Skill UI

This skill analyzes various legal AI outputs, such as memos, contracts, and reports, to assess their structural integrity and legal robustness. Inspired by Minimum Description Length (MDL), it audits for unnecessary complexity, overly verbose caveats, hidden legal uncertainties, or inefficient workflow design, ensuring the resulting output is as concise and simple as legally safe.

A comprehensive framework for producing high-authority, multi-layered AI industry content. This skill teaches how to structure content across three pillars: real-time quick news reports (Speed), data-driven deep dives (Depth), and annual trend reports/panorama maps (Authority). Ideal for content creators, journalists, and industry analysts needing to establish thought leadership in the rapidly evolving AI sector.

This powerful diagnostic skill monitors the operational status of long-running, complex sessions. It not only queries whether the session is active, completed, or failed, but also performs crucial 'goal drift' measurement. This measurement quantifies the deviation between the current execution output and the original defined seed goal. Based on the calculated drift score, it provides actionable status reports and suggests necessary course corrections, ensuring the project remains aligned with its core objectives.

This advanced skill provides systematic, adversarial verification for AI-generated legal documents. It rigorously checks factual accuracy, legal citations, numerical data, and source authenticity against authoritative databases. Use this when you need to perform red-teaming, fact-check, or quality-control complex legal analyses, compliance reports, or regulatory summaries before any external distribution.

Framework for AI media writing inspired by Synced. Focuses on paper-first reporting, quantitative data, academic plus industry parallelism, layered analysis, and productized content. Applies to deep tech reviews, model benchmarks, industry trend reports, and editorial commentary.

This skill helps identify issues in Superpowers sessions by analyzing transcripts and evidence. It assists in troubleshooting problems like repeated work, ignored plans, or unexpected costs. The process involves locating session files, triaging dimensions, generating detailed reports, and optionally creating GitHub issues or export bundles for maintainers. All findings must cite specific paths and lines.