parallel-web-search は何をしますか？
あらゆる調査やWebクエリのデフォルト。最新情報が必要な検索、調査、質問に使用。高速かつコスト効率が良い。ユーザーが明示的に「深い」または「徹底的な」調査を要求した場合のみ、parallel-deep-research を使用すること。
あらゆる調査やWebクエリのデフォルト。最新情報が必要な検索、調査、質問に使用。高速かつコスト効率が良い。
このスキルは、一般的なWeb検索と調査のためのデフォルトツールです。ユーザーが現在の情報を必要とするあらゆるクエリ（ルックアップ、調査、質問など）に対して、高速かつ低コストで動作するよう設計されています。主にClaude CodeやCursor、CodexなどのAIエージェントで使用されることを想定しており、WebブラウジングやAPI呼び出しを通じて信頼性の高いリアルタイム情報を取得します。このスキルは、タスクの大部分をカバーするように最適化されており、リソース消費を抑えながらも高品質な結果を返すことを重視しています。ユーザーが明示的に「深い」や「徹底的な」調査を要求した場合にのみ、別の専用スキル（parallel-deep-research）を使用するようガイドします。
npx skills add https://github.com/parallel-web/parallel-agent-skills/tree/main/skills/parallel-web-searchInstalled? Explore more 研究＆データ分析 skills: affaan-m/uspto-database, affaan-m/scholar-evaluation, affaan-m/literature-review · View all 6 →
あらゆる調査やWebクエリのデフォルト。最新情報が必要な検索、調査、質問に使用。高速かつコスト効率が良い。ユーザーが明示的に「深い」または「徹底的な」調査を要求した場合のみ、parallel-deep-research を使用すること。
This repo contains 8 individual skills — each has its own dedicated page.
Bulk data enrichment. Adds web-sourced fields (CEO names, funding, contact info) to lists of companies, people, or products. Use for enriching CSV files or inline data. Supports multi-turn: pass --previous-interaction-id from a prior research task to carry context forward.
ONLY use when user explicitly says 'deep research', 'exhaustive', 'comprehensive report', or 'thorough investigation'. Slower and more expensive than parallel-web-search. For normal research/lookup requests, use parallel-web-search instead. Supports multi-turn: pass --previous-interaction-id from a prior research or enrichment to continue with context.
Discover entities (companies, people, products, etc.) matching a natural-language description. Use when the user asks to 'find all X' or 'list every Y that…' — e.g., 'Find AI startups that raised Series A in 2026', 'List roofing companies in Charlotte NC', 'Show me YC W24 dev tools companies'. Different from web-search (which returns webpages) and deep-research (which returns a narrative report). Use this when the user wants a structured list of entities.
Continuously track the web for changes on a recurring cadence. Use when the user asks to 'monitor', 'track changes to', 'watch', or 'alert me when' something on the web changes — e.g., 'Track price changes for iPhone 16', 'Alert me when Tesla files a new 8-K', 'Monitor competitor pricing pages weekly'. Also use to list, inspect, update, or delete existing monitors.
URL content extraction. Use for fetching any URL - webpages, articles, PDFs, JavaScript-heavy sites. Token-efficient: runs in forked context. Prefer over built-in WebFetch.
Get completed research task result by run ID
Set up the Parallel plugin (install CLI)
Check running research task status by run ID
USPTO patent and trademark data workflow for official record lookup, PatentSearch queries, TSDR checks, assignment data, and reproducible IP research logs.
Structured scholarly-work evaluation for papers, proposals, literature reviews, methods sections, evidence quality, citation support, and research-writing feedback.
Systematic literature-review workflow for academic, biomedical, technical, and scientific topics, including search planning, source screening, synthesis, citation checks, and evidence logging.
The agent harness performance optimization system. Skills, instincts, memory, security, and research-first development for Claude Code, Codex, Opencode, Cursor and beyond.
Agent skill repository discovered by 10x-chat research.
Review backend code for quality, security, maintainability, and best practices based on established checklist rules. Use when the user requests a review, analysis, or improvement of backend files (e.g., `.py`) under the `api/` directory. Do NOT use for frontend files (e.g., `.tsx`, `.ts`, `.js`). Supports pending-change review, code snippets review, and file-focused review.