research-methodology

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Best practices for systematic research, source evaluation, and evidence gathering

AI & Automation 859 stars 98 forks Updated yesterday MIT

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# Research Methodology Guide ## Search Strategy ### Phase 1: Broad Discovery - Start with general queries to understand the landscape - Use different phrasings for the same concept - Note key terminology, authors, and organizations ### Phase 2: Focused Deep-Dive - Search for specific claims, statistics, or technical details - Target authoritative sources identified in Phase 1 - Use exact phrases in quotes for precision ### Phase 3: Verification - Cross-reference key claims across multiple sources - Search for counter-arguments or contradictions - Check publication dates for recency ## Source Evaluation ### Reliability Hierarchy 1. **Academic papers** (peer-reviewed journals, arXiv preprints) 2. **Official documentation** (government, organization, project docs) 3. **Reputable news** (established outlets with editorial standards) 4. **Expert blog posts** (known authors with credentials) 5. **Community forums** (Stack Overflow, Reddit — use cautiously) ### Evaluation Checklist - **Authority**: Who wrote it? What are their credentials? - **Currency**: When was it published? Is it still relevant? - **Coverage**: Does it address the topic comprehensively? - **Accuracy**: Can claims be verified elsewhere? - **Objectivity**: Is there obvious bias or commercial interest? ## Note-Taking Best Practices ### Structure Each Note File ```markdown # [Sub-topic Title] ## Key Findings - Finding 1 [SOURCE: url, accessed YYYY-MM-DD] [HIGH confidence] - Finding 2 [SOURCE: url, accessed...

Details

Author
vstorm-co
Repository
vstorm-co/pydantic-deepagents
Created
6 months ago
Last Updated
yesterday
Language
Python
License
MIT

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