Skill UI

This skill enforces a rigorous data validation protocol by establishing hard boundaries at every point data enters the system (API requests, user input, environment variables, webhooks, etc.). It mandates a four-phase process: detection, trust classification, mandatory filtering (schema validation, sanitization, type checking), and final verification. This prevents untrusted data from reaching core business logic, mitigating risks like SQL injection and XSS.

Builds two parameterized UI modes—iridescent white and colorful black—using OKLCH palettes, procedural WebGL spectral fields with CSS fallback, vision gating, screenshot QA, and total/per-color intensity reports.

Coordinates a bounded code review of a defined diff from correctness, authorization and performance perspectives, delegating to independent agents only when authorized and reproducing important findings centrally.

Orchestrate bounded coding tasks by delegating them to the Qoder CLI implementer, then review and land the resulting changes. This skill provides a structured loop for writing briefs, dispatching via a relay script, reviewing diffs, and committing verified work, with strict permission and authorization controls.

TextMe is a local daemon that transforms your smartphone into a powerful remote control for Claude Code sessions. By bridging inbound iMessages (from whitelisted numbers) through services like Sendblue, users can interact with their AI session on their laptop, executing code, navigating filesystems, sending voice notes, and receiving real-time updates. Ideal for supervising headless workstations or coding while away from your desk.

This skill involves conducting threat modeling using the STRIDE methodology to identify potential security threats, assess risks, and design appropriate security controls. It is essential when designing secure systems, making architectural changes, or preparing for security audits. The process includes analyzing data flows, identifying trust boundaries, and mitigating risks related to spoofing, tampering, repudiation, information disclosure, denial of service, and privilege escalation.

Guides investigating common or slow process variants, cases with repeated work, and exact-case queries in Process Mining. Provides step-by-step tool calls for variant metrics, rework filtering, and attribute-based case selection, adhering to shared contracts and investigation methods.

FlowKit is a Python library for analyzing flow cytometry data. It supports spillover compensation, logicle transforms, hierarchical gating, and GatingML strategies. Users can reproduce FlowJo 10 workspace analyses, generate reproducible gate counts, population percentages, and fluorescence summaries. Requires Python 3.13 and specific dependencies for scientific computing.