Skill UI

Provides a deep, structured assessment of whether an AI system meets the criteria for 'high-risk' classification under Article 6 of the EU AI Act. Grounded in the Commission's draft guidelines (Annex I & III), this tool guides users through complex compliance checks, including product safety routes and quasi-provider traps. Essential for making consequential risk verdicts and ensuring legal compliance.

This skill provides a comprehensive audit framework for evaluating AI agents used in legal, compliance, or business operations. It assesses the risks associated with delegated authority—such as sending messages, filing documents, or making payments—by checking for adequate controls, logging, revocation mechanisms, and clear accountability chains. It is essential for firms connecting agents to sensitive systems like CRM, court portals, or financial accounts to ensure safe and compliant deployment.

This skill helps legal professionals set up a personalized, structured Legal Guidance Vault. It guides the user through an interview of their entire digital tool stack (email, calendar, docs, etc.) to ensure all sources are covered. It generates a standardized, reusable prompt template for archiving privileged legal advice, making it searchable by topic, person, or product in future sessions.

This skill addresses the common problem of documentation decay in long-lived software projects. It establishes a canonical governance layer by assigning four non-overlapping roles—Constitution, Map, Status, and History—to existing documentation. By linking these roles to the active agent harness, it prevents documentation drift, ensuring that all project information remains accurate, authoritative, and contextually linked to the current codebase, making it ideal for the maintenance phase.

This skill provides a comprehensive framework for in-house legal teams to evaluate the performance of outside counsel. It guides the creation of a detailed scorecard, structures post-matter feedback forms, prepares Quarterly Business Review (QBR) materials, and generates comparative firm scorecards, allowing for data-driven panel decision-making.

QiuZhi2046's content playbook for AI science popularization: pain-point-first hooks, hands-on testing with real data, one-click solutions, and multi-platform strategies for tutorials, tool reviews, and tech commentary. Ideal for creators making AI accessible.

This tool generates self-contained, interactive HTML "deal cards" that translate complex legal regulations into actionable negotiation and reference guides. It systematically distinguishes between mandatory legal obligations and negotiable implementation choices, making it crucial for contract negotiation support, client education, or internal compliance training across various jurisdictions.

This skill simulates an experienced litigation solicitor reviewing a proposed settlement offer. It rigorously stress-tests the underlying assumptions, identifying potential weaknesses in evidence, legal merits, opponent leverage, and timing pressures. It provides a structured, candid assessment to ensure better-informed decision-making before negotiation.

This skill forces the AI to operate in a non-inferential mode, ensuring every claim—factual, legal, or numerical—is strictly anchored to user-provided materials or verified online sources. It eliminates assumptions, gap-filling, and background knowledge reliance, making it essential for legal research, evidence review, citation checking, and high-stakes document analysis where evidential fidelity is paramount.

This skill provides a guided, hands-on tutorial to teach users the Ouroboros workflow. It guides the user through a structured process of refining vague ideas into precise, executable specifications (Seeds). By simulating an interview and exposing hidden assumptions, it reduces the inherent ambiguity in initial project planning, making it ideal for product development, AI prompt engineering, and initial concept validation.

Apply Martin Kleppmann-inspired rules for designing reliable, scalable, and maintainable data systems. Covers consistency, replication, partitioning, transactions, streams, batch processing, and schema evolution. Use when making architecture decisions for data-intensive applications.

Apply Eric Evans-inspired Domain-Driven Design rules for modeling complex domains. Define bounded contexts, protect ubiquitous language, and design aggregates. Use this skill for strategic domain modeling, context mapping, repositories, and domain services before making design or code decisions.