A powerful utility for generating incremental and full summaries of conversation logs via automated AI workflows.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install dada-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 dada-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 a specialized tool designed for Openclaw Skills to transform verbose chat histories into concise, actionable summaries. By processing JSON-formatted dialogue lists, it allows AI agents to maintain context and provide users with rapid overviews of long-running interactions without manual review. This skill is particularly valuable for developers building complex agentic workflows where memory management and state distillation are critical for performance.
This implementation leverages a robust Python backend to interface with summarization APIs, ensuring that even high-volume chat logs are distilled accurately. It provides a bridge between raw interaction data and high-level comprehension within the Openclaw Skills ecosystem.
Conversation Summary Use Cases
- Distilling long technical support chats into brief, actionable bullet points.
- Generating incremental updates for recurring stand-up or project discussions using Openclaw Skills.
- Creating "at-a-glance" recaps for users returning to an AI session after a long hiatus.
- Pre-processing massive conversation datasets for archival or documentation purposes.
How Conversation Summary Works
- The user triggers a summary request through natural language prompts such as "summarize this conversation."
- The agent gathers the current conversation logs and formats them into a valid JSON chat_list array.
- If a previous summary exists, it is passed as an optional history_summary parameter to enable an incremental update.
- The skill executes a Python script that transmits the payload to the underlying summary engine.
- The system returns a structured JSON response containing the refined summary text and execution status.
Conversation Summary Setup
Ensure you have Python 3 and the requests library installed to use this within the ecosystem of Openclaw Skills.
pip install requests
To call the tool manually for testing or CLI integration:
python3 scripts/conversation_summary.py '<chat_list_json>' '<history_summary>'
Conversation Summary Data Schema & Taxonomy
The skill operates on a standardized JSON input and output schema to ensure compatibility across different Openclaw Skills implementations.
| Field | Type | Description |
|---|---|---|
| chat_list | String (JSON) | A list of objects containing role and content keys representing the dialogue history. |
| history_summary | String | An optional field containing the prior summary text used for context-aware updates. |
| status | String | Indicates the execution state, returning either completed or error. |
| summary | String | The final generated text output from the summarization process. |
Conversation Summary Advanced Features
- Incremental Update Support: Reduces computational overhead and maintains continuity by refining existing summaries rather than reprocessing the entire history.
- Standardized JSON Interoperability: Designed to fit seamlessly into data pipelines involving other Openclaw Skills.
- Automated Validation: Built-in checks to ensure chat_list formatting is valid JSON before processing, preventing script failures.
- Error Resilience: Detailed error reporting for network connectivity issues or API-level failures.
SKILL.md
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