Skill UI

Hookify rules enable developers to define custom, event-driven workflows using Markdown files with YAML frontmatter. These rules monitor specific operational events (such as bash commands, file edits, or user prompts) and can trigger warnings or block operations when predefined regex patterns are matched. They are essential for enforcing coding standards, preventing dangerous operations, and guiding development adherence in complex software environments.

This framework manages the ingestion, organization, synchronization, and search of knowledge across multiple storage layers, including local files, persistent memory, vector stores, and Git repositories. It provides a structured approach for ensuring knowledge durability, deduplication, and maintaining a 'single source of truth' across complex development and operational contexts.

This skill provides comprehensive security and monitoring for Large Language Model (LLM) powered trading agents. It helps to audit trade decisions, ensure compliance with risk parameters, and mitigate potential risks associated with automated financial operations.

This file is dedicated to handling Japanese translations for the 'messages-ops' component. It currently acts as a localization placeholder, indicating that the full Japanese translation is under active implementation. Users should refer to the original English skill file for the core functionality and detailed usage instructions.

This skill guides users through evidence-based terminal operations. It is designed for scenarios requiring direct command execution, Git status checks, debugging CI/build failures, and pushing narrow, verified fixes. It emphasizes following a structured, minimal-scope workflow and accurately reporting the repository's current state (e.g., local changes vs. pushed code).

This comprehensive skill guides developers through integrating and optimizing Firebase Cloud Firestore within Flutter applications. It covers best practices for data modeling, performing advanced CRUD operations, setting up real-time listeners, executing atomic transactions, and designing for massive scale. Learn how to implement robust querying, cursor-based pagination, and secure your data structure effectively.

A comprehensive, generics-first utility library for Go, providing over 500 type-safe, functional helpers (like Map, Filter, Reduce, GroupBy) for slices, maps, and channels. Designed to replace manual, verbose loops with declarative code. It supports immutable operations by default and offers progressive complexity variants (lo, lop, lom, loi) to handle different performance needs, from standard transforms to CPU-bound parallelism and lazy iteration. Ideal for writing clean, maintainable, and performant Go code.

Use the gws people CLI to manage Google People contacts, contact groups, other contacts, and domain directory data through batch operations, searches, and updates—ideal for automating contact administration and sync workflows.

This skill provides comprehensive operations for Feishu Base (Multi-Dimensional Table), serving as a powerful internal database management system. It supports all CRUD operations, including creating and updating tables, managing fields (including formulas and lookups), writing and reading records, setting up complex views, building dashboards, and automating workflows. Use this skill when dealing with multi-dimensional tables, Bitable links, or the Base environment.

This skill provides comprehensive functionality for reading, creating, editing, and downloading content from Lark Feishu Docs (Docx/Wiki). Whether accessing via URL or token, it supports structured content manipulation using both XML and Markdown formats (v2 API). Use it for fetching document details, updating specific blocks, and managing embedded media and resources like whiteboards and images. Note that it requires prerequisite knowledge for advanced operations.

This guide details best practices for using `lark-cli` to interact with Feishu resources. It covers initial configuration, switching between user and bot identities, and crucial authentication flows for AI agents. It provides detailed instructions on handling permission errors, implementing secure split-flow authentication, and managing high-risk write operations to ensure data integrity and user consent.

Create and manage Feishu/Lark spreadsheets: edit sheets and cells, write formulas and styles, search and replace, build charts and pivot tables, and handle bulk updates, filters, and other table structures.