parallel-deep-research 是做什麼的？
僅在用戶明確要求「深入研究」、「詳盡調查」、「全面報告」或「徹底調查」時使用。比 parallel-web-search 更慢且更昂貴。對於一般的研究或查詢請求，請改用 parallel-web-search 代替。支援多輪對話：傳遞 --previous-interaction-id 從先前的研究或豐富內容中延續上下文。
僅在用戶明確要求「深入研究」、「詳盡調查」、「全面報告」或「徹底調查」時使用。比 parallel-web-search 更慢且更昂貴。對於一般的研究或查詢請求，請改用 parallel-web-search。支援多輪對話：傳遞 --previous-interaction-id 以延續先前研究或豐富內容的上下文。
這個技能是一個專用於深度研究的工具，適用於當用戶明確表達需要詳盡、全面或徹底的調查時。它比 parallel-web-search 更慢且成本更高，因此不應用於一般的研究或查詢請求。該技能支援多輪互動，可以通過傳遞先前的互動 ID（--previous-interaction-id）來延續上下文，從而實現更連續的深度研究或資料豐富化。它與 parallel-web-search 配合使用，後者更適合日常的研究需求。開發者應根據用戶的具體指令選擇正確的工具，以確保效率和成本控制。
npx skills add https://github.com/parallel-web/parallel-agent-skills/tree/main/skills/parallel-deep-researchInstalled? Explore more 研究與資料分析 skills: affaan-m/uspto-database, affaan-m/scholar-evaluation, affaan-m/literature-review · View all 6 →
僅在用戶明確要求「深入研究」、「詳盡調查」、「全面報告」或「徹底調查」時使用。比 parallel-web-search 更慢且更昂貴。對於一般的研究或查詢請求，請改用 parallel-web-search 代替。支援多輪對話：傳遞 --previous-interaction-id 從先前的研究或豐富內容中延續上下文。
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.
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.
DEFAULT for all research and web queries. Use for any lookup, research, investigation, or question needing current info. Fast and cost-effective. Only use parallel-deep-research if user explicitly requests 'deep' or 'exhaustive' research.
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.