Skill UI

A comprehensive legal tech plugin designed for precise analysis of complex technology agreements (MSA, DPA, SOW, NDA, etc.). It functions like a senior transactional lawyer, providing deep red-flagging for compliance risks, IP ownership gaps, liability issues, and jurisdictional conflicts (e.g., GDPR, CCPA). Ideal for legal teams and compliance officers handling cross-border or AI-related contracts.

This specialized sub-agent is responsible for transforming high-level feature proposals and technical specifications into a formal, comprehensive 'design.md' document. It systematically captures all necessary technical details, including architectural decisions, data flow diagrams, detailed file changes, API contracts, and thorough testing strategies. Use this skill during the planning phase of any complex software change to ensure technical completeness and feasibility.

This skill compiles user creative intent into executable image and video prompts for AI models. It specializes in character consistency, cinematic storyboards, and reference asset mapping for R2V/I2V/T2V tasks. It ensures visual contracts, narrative flow, and production-ready specifications without replacing model capabilities.

TLC Discover transforms unshaped ideas into verdicts and design documents covering decisions, flows, and contracts. It helps teams research problems, understand feasibility, and decide whether to build before planning how. This tool prevents premature solution proposals and ensures concrete values for decisions, creating a plan anyone can follow without attending the original discussion.

This skill covers essential framework patterns for modern Ruby on Rails applications (Rails 7.1+ and 8.x). It includes directory contracts, skinny controllers, service objects, form objects, query objects, background jobs, ViewComponent, Hotwire, and the Rails 8 Solid stack. Use this when building or reviewing Rails apps, controllers, models, services, jobs, or views to ensure maintainability and best practices.

Create, edit, validate, and run Agent QA tests, suites, and hooks via MCP or CLI while preserving canonical IDs and schema contracts. Supports web and mobile testing with strict ID validation and safe execution.

A 98-rule design specification for building AI-native CLI tools across three certification levels. Covers structured JSON output, error handling, input contracts, exit codes, safety guardrails, self-description, and agent feedback loops.

Implement secure API design patterns including authentication, authorization, input validation, and protection against vulnerabilities. Covers JWT token contracts, refresh sessions, resource authorization, and input parsing. Suitable for backend developers securing endpoints, preventing abuse, and ensuring data integrity in production environments.

This skill specializes in creating realistic mock services for development, testing, and demonstration purposes. It simulates real API behavior to enable parallel development and facilitate thorough testing. Use it for building mock APIs for frontend or integration testing, simulating partner APIs, creating demo environments, and validating API contracts before backend completion. Avoid using for production systems or security testing.

Designs data models, API contracts, file structures, and architectural patterns for software systems. Produces structured blueprints with ADR summaries, security notes, and migration strategies to guide implementation and code review handoffs.

A goal-integrity skill for backend/API/persistence work that preserves existing behavior, validates changes, and prevents scope drift. Emits contracts, deviation notices, and phase checks to maintain alignment with user requirements during complex development tasks. Skip for Q&A or trivial edits.

Atlas Ledger is a critical companion designed to provide lasting 'memory' to project contracts. It automatically processes detected deviations or 'drift' (e.g., from audits or reviews) and distills these instances into formal, actionable contract clauses (WHEN/DON'T/INSTEAD). These clauses are written to a persistent project memory file, Atlas.md. This mechanism ensures that lessons learned from failure are systematically captured, allowing future contract cycles to incorporate these rules, thereby strengthening overall project governance and reliability.