autonomous-research_skill

Overview

This skill performs end-to-end autonomous research: it finds sources, evaluates credibility, synthesizes evidence, and produces structured, citation-backed reports without human direction. It combines source management, analytical frameworks, and report generation to deliver actionable insights and validated conclusions.

How this skill works

You provide a topic or objective and the skill defines scope, locates primary and secondary sources, and extracts key data points. It cross-references findings, applies analysis frameworks (SWOT, trend analysis, comparative), and generates a clear report with citations, recommendations, and identified gaps. Validation steps verify accuracy, highlight uncertainties, and update results when new information appears.

When to use it

• Deep dives on unfamiliar or complex topics where you need comprehensive coverage
• Gathering and validating evidence to support decisions, strategies, or policy
• Preparing executive briefs, whitepapers, or academic-style reports without manual curation
• Comparing technologies, vendors, or approaches with structured analysis
• Tracking trends and forecasting developments in fast-moving fields

Best practices

• Start with a clear research question and defined scope to limit noise
• Use diverse source types: peer-reviewed, industry reports, primary data, and expert commentary
• Cross-reference claims across multiple independent sources before trusting them
• Document all sources and methods for reproducibility and future updates
• Flag uncertainty and assumptions; include confidence levels for key findings

Example use cases

• Generate a market analysis and go-to-market recommendations for an AI product
• Produce a comparative report on autonomous agent platforms with pros/cons
• Synthesize academic and industry literature on LLM reasoning capabilities
• Create an executive brief on AI safety risks and recommended mitigation steps
• Validate an internal research memo by cross-checking cited evidence and gaps