Utilize apenas quando o usuário disser explicitamente 'pesquisa profunda', 'exaustivo', 'relatório abrangente' ou 'investigação minuciosa'. Mais lento e caro que a busca web paralela. Para solicitações normais de pesquisa/consulta, use parallel-web-search. Suporta multi-turn: passe --previous-interaction-id de uma pesquisa ou enriquecimento anterior para continuar com contexto.
A skill parallel-web/parallel-deep-research é uma ferramenta especializada para realizar pesquisas profundas e exaustivas na web, indicada apenas quando o usuário solicita explicitamente investigações minuciosas ou relatórios abrangentes. Ela é mais lenta e consome mais recursos do que a alternativa parallel-web-search, que deve ser usada para consultas comuns de pesquisa ou verificação rápida. O principal diferencial desta skill é o suporte a múltiplas interações (multi-turn): você pode passar o parâmetro `--previous-interaction-id` com o ID de uma interação anterior (como uma pesquisa ou enriquecimento) e continuar a investigação com contexto acumulado. Isso permite que o agente refine e aprofunde gradualmente linhas de investigação, ideal para tarefas que exigem cobertura completa e iterativa de tópicos complexos. A skill é compatível com plataformas como Claude Code, Cursor e Codex, seguindo o padrão de ferramentas de pesquisa paralela do ecossistema.
npx skills add https://github.com/parallel-web/parallel-agent-skills/tree/main/skills/parallel-deep-researchInstalled? Explore more Pesquisa e Análise de Dados skills: affaan-m/uspto-database, affaan-m/scholar-evaluation, affaan-m/literature-review · View all 6 →
Use APENAS quando o usuário disser explicitamente 'pesquisa profunda', 'exaustivo', 'relatório abrangente' ou 'investigação minuciosa'. Mais lento e caro que parallel-web-search. Para solicitações normais de pesquisa/consulta, use parallel-web-search. Suporta multi-turn: passe --previous-interaction-id de uma pesquisa ou enriquecimento anterior para continuar com contexto.
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.