---

name: researching-on-the-internet description: Use when planning features and need current API docs, library patterns, or external knowledge; when testing hypotheses about technology choices or claims; when verifying assumptions before design decisions - gathers well-sourced, current information from the internet to inform technical decisions

Researching on the Internet

Overview

Gather accurate, current, well-sourced information from the internet to inform planning and design decisions. Test hypotheses, verify claims, and find authoritative sources for APIs, libraries, and best practices.

When to Use

Use for:

• Finding current API documentation before integration design
• Testing hypotheses ("Is library X faster than Y?", "Does approach Z work with version N?")
• Verifying technical claims or assumptions
• Researching library comparison and alternatives
• Finding best practices and current community consensus

Don't use for:

• Information already in codebase (use codebase search)
• General knowledge within Claude's training (just answer directly)
• Project-specific conventions (check CLAUDE.md)

Core Research Workflow

1. Define question clearly - specific beats vague
2. Search official sources first - docs, release notes, changelogs
3. Cross-reference - verify claims across multiple sources
4. Evaluate quality - tier sources (official → verified → community)
5. Report concisely - lead with answer, provide links and evidence

Hypothesis Testing

When given a hypothesis to test:

1. Identify falsifiable claims - break hypothesis into testable parts
2. Search for supporting evidence - what confirms this?
3. Search for disproving evidence - what contradicts this?
4. Evaluate source quality - weight evidence by tier
5. Report findings - supported/contradicted/inconclusive with evidence
6. Note confidence level - strong consensus vs single source vs conflicting info

Example:

CopyHypothesis: "Library X is faster than Y for large datasets"

Search for:
✓ Benchmarks comparing X and Y
✓ Performance documentation for both
✓ GitHub issues mentioning performance
✓ Real-world case studies

Report:
- Supported: [evidence with links]
- Contradicted: [evidence with links]
- Conclusion: [supported/contradicted/mixed] with [confidence level]

Quick Reference

Source Evaluation Tiers

Always note source tier in findings.

Search Strategies

Multiple approaches:

• WebSearch for overview and current information
• WebFetch for specific documentation pages
• Check MCP servers (Context7, search tools) if available
• Follow links to authoritative sources
• Search official documentation before community resources

Cross-reference:

• Verify claims across multiple sources
• Check publication dates - prefer recent
• Flag breaking changes or deprecations
• Note when information might be outdated
• Distinguish stable APIs from experimental features

Reporting Findings

Lead with answer:

• Direct answer to question first
• Supporting details with source links second
• Code examples when relevant (with attribution)

Include metadata:

• Version numbers and compatibility requirements
• Publication dates for time-sensitive topics
• Security considerations or best practices
• Common gotchas or migration issues
• Confidence level based on source consensus

Handle uncertainty clearly:

• "No official documentation found for [topic]" is valid
• Explain what you searched and where you looked
• Distinguish "doesn't exist" from "couldn't find reliable information"
• Present what you found with appropriate caveats
• Suggest alternative search terms or approaches

Common Mistakes