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 sophisticated framework designed to simulate complex legal interactions across various domains, including tenancy law, business contracts, startup disputes, and employment claims. This tool is ideal for demonstrating AI-powered legal triage systems, training personnel on responsible AI use, or creating realistic proof-of-concepts for legal technology presentations. Note: This skill is strictly for educational and demonstration purposes and does not provide legal advice.

This skill provides a critical audit layer governing the transition of AI-generated legal output from analysis to real-world consequence. It mandates a rigorous check of evidence sufficiency, institutional authority, procedural adherence, and visible uncertainty before any output can become a reliance, recommendation, or executed commitment. It is essential for high-stakes legal workflows, such as contract review, compliance findings, or drafting final advice.

This skill provides professional translation of legal documents, contracts, and formal agreements from any language into US English. It is designed to maintain the integrity of the original .docx formatting, including fonts, styles, headers, footers, and track changes. Use this whenever translating complex legal texts across domains such as M&A, IP, Real Estate, or corporate law, ensuring the output is publication-ready.

This skill acts as an expert model-routing advisor for reviewing legal agreements (NDAs, MSAs). Instead of reviewing the contract itself, it analyzes the document's nature—such as dominant sub-task (extraction, reasoning, redlining), stakes, and length—to recommend the optimal primary and fallback LLM. It provides comprehensive decision support, mitigating common errors and suggesting necessary human verification points.

This tool acts as a model-routing advisor for extracting structured data from complex legal documents, such as contracts. It analyzes key parameters—including stakes, cost, required speed, and document type (e.g., scanned vs. clean digital)—to recommend the optimal LLM model combination (Primary, Fallback, Avoid). It provides critical decision support, guiding users on which AI approach to use for extracting clauses, dates, and parties, without performing the actual extraction.

This tool serves as a model-routing advisor for high-stakes legal translation tasks, covering contracts, statutes, and case law. It does not perform the translation itself, but instead provides expert decision support by recommending the optimal primary and fallback LLMs based on language pair, required privacy level, cost, and speed. Crucially, it emphasizes that human legal-linguist review is mandatory, as no single LLM can guarantee certified legal accuracy.

This skill guides the extraction of structured data from multiple documents (PDF, DOCX) into a comprehensive, cited Excel matrix. It is ideal for legal, contractual, or research review processes where users need to compare specific clauses, provisions, or pieces of information across numerous source files, ensuring every extracted data point includes a citation (page number and context quote) for verifiable accuracy.

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.

Defines an operator approval contract for agent-drafted outbound messages: hashed draft filing, epoch-keyed decisions, approval snapshots, durable delivery claims and receipts, plus a pre-draft baseline gate. Use when a human must approve, reject, or steer each send before it leaves.

This skill enables independent auditing of AI agent, gateway, or automation workflow runs. It reconstructs events from traces, checkpoints, and tool calls to verify success claims without trusting self-reports. Users establish contracts, build claim ledgers, normalize evidence, rank witnesses, and assign verdicts like proven or contradicted. It ensures integrity in multi-step automation and separates autonomous success from human-assisted outcomes.

Extract structured fields from documents like invoices, payslips, and contracts with page grounding. Each value cites its source page and confidence score. Missing values are reported as not found instead of hallucinated. Supports PDF, PNG, and DOCX files. Ideal for accounting, compliance, and data parsing tasks where accuracy is critical. Uses Stipple API for processing.