Claude-skill-registry keep-current

Research current online documentation and information. Use when working with external libraries, frameworks, APIs, services, version-specific issues, trends, or any topic where LLM training cutoff may impact accuracy. Guides when to use websearch, codesearch, or webfetch.

install
source · Clone the upstream repo
git clone https://github.com/majiayu000/claude-skill-registry
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/majiayu000/claude-skill-registry "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/data/keep-current" ~/.claude/skills/majiayu000-claude-skill-registry-keep-current && rm -rf "$T"
manifest: skills/data/keep-current/SKILL.md
source content

Keep Current

Ensure responses are accurate and up-to-date by doing targeted research (use helper agents when available) before answering.

When to Research

Research when working with:

  • External dependencies: Libraries, frameworks, languages, SDKs
  • External services: APIs, SaaS products (WorkOS, Stripe, morphllm, etc.)
  • Version-specific topics: Migration guides, breaking changes, version compatibility
  • Time-sensitive topics: Recent developments, trends, "latest" features, deprecations
  • Uncertain knowledge: When not confident in the recency of your answer

What NOT to Research

Skip research for:

  • Language basics: Syntax, core operators, standard data structures
  • Stable APIs: Well-established features that rarely change
  • Universal concepts: Programming patterns, algorithms, design principles
  • Confident knowledge: When certain the answer is in your knowledge base and unchanged
  • General knowledge: Topics that don't depend on recent changes

Rule of thumb: If it's core programming knowledge that hasn't changed in years, don't research it.

Research Assistance

When research is needed, use available research assistance (for example, a general-purpose research agent) to gather up-to-date information:

Provide Context

Include in your prompt:

  • The research question: What specific information is needed
  • Context: What you're building, version requirements, language/framework
  • Scope: Level of detail needed (high-level overview vs deep dive)
  • Constraints: Any specific requirements or limitations

Emphasize Thoroughness

The subagent must:

  • Continue researching until it has a complete, confident understanding
  • Explore multiple sources (official docs, community discussions, examples)
  • Verify information across sources
  • Not return until it has thoroughly researched the topic
  • Provide distilled findings with source URLs

Example Prompt

I need to integrate WorkOS for authentication in a Next.js app.
Research the current WorkOS documentation to understand:
- Integration setup and configuration
- SDK usage and code examples
- Authentication flow implementation
- Common patterns and best practices

Thoroughly research this topic. Do not return until you have a complete understanding of how to integrate WorkOS based on current documentation. Provide distilled findings with source URLs.

Using Subagent Results

  • The subagent returns distilled, synthesized information
  • Apply findings to the user's request
  • Reference sources when appropriate
  • If findings are insufficient, ask for more specific research