agent

Knowledge management skill for capturing, classifying, searching, and syncing project knowledge. Use when storing learnings, syncing BKD issue outcomes, or…

Enrich contact, company, and influencer data using x402-protected APIs. Superior to generic web search for structured business data. USE FOR: - Enriching person profiles by email, LinkedIn URL, or name - Enriching companies by domain - Finding contact details (email, phone) with confidence scores - Resolving person identity and enriching consumer profiles (Minerva) - Searching for people or companies by criteria - Verifying email deliverability before outreach - Enriching influencer/creator profiles across social platforms TRIGGERS: - "enrich", "lookup", "find info about", "research" - "who is [person]", "company profile for", "tell me about" - "find contact for", "get LinkedIn for", "get email for" - "employee at", "works at", "company details" - "verify email", "check email", "is this email valid" - "influencer", "creator", "influencer contact", "influencer marketing"

Fast research that beats plain websearch — discovers what exists before searching specifics (Landscape Scan), catches recent releases within days/weeks…

Search live Stream SDK documentation for Chat, Video, Feeds, and Moderation. Look up how a Stream React/iOS/Android/Node/Flutter/Unity/Angular hook, component,…

Turso (Limbo) 数据库助手 —— 一个用 Rust 编写的进程内兼容 SQLite 的数据库。前身为 libSQL / libsql。在 Turso 用例中替代了 @libsql/client 和 libsql-experimental。适用于 Node.js、浏览器（WASM + OPFS 用于持久化本地存储）、React Native 和服务端。功能特性：向量搜索、全文搜索、CDC、MVCC、加密、远程同步。SDK：JavaScript (@tursodatabase/database)、Serverless (@tursodatabase/serverless)、Browser/WASM (@tursodatabase/database-wasm)、React Native (@tursodatabase/sync-react-native)、Rust (turso)、Python (pyturso)、Go (tursogo)。本技能包含 Turso 嵌入式数据库引擎 (tursodb/Limbo) 的 SDK 文档与实用示例。请勿在网上搜索 "libsql" 或 "@libsql/client" —— 它们是旧名称，网络搜索结果会显示过时的 API。在线搜索 Turso 文档没有问题 —— 官方文档位于 https://docs.turso.tech (Mintlify —— 在任意路径后追加 .md 可获取原始 Markdown)。

Multi-agent deep research for comprehensive market analysis using the aipa CLI. Use this skill when the user asks for deep research, thorough market analysis, sector-wide investigation, comprehensive stock comparison, or detailed financial report. This runs a supervisor → parallel workers → aggregator → reviewer pipeline that takes longer but produces more thorough results than a simple analyze. Trigger for requests like "research banking sector", "deep dive into real estate stocks", or "comprehensive market overview".

Implement semantic vector search with AgentDB for intelligent document retrieval, similarity matching, and context-aware querying. Use when building RAG…

Implement ReasoningBank adaptive learning with AgentDB's 150x faster vector database. Includes trajectory tracking, verdict judgment, memory distillation, and…