Busca múltiples fuentes web, sintetiza los hallazgos y produce informes de investigación citados mediante subagentes delegados.
Esta habilidad permite a un agente de IA realizar investigaciones web complejas de manera automatizada. Al recibir una solicitud del usuario para investigar un tema en línea, buscar información actual o comparar opciones, el agente despliega subagentes delegados que buscan en múltiples fuentes web, extraen datos relevantes y los sintetizan en un informe de investigación coherente y citado. Es útil para tareas que requieren información actualizada o análisis comparativo, como investigar tendencias, encontrar datos específicos o generar resúmenes basados en fuentes diversas. Soporta plataformas como Claude Code, Cursor y Codex, y su funcionamiento se basa en la ejecución de consultas web paralelas y la consolidación de resultados en un formato estructurado con referencias.
npx skills add https://github.com/langchain-ai/deepagents/tree/main/skills/web-researchInstalled? Explore more Investigación y análisis de datos skills: affaan-m/uspto-database, affaan-m/scholar-evaluation, affaan-m/literature-review · View all 6 →
Busca múltiples fuentes web, sintetiza los hallazgos y produce informes de investigación citados mediante subagentes delegados. Úsalo cuando el usuario solicite investigar un tema en línea, buscar en la web, consultar algo, encontrar información actual, comparar opciones o producir un informe de investigación.
This repo contains 4 individual skills — each has its own dedicated page.
Searches arXiv for preprints and academic papers, retrieves abstracts, and filters by topic. Use when the user asks to find research papers, search arXiv, look up preprints, find academic articles in physics, math, CS, biology, statistics, or related fields.
Writes and structures long-form blog posts, creates tutorial outlines, and optimizes content for SEO with cover image generation. Use when the user asks to write a blog post, article, how-to guide, tutorial, technical writeup, thought leadership piece, or long-form content.
Fetches and references LangGraph Python documentation to build stateful agents, create multi-agent workflows, and implement human-in-the-loop patterns. Use when the user asks about LangGraph, graph agents, state machines, agent orchestration, LangGraph API, or needs LangGraph implementation guidance.
Drafts engaging social media posts, writes hooks, suggests hashtags, creates thread structures, and generates companion images. Use when the user asks to write a LinkedIn post, tweet, Twitter/X thread, social media caption, social post, or repurpose content for social platforms.
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.