research-free
APIキー不要の統合リサーチスキル。Claude Code組み込みのWebSearch/WebFetchを使用。他人に配布してもそのまま使える。
Best use case
research-free is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
APIキー不要の統合リサーチスキル。Claude Code組み込みのWebSearch/WebFetchを使用。他人に配布してもそのまま使える。
Teams using research-free should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/research-free/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How research-free Compares
| Feature / Agent | research-free | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
APIキー不要の統合リサーチスキル。Claude Code組み込みのWebSearch/WebFetchを使用。他人に配布してもそのまま使える。
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
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SKILL.md Source
# research-free - APIキー不要リサーチシステム ## 概要 **APIキー設定なし**で使えるリサーチスキル。Claude Code組み込みのWebSearch/WebFetchのみを使用。 ``` ┌─────────────────────────────────────────────────────────────────────┐ │ RESEARCH-FREE (APIキー不要) │ ├─────────────────────────────────────────────────────────────────────┤ │ │ │ ┌─────────────────────────────────────────────────────────────┐ │ │ │ Claude Code 組み込みツール（APIキー不要） │ │ │ │ │ │ │ │ ┌─────────────┐ ┌─────────────┐ │ │ │ │ │ WebSearch │ │ WebFetch │ │ │ │ │ │ (Anthropic) │ │ (直接取得) │ │ │ │ │ └──────┬──────┘ └──────┬──────┘ │ │ │ │ │ │ │ │ │ │ └──────────┬───────────┘ │ │ │ │ ▼ │ │ │ │ ┌─────────────────┐ │ │ │ │ │ 統合・分析 │ │ │ │ │ └────────┬────────┘ │ │ │ │ ▼ │ │ │ │ ┌─────────────────┐ │ │ │ │ │ レポート出力 │ │ │ │ │ └─────────────────┘ │ │ │ └─────────────────────────────────────────────────────────────┘ │ │ │ │ ✅ インストール後すぐに使える │ │ ✅ APIキー設定不要 │ │ ✅ 他人に配布してもそのまま動作 │ └─────────────────────────────────────────────────────────────────────┘ ``` ## 使い方 ```bash # 基本リサーチ /research-free AIエージェントの最新動向 # クイック検索（5件程度） /research-free Next.js 15 新機能 --depth=quick # 標準リサーチ（10-15件） /research-free 生成AI市場 --depth=standard # 深層リサーチ（20件以上） /research-free 量子コンピューティング投資 --depth=deep ``` ## 実行フロー ### 1. WebSearch で情報収集 ``` WebSearch(query="トピック + 最新") WebSearch(query="トピック + とは") WebSearch(query="トピック + 比較") WebSearch(query="トピック + メリット デメリット") ``` ### 2. 重要URLをWebFetchで詳細取得 ``` WebFetch(url="重要そうなURL", prompt="要点を抽出") ``` ### 3. 統合・分析 - 複数ソースからの情報をクロスチェック - 矛盾点を特定 - 信頼度を評価 ### 4. レポート出力 ```markdown # [トピック] 調査レポート ## 要約 - ポイント1 - ポイント2 ## 主要な発見 ### 発見1 [内容] **出典**: [URL] ## 出典一覧 1. [タイトル](URL) ``` ## 深度別の検索パターン ### quick（5件程度） ``` 1. "[トピック] 2026" → 最新情報 2. "[トピック] とは" → 基本情報 ``` ### standard（10-15件） ``` 1. "[トピック] 2026 最新" 2. "[トピック] とは わかりやすく" 3. "[トピック] メリット デメリット" 4. "[トピック] 比較" 5. "[トピック] 始め方" ``` ### deep（20件以上） ``` 1-5. standard の検索 6. "[トピック] 事例" 7. "[トピック] 失敗" 8. "[トピック] 成功" 9. "[トピック] 注意点" 10. "[トピック] 将来性" 11. "[トピック] 市場規模" 12. "[トピック] 競合" + 重要URLのWebFetch詳細取得 ``` ## API版との比較 | 機能 | research-free | mega-research (API版) | |------|--------------|----------------------| | **APIキー** | 不要 ✅ | 必要 | | **配布時** | そのまま動作 ✅ | 設定必要 | | **検索精度** | 良好 | 高精度 | | **検索速度** | 標準 | 高速（並列） | | **ニュース** | WebSearch経由 | NewsAPI直接 | | **コミュニティ** | WebSearch経由 | Reddit API直接 | | **AI要約** | Claude分析 | Perplexity | ## 制限事項 1. **レート制限**: WebSearchは連続使用で制限される場合あり 2. **リアルタイム性**: ニュースAPIほどのリアルタイム性はない 3. **構造化データ**: SerpAPIのような構造化結果は得られない ## ベストプラクティス 1. **具体的なクエリ** - ❌ "AI" - ✅ "2026年 AIエージェント 市場動向" 2. **年を含める** - 最新情報が必要な場合は「2026」を追加 3. **複数の観点** - 「メリット」「デメリット」「比較」など複数視点で検索 ## 出力ディレクトリ ``` research/runs/<timestamp>__<slug>/ ├── input.yaml # 入力パラメータ ├── evidence.jsonl # 収集した証拠 ├── report.md # 最終レポート └── sources.json # ソース一覧 ``` ## 関連スキル - `keyword-free` - APIキー不要キーワード抽出 - `mega-research` - API版（高精度） - `gpt-researcher` - 自律型深層リサーチ（要API）
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