test(llm): lock in _should_think classifier; drop briefing think overrides

Adds 38 parametrized tests for the _should_think classifier covering the
explicit-override path, empty/whitespace content, short/medium/long length
boundaries, case-insensitive keyword matching, and a chatty-message negative
set. These pin the content-based semantics so future tweaks to the keyword
list or length thresholds surface regressions immediately instead of going
unnoticed behind subtle latency changes.

Also drops the `think=True` overrides from the briefing /discuss-article
and /discuss-topic entry points. With `"discuss"` added to _THINK_KEYWORDS,
those canned prompts trip the classifier naturally, so the overrides were
redundant — keeping a uniform "classifier is authoritative" rule makes the
code easier to reason about.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

src/fabledassistant/routes/briefing.py

@@ -578,7 +578,6 @@ async def discuss_article(item_id: int):
         buf, history, model,
         uid, conv_id, conv.title or "",
         "Please summarize and discuss this article.",
-        think=True,
     ))
 
     return jsonify({"assistant_message_id": assistant_msg.id, "status": "generating"}), 202
@@ -677,7 +676,6 @@ async def discuss_topic(topic: str):
         buf, history, model,
         uid, conv_id, conv.title or "",
         user_prompt,
-        think=True,
     ))
 
     return jsonify({

src/fabledassistant/services/generation_task.py

@@ -67,6 +67,7 @@ _THINK_KEYWORDS: tuple[str, ...] = (
     "review", "critique", "evaluate", "trade-off", "tradeoff", "trade off",
     "pros and cons", "step by step", "walk me through",
     "prove", "derive", "figure out", "work through",
+    "discuss",  # covers briefing /discuss-article + /discuss-topic entry points
 )
 
 # Messages shorter than this and without any think-keyword are treated as

tests/test_should_think.py

@@ -0,0 +1,127 @@
+"""Tests for the `_should_think` classifier.
+
+`_should_think` decides whether qwen3-class models should engage chain-of-
+thought for a given chat turn. It is the single source of truth: frontend
+callers pass `think_requested=False` by default and defer to this function,
+while explicit `think_requested=True` acts as an override for curated
+analytical entry points.
+
+These tests lock in the content-based behavior so future tweaks don't
+silently regress the short / long / keyword boundaries.
+"""
+
+import pytest
+
+from fabledassistant.services.generation_task import (
+    _LONG_MESSAGE_CHARS,
+    _SHORT_MESSAGE_CHARS,
+    _should_think,
+)
+
+
+class TestExplicitOverride:
+    def test_override_forces_on_for_empty(self):
+        assert _should_think("", think_requested=True) is True
+
+    def test_override_forces_on_for_short_greeting(self):
+        assert _should_think("hi", think_requested=True) is True
+
+    def test_override_forces_on_for_medium_no_keyword(self):
+        text = "just checking in on the status of things for the week"
+        assert _should_think(text, think_requested=True) is True
+
+
+class TestEmptyAndWhitespace:
+    def test_empty_string_off(self):
+        assert _should_think("", think_requested=False) is False
+
+    def test_none_content_off(self):
+        # _should_think defensively handles None content from upstream callers
+        assert _should_think(None, think_requested=False) is False  # type: ignore[arg-type]
+
+    def test_whitespace_only_off(self):
+        assert _should_think("   \n\t  ", think_requested=False) is False
+
+
+class TestShortMessages:
+    def test_short_greeting_off(self):
+        assert _should_think("hi", think_requested=False) is False
+
+    def test_short_thanks_off(self):
+        assert _should_think("thanks!", think_requested=False) is False
+
+    def test_short_acknowledgement_off(self):
+        assert _should_think("ok sounds good", think_requested=False) is False
+
+    def test_just_below_short_threshold_off(self):
+        text = "a" * (_SHORT_MESSAGE_CHARS - 1)
+        assert _should_think(text, think_requested=False) is False
+
+
+class TestLongMessages:
+    def test_at_long_threshold_on(self):
+        text = "a" * _LONG_MESSAGE_CHARS
+        assert _should_think(text, think_requested=False) is True
+
+    def test_well_above_long_threshold_on(self):
+        text = "x" * (_LONG_MESSAGE_CHARS * 3)
+        assert _should_think(text, think_requested=False) is True
+
+
+class TestMediumMessages:
+    def test_medium_no_keyword_off(self):
+        # Between the short and long thresholds with no reasoning cue.
+        text = "a" * ((_SHORT_MESSAGE_CHARS + _LONG_MESSAGE_CHARS) // 2)
+        assert _should_think(text, think_requested=False) is False
+
+
+class TestKeywordTriggers:
+    @pytest.mark.parametrize(
+        "text",
+        [
+            "why is this failing",
+            "how does caching work here",
+            "how do i configure this",
+            "explain the retry logic",
+            "analyze the latency breakdown",
+            "compare gemma3 vs qwen3 for tool use",
+            "please design the schema for X",
+            "debug this error",
+            "troubleshoot the connection issue",
+            "root cause the outage",
+            "review this PR",
+            "critique my approach",
+            "walk me through the flow",
+            "step by step instructions please",
+            "pros and cons of each option",
+            "help me figure out what's wrong",
+            "discuss this article",  # covers briefing /discuss entry points
+        ],
+    )
+    def test_keyword_forces_on(self, text):
+        assert _should_think(text, think_requested=False) is True
+
+    def test_keyword_case_insensitive(self):
+        assert _should_think("WHY does this break?", think_requested=False) is True
+
+    def test_keyword_in_longer_sentence(self):
+        text = "hey quick one — can you explain what caching does for qwen3"
+        assert _should_think(text, think_requested=False) is True
+
+
+class TestNonTriggers:
+    """Messages that look chatty and should NOT trigger thinking."""
+
+    @pytest.mark.parametrize(
+        "text",
+        [
+            "hey",
+            "yep",
+            "no worries",
+            "got it, thanks",
+            "good morning",
+            "remind me later",  # no reasoning keyword, short
+        ],
+    )
+    def test_chatty_messages_off(self, text):
+        assert _should_think(text, think_requested=False) is False