researching-on-the-internet

Research

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

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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

Do not use nested subagents. If you are running as a research subagent, perform the research directly with web/search/fetch tools already available to you. Do not dispatch or invoke additional subagents.

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

Hypothesis Testing

When given a hypothesis to test:

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

Example:

Hypothesis: "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

Task	Strategy
API docs	Official docs → GitHub README → Recent tutorials
Library comparison	Official sites → npm/PyPI stats → GitHub activity
Best practices	Official guides → Recent posts → Stack Overflow
Troubleshooting	Error search → GitHub issues → Stack Overflow
Current state	Release notes → Changelog → Recent announcements
Hypothesis testing	Define claims → Search both sides → Weight evidence

Source Evaluation Tiers

Tier	Sources	Usage
1 - Most reliable	Official docs, release notes, changelogs	Primary evidence
2 - Generally reliable	Verified tutorials, maintained examples, reputable blogs	Supporting evidence
3 - Use with caution	Stack Overflow, forums, old tutorials	Check dates, cross-verify

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

Mistake	Fix
Searching only one source	Cross-reference minimum 2-3 sources
Ignoring publication dates	Check dates, flag outdated information
Treating all sources equally	Use tier system, weight accordingly
Reporting before verification	Verify claims across sources first
Vague hypothesis testing	Break into specific falsifiable claims
Skipping official docs	Always start with tier 1 sources
Over-confident with single source	Note source tier and look for consensus