Skill UI

A comprehensive guide detailing the rigorous, theory-specific peer review process for major academic journals. It explains the mechanics of masked peer review, the distinction between Theoretical Articles and Theoretical Notes, and anticipates the deep theoretical objections that reviewers—who are often rival model builders—will raise. Use this before submission or after receiving a decision letter to properly strategize revisions.

A comprehensive guide detailing how to package and present research artifacts—including code, hardware designs, and datasets—for major academic conferences. It outlines best practices for both initial review-time evidence and long-term public reuse, ensuring reproducibility and maximizing the chances of adoption by future builders.

Build a local multimedia webpage project from a user topic, audience, language, style, and media preferences by framing requirements, researching, planning, acquiring media, generating files, packaging, validating, repairing, and delivering usage guidance.

This skill constructs a comprehensive, chronologically sorted patient timeline from raw clinical entities extracted from medical notes. It specializes in temporal normalization, resolving both absolute and relative dates (e.g., 'two days after admission') against a defined anchor date. The resulting sorted sequence of diagnoses, medications, and procedures is ready for immediate visualization or seamless export to FHIR resources.

Creates an Agent Authority Charter to define permissions, delegation, approvals, escalation, and audit requirements for AI agents before enterprise or regulated deployment. Helps legal, compliance, risk, and product teams document what an agent may and may not do, prepare for human review, and ensure auditable governance across the agent lifecycle.

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.

Builds and edits model-driven Power Apps applications from natural-language intent, covering tables, columns, relationships, forms, views, charts, and more. Runs an interactive multi-turn authoring flow: environment selection, jobs-to-be-done, app spec authoring, guardrail lint, plan approval, and generation/deployment.

Autonomous agent that builds a complete Power Automate flow from a natural language description. It discovers environments, connectors, and connections, generates a validated flow definition, creates the flow, and optionally publishes it. Ideal for accelerating low-code automation delivery with minimal manual effort.

Build card games with robust card data, deck/hand/discard zones, draw/shuffle/reshuffle, turn phases, costs, and effect resolution. Ideal for deckbuilders, TCG/CCG, and roguelike deckbuilders; includes compositional patterns and pitfalls to avoid.

Builds court-facing litigation chronologies from disclosure bundles, witness statements, and matter files. Applies CPR 31.22 implied-undertaking check, privilege screen, and case-theory significance tagging. Use for UK civil litigation to generate working or Statement-of-Facts timelines.

Creates a client instruction schedule: a plain-English, Scott Schedule-style Word table that gathers a client's evidence and instructions issue by issue, plus a one-page covering note. It helps overwhelmed clients in document-heavy disputes by turning case papers into structured, mostly closed questions for solicitor review.

Compile documents, notes, transcripts, research materials, or code repositories into an evidence-grounded, visualization-ready knowledge graph with typed entity nodes, statement-level provenance, and directed relationship edges.