How does the Parallel Research skill work?

It spawns five independent sub-agents that simultaneously investigate technical specs, ecosystem tools, expert patterns, pitfalls, and implementation paths, then synthesizes their findings into one structured report.

Where are the research findings stored during the process?

Temporary findings are saved in a local .research/ directory during the investigation phase and are automatically cleaned up once the final synthesis is generated.

Can I specify the research topic via command line?

Yes, you can provide the topic directly as an argument (e.g., 'research TypeScript performance') or simply run the command and provide the topic when prompted.

Does this skill use multiple model invocations?

Yes, by spawning parallel sub-agents, it performs multiple concurrent invocations to provide a more comprehensive and faster analysis than a single linear prompt could achieve.

Parallel Research

Name: Parallel Research
Author: potenlab

bypotenlab

0•

生産性とワークフロー

Conducts multi-dimensional research using parallel sub-agents to synthesize technical insights and implementation paths.

The Research skill accelerates technical decision-making by deploying five specialized sub-agents to investigate any topic across technical, ecosystem, architectural, and practical dimensions simultaneously. It automates the complex process of gathering expert patterns, identifying common pitfalls, and recommending a clear path forward, ultimately consolidating diverse findings into a single, actionable report with confidence scores for every insight.

主な機能

01Automatic synthesis of findings to resolve cross-dimensional contradictions

02Structured analysis across technical, ecosystem, and pattern dimensions

03Confidence-graded insights for reliable technical decision making

04Multi-agent parallel execution for rapid data gathering

05Actionable recommendations with specific next steps and source tracking

060 GitHub stars

ユースケース

01Conducting deep-dive analysis on complex technical pitfalls and gotchas

02Evaluating new libraries or frameworks before project adoption

03Investigating architectural patterns for specific technical challenges

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add potenlab/marketplace-potenlab research

For use in Claude.ai and ChatGPT

主な機能

01Automatic synthesis of findings to resolve cross-dimensional contradictions

02Structured analysis across technical, ecosystem, and pattern dimensions

03Confidence-graded insights for reliable technical decision making

04Multi-agent parallel execution for rapid data gathering

05Actionable recommendations with specific next steps and source tracking

060 GitHub stars

ユースケース

01Conducting deep-dive analysis on complex technical pitfalls and gotchas

02Evaluating new libraries or frameworks before project adoption

03Investigating architectural patterns for specific technical challenges

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add potenlab/marketplace-potenlab research

For use in Claude.ai and ChatGPT