conversation-summary

What This Skill Does

The conversation-summary skill is a robust tool designed for OpenClaw AI agents to distill lengthy dialogue logs into concise, coherent executive summaries. By leveraging incremental update logic, the skill efficiently tracks the progression of a conversation without needing to re-process every historical interaction from scratch. It takes a list of chat objects—formatted in standard JSON—and outputs a high-level overview, making it perfect for long-running assistant sessions where keeping context is vital. The skill handles the heavy lifting of language processing, allowing agents to maintain situational awareness throughout complex task flows or extended user interactions.

Installation

To integrate this skill into your local OpenClaw environment, execute the following command in your terminal. Ensure that you have the necessary permissions to install packages within your agent's directory:

clawhub install openclaw/skills/skills/dadaliu0121/dada-conversation-summary

Once the installation is complete, verify that the path is correctly set in your configuration to allow the agent to reference conversation_summary.py during runtime.

Use Cases

This skill is highly valuable in several scenarios, including:

• Customer Support: Agents can summarize long support tickets to provide quick handoffs to human managers.
• Meeting Notes: If OpenClaw is being used to transcribe a meeting, this skill can provide a bulleted summary of key decisions made.
• Long-term Context Management: When a user checks in on a project after several days, the agent can use this skill to quickly synthesize what has been decided so far.
• Documentation: Transforming unstructured chat logs into a clean summary for project logs or archival purposes.

Example Prompts

1. "Could you summarize this conversation so I can catch up on what we decided?"
2. "Generate a quick summary of the main points from our recent chat history."
3. "What did we talk about regarding the project deadline earlier?"

Tips & Limitations

To get the best results, always ensure that your input chat_list is properly sanitized and formatted as a strict JSON array. Because the skill relies on an external script, please ensure your network settings allow the agent to interact with the API endpoints required for processing. If the conversation history is exceptionally large, consider providing a history_summary parameter to trigger the incremental update feature, which optimizes performance and reduces token usage significantly. Always validate that your chat logs contain accurate role labels ("user" or "assistant") to prevent parsing errors.