O que ai-knowledge-base faz?
Projeto de automação de base de conhecimento de IA: inclui OpenCode, Sub-Agent, Skill, Pipeline, MCP e coleta agendada com GitHub Actions.
Projeto de automação de base de conhecimento de IA: inclui OpenCode, Sub-Agent, Skill, Pipeline, MCP e coleta agendada com GitHub Actions.
Este projeto, `insistgang/ai-knowledge-base`, é uma base de conhecimento de IA automatizada que agrega e organiza informações utilizando várias ferramentas e frameworks do ecossistema de agentes de IA. Ele suporta OpenCode, Sub-Agent, Skill, Pipeline, MCP (Model Context Protocol) e coleta agendada via GitHub Actions. O objetivo é fornecer um repositório centralizado e atualizado automaticamente de conhecimentos sobre agentes de IA, desenvolvimento de ferramentas e engenharia de software. Útil para desenvolvedores e entusiastas que desejam acompanhar as últimas práticas e recursos em automação de conhecimento com IA.
npx skills add insistgang/ai-knowledge-baseInstalled? Explore more Pesquisa e Análise de Dados skills: affaan-m/uspto-database, affaan-m/scholar-evaluation, affaan-m/literature-review · View all 6 →
Projeto de automação de base de conhecimento de IA: inclui OpenCode, Sub-Agent, Skill, Pipeline, MCP e coleta agendada com GitHub Actions.
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.