A specialized tool for generating concise summaries and incremental updates for multi-turn conversation logs.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install chat-conversation-summary
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install chat-conversation-summary using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Conversation Summary?
The Conversation Summary skill is designed to help AI agents and developers distill long-form dialogues into manageable summaries. As a powerful addition to the Openclaw Skills library, it offers unique support for incremental updates, allowing the system to merge new chat data with existing summaries without starting from scratch. This ensures that context is preserved efficiently across long-running sessions.
By automating the synthesis of chat logs, this skill enables users to quickly grasp the core themes of a discussion or retrieve specific outcomes from a previous interaction. It is built to be lightweight, relying on Python and standard HTTP requests to interface with summary engines.
Conversation Summary Use Cases
- Recapping complex technical discussions or project brainstorming sessions.
- Generating brief highlights for customer support or client communication logs.
- Maintaining a running history of AI-user interactions for long-term memory management.
- Extracting key action items or decisions from multi-participant chat history.
How Conversation Summary Works
- The AI agent identifies a trigger phrase such as 'summarize this' or 'what did we talk about'.
- The relevant chat history is prepared as a JSON-formatted list of role and content objects.
- The summarize_conversation tool is called, optionally passing an existing summary to perform an incremental update.
- A Python script processes the input and communicates with the underlying summarization API.
- The tool returns a structured JSON response containing the generated summary text and execution status.
Conversation Summary Setup
To integrate this skill into your Openclaw Skills workflow, ensure you have Python 3 and the required dependencies installed:
pip install requests
The script can be executed directly via the command line:
python3 scripts/conversation_summary.py '<chat_list_json>' '<history_summary>'
Conversation Summary Data Schema & Taxonomy
The skill utilizes a structured JSON schema for both inputs and outputs to ensure data integrity:
| Component | Type | Description |
|---|---|---|
| chat_list | JSON String | Array of message objects (e.g., [{"role":"user", "content":"..."}]). |
| history_summary | String | Optional previous summary used for incremental context building. |
| status | String | Indicates success ('completed') or failure ('error'). |
| summary | String | The final generated text containing the conversation highlights. |
| error | String | Detailed error logs provided if the API request fails. |
Conversation Summary Advanced Features
- Incremental Update Support: Efficiently appends new context to existing summaries rather than re-summarizing the entire thread.
- Role-Based Parsing: Specifically optimized for user/assistant message structures found in modern AI interactions.
- Error Resilience: Includes built-in validation for JSON formatting and network connectivity error handling.
- Native Openclaw Skills Compatibility: Designed to work seamlessly within agentic workflows that require automated documentation and context tracking.
SKILL.md
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