A powerful multi-model synthesis tool that queries Claude, GPT, and Gemini simultaneously to provide comprehensive, expert-vetted answers.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install multisage
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 multisage 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 multisage?
multisage is a sophisticated technical skill designed to harness the collective intelligence of the world's leading AI models. By sending queries to Claude, GPT, and Gemini in parallel, it eliminates the bias of any single model and provides a synthesized response that identifies consensus and highlights productive debates between different AI perspectives. This makes it an invaluable asset for users looking to expand their Openclaw Skills library with high-reliability reasoning capabilities.
The skill is built for developers and researchers who need more than a single opinion. It automates the workflow of cross-referencing information, allowing users to receive a "consultation" from multiple experts in a single step. Whether you are solving complex architectural problems or performing deep market research, this tool ensures your answers are well-rounded and thoroughly analyzed.
multisage Use Cases
- Comparing technical trade-offs between different programming languages or frameworks.
- Resolving complex debugging sessions by getting perspectives from multiple model architectures.
- Performing deep-dive research on academic or market topics using parallel web-search agents.
- Validating facts and finding consensus across different AI providers to reduce hallucinations.
- Generating comprehensive summaries that incorporate diverse viewpoints for report writing.
How multisage Works
- The skill receives a natural language query or research prompt from the user interface.
- It triggers the multisage CLI to communicate with the Multisage API, passing the query to multiple AI providers (Claude, GPT, Gemini) simultaneously.
- The system monitors the progress of each provider, especially during long-running deep research tasks.
- A synthesis engine aggregates the individual responses, creating a unified answer that highlights agreements and disagreements.
- The final output is streamed back to the user, including a breakdown of individual expert opinions and credits consumed.
multisage Setup
To integrate this into your environment, first install the CLI globally:
npm install -g multisage
You must then set your API key in your environment variables to enable the Openclaw Skills integration to function correctly:
export MULTISAGE_API_KEY="msk_your_actual_key"
Always use the -q flag when running commands through automated agents to prevent interactive spinners from interfering with the output.
multisage Data Schema & Taxonomy
The skill returns structured data that can be consumed as plain text or JSON. Below is the primary structure of the synthesis:
| Property | Description |
|---|---|
| answer | The primary synthesized response from all experts. |
| stages.synthesis | The detailed integration of all expert viewpoints. |
| stages.debate | A section highlighting where the AI models disagreed. |
| experts | A list of the specific AI models used for the query. |
| creditsUsed | The credit cost (1 for standard, 5 for deep research). |
multisage Advanced Features
- Deep Research Mode: Initiates 5-25 minute parallel research sessions using web-search enabled agents for exhaustive technical analysis.
- JSON Formatting: Use the
-jflag to output structured data for integration into other scripts or automation workflows. - Thread Management: Capability to detach from long-running research tasks and retrieve results later using unique thread IDs.
- Full Verbosity: The
--fullflag allows users to see the raw, individual responses from each AI model before they are synthesized.
SKILL.md
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