parallel-search

What This Skill Does

The parallel-search skill is a robust, AI-optimized web search engine specifically engineered for OpenClaw agents. Unlike standard search APIs, it provides context-aware, ranked results accompanied by intelligent text excerpts. These excerpts are meticulously processed to suit the input token requirements of LLMs, reducing noise and highlighting essential information. The tool provides a powerful CLI interface allowing for granular control over search parameters such as domain filtering, date constraints, and keyword injection, ensuring that your agent retrieves only the most relevant and high-quality data for its tasks.

Installation

You can integrate this skill into your environment using the standard OpenClaw installer. Execute the following command in your terminal: clawhub install openclaw/skills/skills/normallygaussian/parallel-search

Use Cases

This skill is indispensable for research-heavy AI tasks. Use it for:

• Fact-Checking: Verify claims and retrieve citations to reduce hallucinations.
• Market Research: Gather the latest industry news, competitive analysis, or trends.
• Technical Documentation: Perform domain-specific lookups on platforms like GitHub or official developer documentation to solve specific coding issues.
• Current Event Monitoring: Use date filters to fetch real-time updates and news articles for time-sensitive projects.

Example Prompts

1. "Perform a search for the best practices in React server components. Please focus specifically on results from the official react.dev domain and filter out older articles from before 2025."
2. "Research the latest breakthroughs in fusion energy for the first quarter of 2026. Use at least 5 keyword modifiers to ensure accuracy, and provide me with a summary citing the top three results."
3. "Look up the current status of the open-source project 'OpenClaw' on GitHub. Provide me with the latest release notes and identify if there are any known critical bugs mentioned in the documentation or issues."

Tips & Limitations

To maximize the performance of parallel-search, always utilize the -q flag to define specific keyword constraints; providing 3-8 keywords significantly improves precision. When dealing with long-running agent sessions, remember to output your findings to a file using the -o flag to prevent context window overflow. Be aware that while the skill retrieves high-quality excerpts, primary sources should always be validated manually if the information pertains to critical decision-making or legal compliance. Avoid using excessively broad search queries without domain filtering, as this may dilute the quality of the ranked results returned by the engine.