The advisor prompt was flooded with internal refiner state that means
nothing to a language model: phrase category tags, raw axis code labels,
redundant recommendations, and duplicate encoded/original prompt fields.
With 15+ fields of noisy context, explicit user feedback buried at the
bottom was competing with everything else for the model's attention.
Changes:
- Phrase analysis removed entirely from advisor context
- Axis labels translated to plain English descriptions via _v2_axes_to_
plain_english: "missing action axis" → "The previous output was missing:
main action, movement, motion direction"
- V2 recommendations field removed (was a third copy of the same axis/
candidate information)
- Encoded prompt only shown when it actually differs from the original
- Repair candidates capped to 5 and framed as "Consider adding:" rather
than a raw list
- Negative advisor prompt receives the same treatment
- Negative prompt length rejection raised from 900 to 1200 chars
- feedback_prompt placed first in user context in both advisors, before
all other fields
- System prompt OVERRIDE block injected when feedback is present
- Protected-category and intent-distance validation bypassed when user
feedback is provided
- is_perfect analysis-only block and intent-change guard also bypassed
when feedback is present
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
