rag-feedbacklisted

# rag-feedback — record search-result feedback > Before executing this workflow, read and apply `../HOST_CONTRACT.md`. ## What Records via `rag_record_feedback` whether the most recent `rag-search` result was good or not. Feedback accumulates in `.noory/rag/feedback.json` (personal — not shared) and, from the next search on, is **reflected in ranking at the material (file) level** — material that was good rises, material that was not sinks. (Not embedding retraining — it is a per-`rel_path` bonus/penalty, so it survives reindexing.) ## Steps 1. **Identify the target**: capture the **query** of the most recent search and the target **evidence file (rel_path)** for the feedback. - If the user points at a specific piece of evidence ("evidence #2 was right"), use that `rel_path`. - For an overall assessment, apply it to each of the top evidence items' `rel_path`. 2. **Extract the verdict**: good/bad from the utterance. - Positive ("was good / correct / helpful") → `good` - Negative ("meh / wrong / no / irrelevant") → `bad` 3. **Record**: for each (query, rel_path), `rag_record_feedback(query=<query>, rel_path=<file>, verdict=<good|bad>)`. 4. **Confirmation output**: ``` ✅ Feedback recorded: <rel_path> ← good/bad It will be reflected from the next search on. Aggregation is `/rag:rag-feedback-report`. ``` ## Notes - If there is no recent-search context, confirm which query/material the feedback is about before proceeding. - Feedback is personal materia