conversation-review
Use when a semantic/context layer curator wants to review past analysis conversations in bulk, categorize user feedback into actionable improvement areas, and apply targeted changes to the semantic model or context layer. Covers the full workflow from collecting conversations and classifying feedback through to creating action items and applying them on a branch.
Install
With your agent
Install OMGSkills skill "honeydew-ai/honeydew-ai-coding-agents-plugins:skills/conversation-review" into this agent's normal skills directory: call the OMGSkills MCP get_install_plan tool for your agent and run the script it returns (it installs only the pinned commit and verifies SKILL.md), and stop if MCP or the pin is unavailable. Do not overwrite or change existing skills without asking me.
Manual command
git clone https://github.com/honeydew-ai/honeydew-ai-coding-agents-plugins /tmp/honeydew-ai-coding-agents-plugins && ln -s /tmp/honeydew-ai-coding-agents-plugins/skills/conversation-review ~/.claude/skills/conversation-review
From README
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: Categorize — review past conversations with feedback and classify each piece of feedback into an actionable improvement category 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 getsessionworkspaceandbranch to check the current context. If nothing is set, use listworkspaces and setsessionworkspaceandbranch. 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 listanalysischats to retrieve past conversations.
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