web-researcher

Name: web-researcher
Availability: InStock
Author: kit4some

Launch parallel research agents to search and deduplicate web results.

4|Updated Mar 21, 2026

Search Tags:#automation #memory #parallel #web-research #knowledge-graph #topic-analysis

Ready to run

npx skills add https://github.com/Kit4Some/Oh-my-ClaudeClaw --skill web-researcher-kit4some

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: web-researcher
Source: https://github.com/Kit4Some/Oh-my-ClaudeClaw/tree/main/skills/web-researcher
Command: npx skills add https://github.com/Kit4Some/Oh-my-ClaudeClaw --skill web-researcher-kit4some

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Web research is time-consuming and fragmented. This Skill enables parallel, structured web research with memory integration to accelerate knowledge gathering and maintain context across tasks.

Core Features & Use Cases

Parallel research across multiple queries and angles
Memory-driven knowledge graph linking and deduplication
Guided workflow for sourcing, validating, and structuring findings
Use case: When investigating a topic, trigger parallel agents to gather diverse perspectives, then synthesize insights into a connected knowledge graph.

Quick Start

Trigger web research on a topic to start parallel searches and store results in memory.

Frequently Asked Questions about web-researcher

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I automate parallel web research for topic deep-dives?▼

Automate parallel web research by launching multiple research agents to perform multi-angle searches and deduplicate results. This systematic approach gathers diverse perspectives on a topic and synthesizes findings into a connected knowledge graph.

What is a knowledge graph and how does it structure web research findings?▼

A knowledge graph structures web research findings by linking deduplicated results into a connected network. Memory-driven integration maintains context across tasks, accelerating knowledge gathering and ensuring findings are mapped systematically.

Can I use memory integration to maintain context across multiple research tasks?▼

Memory integration allows you to maintain context across multiple research tasks by linking and deduplicating findings within a knowledge graph. This memory access ensures that previous research context informs and enriches current topic analysis.

Does this web research approach apply to market intelligence and trend analysis?▼

This parallel web research approach applies directly to market intelligence and trend analysis. By triggering parallel agents to gather diverse perspectives, it systematically sources, validates, and structures findings for comprehensive intelligence gathering.

What are the limitations of using multi-agent orchestration for web research?▼

Multi-agent orchestration for web research requires memory access and guardrails to ensure freshness, relevance, and safe proactive behavior. Without these guardrails, parallel agents may return redundant, outdated, or irrelevant search results.

Do I need memory access to run parallel research agents for topic analysis?▼

Memory access is required to run parallel research agents effectively for topic analysis. It enables memory-driven knowledge graph linking and deduplication, ensuring that gathered insights maintain context and connect systematically across tasks.