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skills/web_search_brainstorm.md
dan f3d7c5bc2d docs: resolve web search design questions 
Context changed - Claude Code now has built-in WebSearch/WebFetch.

Decisions:
- Keep two separate skills (web-search, web-research)
- web-search: OpenCode only (Claude Code has native search)
- web-research: Both (deep research beyond built-in capability)
- Source filtering via WebSearch allowed_domains, not skill feature
- Summaries by default, not raw links

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2025-12-28 22:21:05 -05:00

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Brainstorming: Advanced Web Search Skill

Objective

Create a versatile web search skill that supports multiple search modes, providers, and use cases.

Potential Search Modes

1. General Search

  • Goal: Find general information, answers to questions.
  • Tools: claude -p (existing), googler, ddgr.
  • Features: Summaries, top N results.

2. Documentation Search

  • Goal: Find specific technical documentation.
  • Target: MDN, Python Docs, Rust Docs, NixOS Wiki.
  • Strategy: Restrict search to specific domains (site:docs.python.org).

3. Code Search

  • Goal: Find code snippets, libraries, or usage examples.
  • Target: GitHub, GitLab, StackOverflow.
  • Tools: GitHub CLI (gh), specialized code search APIs.

4. Package Search

  • Goal: Find packages and versions.
  • Target: NixOS Packages, PyPI, NPM, Crates.io.
  • Tools: nix-search (if available), pip search (deprecated, need alternative), npm search.

5. Deep Research / Investigation

  • Goal: Thoroughly investigate a topic by following links.
  • Strategy: Recursive search or multi-step agentic workflow (search -> read -> search).

Implementation Options

Option A: Enhanced claude -p Wrapper

  • Expand the existing web-search skill.
  • Add flags: --docs, --code, --package.
  • Modify the prompt sent to Claude to guide its search behavior.
  • Pros: Uses existing powerful agent.
  • Cons: Dependent on Claude's tools and context window.

Option B: Direct CLI Tools

  • Use tools like googler or ddgr directly for faster, raw results.
  • Pros: Fast, lightweight, structured output (JSON).
  • Cons: Requires installing extra tools, raw output might need parsing.

Option C: Hybrid Approach

  • Use CLI tools for discovery (getting URLs).
  • Use claude or curl + readability for content extraction.

Questions for User

  • Do you prefer a single "smart" skill that figures out what to do, or explicit flags/subcommands?
  • Are there specific sources you search often (e.g., NixOS packages)?
  • Do you want raw links or summarized answers?

Resolution (2025-12-28)

Context changed: Claude Code now has built-in WebSearch and WebFetch tools.

Decisions:

  1. Single smart skill vs flags? Keep two separate skills:

    • web-search: Quick searches (for OpenCode which lacks built-in search)
    • web-research: Deep research with structured reports (valuable for both)

  2. Specific sources priority? Not needed as skill feature.

    • WebSearch has allowed_domains parameter
    • User says "search nixos wiki for X" and agent uses domain filtering

  3. Raw links vs summaries? Summaries by default (current behavior).

    • Raw links without context are less useful
    • Agent synthesizes information

Deployment:

  • web-search: OpenCode only (Claude Code has native WebSearch)
  • web-research: Both (deep research with backends beyond built-in capability)

Status: Questions resolved, no changes needed to skills.