    top = cfg.tag_top if top is None else top
+    max_tags = cfg.tag_max_tags if max_tags is None else max_tags
+    min_confidence = (
+        cfg.tag_min_confidence if min_confidence is None else min_confidence
+    )
     rt = _tagging_runtime(cfg)
 
     def progress(key: str, result: Any, why: str) -> None:
@@ -357,9 +364,11 @@ def eval_tags(
     limit: int = typer.Option(
         0, "--limit", help="Score only the first N golden entries."
     ),
-    top: int = typer.Option(8, "--top"),
-    max_tags: int = typer.Option(3, "--max-tags"),
-    min_confidence: float = typer.Option(0.60, "--min-confidence"),
+    top: int = typer.Option(None, "--top", help="[llm].tag_top"),
+    max_tags: int = typer.Option(None, "--max-tags", help="[llm].tag_max_tags"),
+    min_confidence: float = typer.Option(
+        None, "--min-confidence", help="[llm].tag_min_confidence"
+    ),
     dump: str = typer.Option(
         "",
         "--dump",
@@ -406,7 +415,13 @@ def eval_tags(
         from llm import config as llm_config
         from llm.tagger import tag_comment
 
-        rt = _tagging_runtime(llm_config.load())
+        cfg = llm_config.load()
+        top = cfg.tag_top if top is None else top
+        max_tags = cfg.tag_max_tags if max_tags is None else max_tags
+        min_confidence = (
+            cfg.tag_min_confidence if min_confidence is None else min_confidence
+        )
+        rt = _tagging_runtime(cfg)
         dumped: dict[str, Any] = {}
 
         def tag_one(key: str):

src/llm/config.py

@@ -39,6 +39,12 @@ class LlmConfig:
     instruct_model_large: str = ""
     large_min_vram_gb: float = 20.0
     chat_num_ctx: int = 8192
+    #: Theme tagger (P35): candidates shortlisted per comment, most tags
+    #: written, and the shortlist similarity a judged yes must reach.
+    #: `stack llm tag` and `eval-tags` both default to these.
+    tag_top: int = 8
+    tag_max_tags: int = 3
+    tag_min_confidence: float = 0.60
     chat_temperature: float = 0.2
     chat_max_tokens: int = 1200
     #: Characters per token the instruct model's tokenizer yields on the
@@ -127,6 +133,9 @@ def load() -> LlmConfig:
         instruct_model_large=str(_opt(section, "instruct_model_large", "")),
         large_min_vram_gb=float(_opt(section, "large_min_vram_gb", 20.0)),
         chat_num_ctx=int(_opt(section, "chat_num_ctx", 8192)),
+        tag_top=int(_opt(section, "tag_top", 8)),
+        tag_max_tags=int(_opt(section, "tag_max_tags", 3)),
+        tag_min_confidence=float(_opt(section, "tag_min_confidence", 0.60)),
         chat_temperature=float(_opt(section, "chat_temperature", 0.2)),
         chat_max_tokens=int(_opt(section, "chat_max_tokens", 1200)),
         chat_chars_per_token=float(_opt(section, "chat_chars_per_token", 2.4)),

stack.toml

@@ -114,6 +114,9 @@ instruct_model = "qwen2.5:14b"         # baseline, pulled on every fleet host
 instruct_model_large = "qwen2.5:32b"   # used when the chosen host declares >= large_min_vram_gb
 large_min_vram_gb = 20
 chat_num_ctx = 8192                    # passed per request; no Modelfile ctx variants
+tag_top = 8                            # theme tagger: candidates judged per comment (P35)
+tag_max_tags = 3                       # most themes written per comment
+tag_min_confidence = 0.60              # shortlist similarity a judged yes must reach; gated with eval-tags
 chat_temperature = 0.2                 # grounded answers cite labels verbatim; low temperature keeps them literal
 chat_max_tokens = 1200                 # num_predict: a history answer ran to 5,000 tokens (3 min) without a cap
 chat_chars_per_token = 2.4             # measured 2.5–2.9 on FR/regulatory text; sizes the excerpt budget so prompt + reply fit chat_num_ctx (overflow is caught and rebuilt)

tests/cli/test_llm_tag_cli.py

@@ -2,6 +2,8 @@
 
 from __future__ import annotations
 
+from types import SimpleNamespace
+
 import pytest
 from typer.testing import CliRunner
 
@@ -47,7 +49,10 @@ def rt(monkeypatch, tmp_path):
         "model": "m",
     }
     monkeypatch.setattr(llm_cli, "_tagging_runtime", lambda cfg: runtime)
-    monkeypatch.setattr("llm.config.load", lambda: object())
+    monkeypatch.setattr(
+        "llm.config.load",
+        lambda: SimpleNamespace(tag_top=8, tag_max_tags=3, tag_min_confidence=0.0),
+    )
     try:
         yield store, key, judged
     finally:

tests/llm/test_config.py

@@ -153,3 +153,14 @@ def test_instruct_model_env_override(monkeypatch):
     assert load().instruct_model == "qwen2.5:32b"
     monkeypatch.delenv("LLM_INSTRUCT_MODEL")
     assert load().instruct_model == "qwen2.5:14b"
+
+
+def test_tagging_parameters_load_from_config():
+    # `stack llm tag` defaulted to min_confidence 0.0 while eval-tags used
+    # 0.60: the run and its gate disagreed. Both now read these.
+    from llm.config import load
+
+    cfg = load()
+    assert cfg.tag_top == 8
+    assert cfg.tag_max_tags == 3
+    assert cfg.tag_min_confidence == 0.60