conversation-review

## Overview This skill is for **semantic and context layer curators** who want to use accumulated user feedback to drive continuous improvement. It structures the work into two phases: 1. **Categorize** — review past conversations with feedback and classify each piece of feedback into an actionable improvement category 2. **Act** — turn the categorized feedback into a concrete list of changes, then apply them to the semantic model or context layer on a branch --- ## Prerequisites Before starting, ensure a workspace and branch are set. Use `get_session_workspace_and_branch` to check the current context. If nothing is set, use `list_workspaces` and `set_session_workspace_and_branch`. See the `workspace-branch` skill for the full reference. You will be reading the model as-is (use `prod` branch for reading), then applying changes on a development branch later. --- ## Phase 1: Collect Conversations ### 1.1 Fetch conversations with feedback Use `list_analysis_chats` to retrieve past conversations. Focus on those that have received feedback — positive or negative. ``` list_analysis_chats(limit=50, offset=0) ``` Paginate with `offset` until you have covered the desired time window or conversation count. For each conversation, note: - `conversation_id` - `title` - `feedback` (the stored feedback text, if any) - `agent` and `domain` - `created_at` and `created_by` **Filter to conversations with feedback.** Skip conversations with no feedback unless the user explicitly wa...