Skill UI

This skill builds a persistent knowledge base combining LLM wiki patterns with structured graphs. It ingests documents once to generate wiki pages and extract entities/relations, avoiding re-derivation. It supports agents with evidence-based querying, wiki search, and knowledge accumulation, ensuring cross-references are never lost.

This advanced playbook covers escalating prototype pollution into Remote Code Execution (RCE) and Cross-Site Scripting (XSS). It details exploitation techniques across various environments, including Node.js child_process, EJS, Pug, Handlebars, and client-side libraries like jQuery and Lodash. It is designed for security researchers and penetration testers to systematic locate and exploit deep merge sinks and framework gadgets.

This guide provides a comprehensive workflow for searching and retrieving biomedical literature from PubMed and NCBI. It covers advanced query construction using MeSH terms and specific field tags, advanced filtering (date, publication type), and a repeatable programmatic workflow using NCBI E-utilities (esearch, efetch). Essential for researchers conducting systematic reviews and literature monitoring.

This advanced skill acts as a hybrid router for complex research queries. It deterministically classifies the user's intent, delegating to specialized modules (e.g., funding grants, academic literature, patent search, company dossier) when applicable. If no specialist fits, it executes a robust fallback plan, synthesizing multi-source information into a detailed, cited briefing or document. Ideal for comprehensive investigative research across multiple domains.

A dedicated tool for querying Lark Meeting Notes (Notes) details and raw verbatim transcripts. It requires an explicit note_id to function, allowing users to determine the display type, access associated document tokens, and retrieve the original unified transcript. It strictly focuses on note-based retrieval and does not handle searching by title, document body, or meeting ID.

A powerful utility that queries multiple free APIs (Pexels, Pixabay, Internet Archive, etc.) in a single query. It retrieves normalized, license-tagged results for real-world, historical, or archival images, videos, and GIFs, making it a peer to local semantic search and generative media tools. Includes specialized scripts for fetching and judging audio.

This skill systematically researches real-time public sentiment and user opinions on any topic by querying Reddit, X/Twitter, and the broader web. It bypasses curated SEO content to provide a structured report detailing consensus points, recurring pain points, genuine praise, and signal confidence, offering actionable insights into current market sentiment.

This skill provides comprehensive, read-only access to the pkg.go.dev API using the `godig` tool. It allows users to query detailed information about Go packages and modules, including full documentation, API signatures, available versions, dependency graphs, and known security vulnerabilities. It is essential for researching the external Go ecosystem and comparing library metadata.

A comprehensive skill for interacting with Weaviate vector databases. It enables advanced operations including semantic search, hybrid keyword querying, schema inspection, data exploration, collection creation, and bulk data import (CSV, JSON, PDF). Use this skill when you need to query data conceptually, retrieve specific raw objects, or manage the lifecycle of Weaviate collections.

Query and manage agent knowledge through the controller bridge. Supports semantic routing, hierarchical recall, causal graphs, and context synthesis. Use MCP tools to store, retrieve, search patterns, and build knowledge graphs for AI agents.

This pattern is designed to solve context limitations in complex multi-agent workflows. Instead of relying on a single, massive context dump, it implements a structured, multi-cycle loop (Dispatch -> Evaluate -> Refine -> Loop). This process iteratively refines the search query by scoring content relevance and identifying missing context gaps, ensuring sub-agents gather the most targeted and highly relevant information needed for tasks like debugging or feature implementation.

A state-of-the-art memory search engine providing multi-faceted retrieval strategies. It supports default dense semantic matching, advanced hybrid search (sparse + dense with RRF), deep multi-hop Graph RAG for complex reasoning, and 'Smart' search utilizing query expansion, recency boosting, and MMR diversity reranking. Ideal for retrieving nuanced, diverse, and time-sensitive information from large, complex knowledge bases across multiple namespaces.