Skill UI

This skill acts as an Identity Psychologist, identifying the target customer's deepest aspirational self-concept. It analyzes the gap between their current self and their desired self, then rewrites brand messaging and copy to 'mirror' this desired identity. This ensures that the brand communication resonates personally, evokes a strong sense of belonging, and guides the user toward self-actualization, moving beyond merely broad persuasion.

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 guide addresses the critical difference between standard Node.js SHA3-256 and the Keccak-256 hash function required by Ethereum. Using the wrong hash function can silently corrupt calculated function selectors, event topics, storage slots, and derived addresses. It provides best practices and code examples for using dedicated libraries (like ethers, viem, web3.js) to ensure correct, Ethereum-compliant hashing in JavaScript and TypeScript environments.

This skill file acts as a Japanese translation placeholder for the 'product-capability' module. It indicates that the localized content is currently under development and not functional. Users should refer to the original English skill file for the core functionality and detailed implementation.

This is an advanced, structured workflow designed to conduct deep, multi-source investigations. It synthesizes current public evidence with user-provided context to generate highly structured reports. The workflow explicitly differentiates between verifiable facts, user-supplied evidence, logical inferences, and actionable recommendations, making it ideal for complex comparative analysis or continuous monitoring tasks.

A guide for security researchers focused on finding exploitable, remote-reachable vulnerabilities for bug bounties or responsible disclosure. It emphasizes high-signal flaws such as SSRF, RCE, and SQL injection, while guiding users through the professional triage and PoC creation process for penetration testing.

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).

Design and implement a unified operational workflow for managing notifications sourced from disparate tools like GitHub, Linear, local hooks, and chat platforms. This skill addresses notification fragmentation, alert noise, and redundancy by establishing clear severity levels, ownership, routing channels, and next operational actions into a single, cohesive pipeline.

A cross-protocol platform for discovering and searching 18,000+ MCP servers and AI agents across six or more registries. It allows users to find the necessary endpoint for specific tasks (like database access or file conversion) by searching across MCP, A2A, and agents.txt protocols simultaneously.

A robust, production-tested pattern for coordinating multiple specialized AI agents. The orchestrator decomposes complex tasks, routes them to the most suitable specialist, prevents redundant or conflicting work (anti-duplication), and enforces mandatory quality gates (e.g., running tests, checking file diffs) to verify results before marking a task as complete. It also includes heartbeat monitoring for task progress.