Coordinate multi-agent web research and synthesize cited Markdown reports.
npx skills add https://github.com/Lincoln504/pi-research --skill pi-research
Please help me install this Agent Skill. Skill: pi-research Source: https://github.com/Lincoln504/pi-research/tree/main/skills/pi-research Command: npx skills add https://github.com/Lincoln504/pi-research --skill pi-research
This Skill solves the challenge of gathering comprehensive, cited, and synthesized information from the internet without the limitations of standard chat-based browsing or the need for manual search and scraping.
Use the pi-research skill to perform a deep-dive research report on the current state of solid-state battery technology for 2026.
High-intent search queries and answers about installing and using this skill.
You can automate web research by using a multi-agent engine that decomposes complex queries into subtasks for parallel investigation, ultimately synthesizing a cited Markdown report from public internet sources.
Multi-agent web scraping works by decomposing complex information gathering tasks into parallel subtasks, allowing multiple agents to investigate simultaneously and synthesize findings into a comprehensive, cited report.
Yes, you need Node.js and a configured LLM provider to drive the research engine and handle the web scraping operations required for multi-agent web research and synthesis.
Yes, you can query a local, searchable knowledge store database of previous research findings to provide instant, cost-free answers without needing to perform new web scraping operations.
The best way to perform trend analysis and technical fact-finding is using an automated multi-agent research engine that gathers comprehensive, cited, and synthesized information without the limitations of standard chat-based browsing.
You should avoid using an automated research agent if you lack Node.js or a configured LLM provider, as these are required dependencies to drive the research engine and handle web scraping operations.
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