research

What This Skill Does

The research skill is a powerful, persistent documentation engine designed for OpenClaw. Unlike ephemeral chat, this skill creates a structured, evolving markdown workspace to track inquiries from conception to conclusion. It manages the lifecycle of a topic by creating a dedicated directory containing your original prompt, your living research findings, and any supporting artifacts. Whether you are performing a quick fact-check or a long-term technical deep-dive, the research skill ensures your information is organized, accessible, and iterative.

Installation

To install this skill, use the following command in your terminal: clawhub install openclaw/skills/skills/brennerspear/parallel-ai-research

Use Cases

• Technical Due Diligence: Evaluate frameworks or libraries before integration by creating a comparison matrix in your research document.
• Market Analysis: Use the Deep Research mode to aggregate competitive landscape data over an extended period.
• Knowledge Management: Document complex project requirements or investigate architectural decisions that need to be captured for team transparency.
• Brainstorming & Strategy: Explore multi-faceted problems by breaking them down into 'Open Questions' and 'Findings' sections within the generated workspace.

Example Prompts

1. "I need to figure out if Rust or Go is better for our new microservice architecture. Start a research doc for this and list the pros and cons."
2. "Perform deep research on the current state of decentralized identity protocols and summarize the security implications in my research folder."
3. "Keep researching these integration options; add your findings to the existing research.md file and suggest three next steps."

Tips & Limitations

• Maintain Context: Always let the agent know if you are continuing an existing research project or starting a new topic to ensure files are organized correctly.
• Use Deep Research Sparingly: Deep research is resource-intensive. Reserve it for tasks that truly require parallel exploration and time, rather than simple fact-retrieval.
• Manual Curation: While the agent automates the collection, the most valuable research documents are those where the user periodically refines the 'Findings' and 'Next Steps' sections to keep the document focused.