smithery/ed3dai

researching-on-the-internet

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

Installation

$ npx skills add smithery/ed3dai --skill researching-on-the-internet

Summary

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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More details

Agent compatibility

Declared targets from SKILL.md / docs. Unmarked agents are not listed — the skill may still install via the CLI.

Claude Code Declared
Cursor Not declared
Codex Not declared
GitHub Copilot Not declared
Windsurf Not declared
Gemini CLI Not declared
Cline Not declared
OpenCode Not declared

Skill metadata

Parsed from SKILL.md frontmatter.

Declared agents claude-code

Package contents

Files included with this skill beyond the listing page.

  • skill md SKILL.md 5,361 B
  • docs SUMMARY.md 332 B

History

  1. First recorded snapshot · 0 installs

SKILL.md

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.

  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:

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