Agent Skills Hub

querying-json

Efficiently extract, filter, and transform specific fields from JSON files using jq, saving up to 95% of context window usage compared to reading full files.

qmd

Local hybrid search engine for markdown notes, documentation, and codebase knowledge bases to reduce token consumption and improve retrieval efficiency.

autoresearch

Autonomous multi-team codebase improvement agent with specialized modes: narrow (goal-directed), broad (hypothesis-divergent), and sweep (quality-focused).

file-search

Search codebases efficiently using ripgrep for lightning-fast text patterns and ast-grep for precise, syntax-aware structural code analysis.

java-dev

Standardized Java development guidelines including naming conventions, exception handling, Spring Boot best practices, and concurrency patterns.

memory-systems

Guides agent memory system implementation, compares frameworks (Mem0, Zep, Letta, LangMem, Cognee), and designs persistence architectures for cross-session knowledge retention.

maishou

Real-time e-commerce price comparison and coupon hunting across major Chinese platforms like Taobao, JD, Pinduoduo, and more.

database-driver-design

Expert guidance for building production-ready Swift database client libraries, covering wire protocols, connection pooling, state machines, and NIO integration.

code-search-selector

Intelligent tool selector for code search. Routes queries between semantic (claudemem) and native tools (Grep/Glob) to optimize efficiency, token usage, and search accuracy.

newebpay-query

Implements NewebPay QueryTradeInfo API for transaction status verification, order tracking, and payment reconciliation in Taiwan e-commerce systems.

upstash-vector-db-skills

Upstash Vector DB setup, semantic search, namespaces, and embedding models. Ideal for building high-performance vector search features in Next.js 16/Vercel projects.

yq

Extract specific fields from YAML files efficiently without reading entire files, saving 80-95% of context window usage.