Privatedeepsearch Melt

What This Skill Does

Privatedeepsearch Melt is a specialized, privacy-centric research assistant designed for the OpenClaw ecosystem. Developed by romancircus, it acts as a decentralized alternative to corporate-controlled search engines. Unlike standard AI research tools that rely on centralized, telemetry-heavy APIs like Google or Bing, Melt utilizes SearXNG to aggregate results from privacy-respecting search engines such as DuckDuckGo, Brave, and Startpage.

The core functionality resides in its 'Deep Research' capability, which goes beyond a single query. Melt performs iterative research cycles: she queries the web, reads content, refines her context based on findings, scrapes full articles, and synthesizes the data into a cohesive report complete with source citations. Because the skill runs entirely on your local hardware via Docker, your search history, behavioral patterns, and personal data remain under your exclusive control. There is no cloud logging, no data monetization, and no subscription fee.

Installation

To integrate Melt into your OpenClaw agent, you have two primary methods:

1. ClawdHub (Recommended): Run the command clawdhub install privatedeepsearch-melt in your terminal. This will automatically pull the necessary dependencies and register the skill within your agent's environment.
2. Manual Setup: Clone the source repository from openclaw/skills, navigate to the docker directory, and run docker-compose up -d. This initiates the local SearXNG instance required for Melt's query processing. Once active, ensure you place the skill files in ~/.clawdbot/skills/ so your agent can interface with the new toolset.

Use Cases

• Sensitive Topic Research: Investigate medical, financial, or private industry topics without leaving a trail for data brokers to build a profile on you.
• Academic & Technical Synthesis: Use the 'deep-research' command to digest complex technical documentation or papers across multiple web sources and generate a summarized report.
• Vendor Agnostic Shopping: Perform market research and feature comparisons without being subjected to ad-tracking algorithms that influence your search results based on historical behavior.

Example Prompts

• 'Melt, deep-research the current state of consumer privacy laws in the European Union vs the United States as of 2026.'
• 'Perform a private search for the best open-source self-hosted password managers and list the top 5 with their respective security audit status.'
• 'Use the searx tool to find recent discussions on the implementation of local-only vector databases for private AI agents.'

Tips & Limitations

• Hardware Requirements: Because Melt performs iterative scraping and reading of full articles locally, ensure your machine has sufficient RAM and CPU overhead to handle multiple concurrent browser-like processes.
• Network Privacy: While the tool prevents tracking by the search engine providers, it still connects to the internet to perform queries. Consider using a VPN alongside Melt if you wish to hide your IP address from the websites you are researching.
• Depth vs Speed: Deep research cycles are resource-intensive. For quick facts, stick to standard search; reserve the deep-research functionality for tasks that actually require multi-step synthesis.