Skill UI

This skill generates a comprehensive, structured catalogue of all key concepts found within a talk's summary and timeline. It categorizes each concept and scores its potential for presentation (HIGH/MEDIUM/LOW) to help users identify the strongest narrative angles. The output is designed to serve as a structured inventory, guiding the subsequent positioning and content development stages.

Builds a structured audit trail of AI-assisted legal tasks. Documents prompts, uploaded materials, outputs, human verification steps, and final reliance. Helps legal teams reconstruct workflows for supervision review and later defense without inventing facts or prejudging privilege.

Turn interpretive-ambiguity audits of legal texts into polished deliverables: multi-page websites, single-page interactive sites, Word documents, PowerPoint decks, or LaTeX/PDF. Handles structured stress-test output, semi-structured reports, or raw prose, and renders consistent scenario-based legal analysis presentations.

Analyze OFAC or OFSI enforcement actions from URLs, pasted text, or uploaded documents and generate a structured root cause analysis Excel (.xlsx) file. The output table covers root causes, what went wrong, how it went wrong, preventive controls, and organizational immunity checks for compliance teams, counsel, and consultants.

Restructures any vague build, research, or legal-drafting request into a highly structured IRAC (Issue, Rule, Analysis, Conclusion) prompt. This method optimizes output quality for frontier models by forcing the definition of constraints, underlying rules, required reasoning, and precise deliverables, moving beyond simple prompting.

This assistant specializes in complex cross-border and comparative legal analysis. It helps research legal questions across multiple global jurisdictions and provides a structured framework for evaluating legal risks. It utilizes the Legal Data Hunter MCP to access 13M+ legal documents covering case law, legislation, and doctrine from over 50 countries. The output is flexible, requiring mandatory inline citations for all legal claims, and emphasizes aggressive data quality reporting to flag gaps.

An internal, deterministic runtime for structured scholarly writing workflows (meta-paper-write). It processes JSON input to perform critical operations such as persisting sections, assembling LaTeX manuscripts, compiling PDFs using xelatex/bibtex, managing citations, and applying length expansions. It ensures artifact integrity and high-quality output for academic publications.

This tool serves as a pre-flight safety check for legal prompts before submission to third-party AI surfaces (e.g., ChatGPT, Claude). It assesses whether the content risks compromising attorney-client privilege or work-product protection. The output provides a structured safety band (SAFE/CAUTION/STOP), detailed triggered risk factors, a discovery impact summary, and a legally safe, redacted rewrite.

A structured first-pass framework for analyzing US federal, state, and local statutes, regulations, and ordinances. This tool assists compliance analysts and junior associates by structuring required inputs, extracting requirements, and defining applicability thresholds. Output is strictly a DRAFT analysis, requiring mandatory review by a qualified attorney. Limited exclusively to US law.

A structured skill embodying Tang Jia San Shao's web fiction creation approach, covering daily updating discipline, cultivation systems with quantifiable levels, team-based battle narratives, IP lifecycle planning via six waves, and emotional anchoring from real-life experiences. Suitable for designing long-running fantasy series, managing consistent writing output, and planning cross-media IP expansion.

Knap is a command-line tool that renders Markdown templates using structured data like JSON or CSV. It supports variables, filters, and logic to batch-generate notes, format Defuddle output, and validate templates. Ideal for developers automating note creation and content processing workflows.

Close defects and incidents with a structured BUG RECEIPT output including VERIFIED, PARTIAL, or BLOCKED status. Establishes evidence boundary, traces root cause, makes responsible changes, and closes the proof loop with explicit checks and gaps.