Skill UI

Audits and generates hreflang implementations for multilingual/multi-region sites, checking self-references, return tags, ISO language/region codes, canonical alignment, protocol consistency, and x-default fallbacks before outputting HTML, header, or sitemap snippets.

This methodology converts verbose, natural language system instructions into an atomic, structured-label format (e.g., trigger:, action:). By structuring rules, it bypasses the limitations of natural language processing, ensuring LLMs allocate full attention to every constraint, thereby maximizing compliance, improving reliability, and reducing token usage.

This skill provides methods for reliably extracting typed, validated, and structured data from Large Language Models (LLMs), moving beyond simple text parsing. It covers best practices across major APIs (OpenAI's response_format, Anthropic's tool_use, Google's responseSchema) and local models. Key workflows include defining schemas (Pydantic/Zod), implementing constrained decoding, and building robust retry loops for production-grade data pipelines.

Analyzes campaign attribution evidence with the Diamond Model and ACH, covering infrastructure overlaps, TTP consistency, malware similarities, timing, and language signals to help SOC analysts and hunters assess threat actor confidence.

Guide to using Splunk Search Processing Language to craft correlation searches that aggregate logs, apply thresholds, detect anomalies, and enrich context so SOC analysts can spot brute-force, lateral movement, exfiltration, and other threats.

Hunt for encoded, download cradle, AMSI bypass, and constrained language PowerShell executions by formulating hypotheses, querying SIEM/EDR telemetry, correlating events, and validating findings to guide containment and response.

Guide for writing YAML-based Semgrep rules to detect app-specific vulnerabilities, enforce coding standards, and plug into CI/CD for continuous SAST assurance across multiple languages.

Automates uploading files from Claude to Google Drive by encoding them and POSTing through a deployed Apps Script, returning Drive links so workflows that produce deliverables can save them directly in Drive across languages.

The Stock Analyzer Skill provides comprehensive technical analysis for stocks and ETFs. It utilizes industry-standard indicators like RSI, MACD, and Bollinger Bands to generate actionable trading signals. Users can perform advanced technical comparisons, monitor portfolio strength, and identify chart patterns through natural language queries, eliminating the need for manual indicator calculation.

A powerful operational companion for database developers. This skill assists with the daily lifecycle of database interactions, including translating natural language requirements into optimized SQL queries, generating database migrations, performing comprehensive schema introspection across multiple dialects (PostgreSQL, MySQL, SQLite, SQL Server), and identifying performance bottlenecks through detailed query optimization and index recommendations. It also supports ORM patterns like Prisma and SQLAlchemy.

Explains how to build LLM-powered apps using Claude, the Anthropic SDKs, or Agent SDK—covering language detection, recommended surfaces, and default model/tooling choices for reliable integrations.

Diagnoses a customer’s awareness level before messaging, calibrating persuasion strategies, language register, and entry points so campaigns match motivation, ability, and trust cues without jumping ahead of the audience’s belief stage.