fix(h3): the emphasis line reports counts, never the phrases themselves

It named the three strongest learned phrases as examples. Phrase memory holds
the user's prompt, so every paste of the log carried prompt text out with it —
stripped by hand each time, which is a thing that will eventually be forgotten.

The strongest weight replaces them: it answers the question the examples were
there for (is emphasis doing too much) without quoting anything. Counts stay.

Adds a test on the SHAPE, not on one message — joining phrase text into a log
line is how this would come back.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>

conditioning.py

@@ -11727,14 +11727,17 @@ class FunPackVideoRefinerV2(FunPackVideoRefiner):
                         landed[_t] = _w
             out.append([cond, meta] if isinstance(entry, list) else (cond, meta))
         if applied:
-            # Names what was APPLIED. Reporting the candidate list meant phrases that are no
-            # longer in the prompt were named as weighted when they had matched nothing.
-            top = sorted(landed.items(), key=lambda p: -p[1])[:3]
+            # COUNTS AND WEIGHTS ONLY — never the phrases themselves. The log is the thing
+            # the user copies out to send somewhere, and the phrases are their prompt: naming
+            # three of them puts prompt text into every paste. The strongest weight is what
+            # the number is for, and it says the same thing about whether emphasis is doing
+            # too much without quoting anything.
+            strongest = max(landed.values()) if landed else 0.0
             _log.note_on_change(
                 "h3:token_weights", "FunPackStudio",
                 f"rating-derived phrase emphasis: {len(landed)} of {len(weighted)} learned "
                 f"phrase(s) are in this prompt and were weighted across {applied} scene(s)"
-                + (" (e.g. " + ", ".join(f"{t!r} x{w:.2f}" for t, w in top) + ")" if top else "")
+                + (f", strongest x{strongest:.2f}" if landed else "")
                 + " — applied as an attention bias on H3's packed stream, where the attn2 "
                   "K/V emphasis has nothing to hook.")
         return out

tests/test_logs_do_not_quote_the_prompt.py

@@ -0,0 +1,44 @@
+"""No log line prints the user's own words back at them.
+
+The log is the thing that gets copied out and sent somewhere. Phrase memory holds the user's
+prompt, so a line naming three learned phrases puts prompt text into every paste — which the
+user then has to strip by hand, every time, and will eventually forget to.
+
+Counts and weights say everything the line is for. The phrases say nothing that a count does
+not, and they are the half that cannot be un-sent.
+"""
+import inspect
+import re
+import sys
+
+sys.path.insert(0, ".")
+
+
+def _source():
+    import conditioning
+    return inspect.getsource(conditioning.FunPackVideoRefinerV2._v2_apply_h3_token_weights)
+
+
+def test_the_emphasis_line_reports_counts_not_phrases():
+    src = _source()
+    assert "of {len(weighted)} learned" in src          # the count survives
+    assert "strongest x" in src                          # so does the magnitude
+    assert "{t!r}" not in src                            # the phrases do not
+    assert "e.g." not in src
+
+
+def test_no_log_line_in_the_refiner_joins_phrase_text():
+    """A guard on the shape, not on one message: `", ".join(...)` over phrase-ish values
+    inside a log call is how this came back the first time."""
+    import conditioning
+    src = inspect.getsource(conditioning)
+    offenders = [m.group(0) for m in re.finditer(r'"\s*\(e\.g\.\s*"\s*\+\s*", "\.join', src)]
+    assert offenders == []
+
+
+def test_the_sampler_reports_the_same_way():
+    """The sampler prints its own emphasis line; it must follow the same rule."""
+    import samplers
+    src = inspect.getsource(samplers)
+    assert "strongest x{strongest:.2f}" in src
+    assert "token span(s) biased" in src