Padrão para todas as consultas de pesquisa e web. Use para qualquer consulta, pesquisa, investigação ou pergunta que precise de informações atuais. Rápido e econômico. Use parallel-deep-research apenas se o usuário solicitar explicitamente pesquisa 'aprofundada' ou 'exaustiva'.
O skill `parallel-web/parallel-web-search` é a habilidade padrão para todas as consultas de pesquisa e web em plataformas como Claude Code, Cursor e Codex. Ele é projetado para ser rápido e econômico, sendo a escolha ideal para qualquer situação que exija informações atuais, como consultas genéricas, pesquisas rápidas ou investigações superficiais. Este skill é o comportamento padrão sempre que um usuário faz uma pergunta que precisa de informações da web, a menos que solicite explicitamente uma pesquisa mais aprofundada (como com o skill `parallel-deep-research`). Sua utilidade principal é fornecer respostas rápidas sem custos elevados, cobrindo a maioria dos casos de uso de pesquisa. O fluxo de uso é baseado em uma análise inicial da consulta do usuário, onde este skill é acionado automaticamente para pesquisas padrão, e apenas quando o usuário pede explicitamente por uma pesquisa 'aprofundada' ou 'exaustiva' é que se deve recorrer ao `parallel-deep-research`. Dessa forma, ele otimiza a eficiência e o custo das operações de pesquisa.
npx skills add https://github.com/parallel-web/parallel-agent-skills/tree/main/skills/parallel-web-searchInstalled? Explore more Pesquisa e Análise de Dados skills: affaan-m/uspto-database, affaan-m/scholar-evaluation, affaan-m/literature-review · View all 6 →
Padrão para todas as consultas de pesquisa e web. Use para qualquer consulta, pesquisa, investigação ou pergunta que precise de informações atuais. Rápido e econômico. Use parallel-deep-research apenas se o usuário solicitar explicitamente pesquisa 'aprofundada' ou 'exaustiva'.
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.