Skill UI

This skill generates fully valid Microsoft Threat Modeling Tool (.tm7) files. It translates complex system architectures, including components, data stores, data flows, and external actors, into the required WCF DataContractSerializer XML format. Use it for structured STRIDE threat modeling outputs compatible with Microsoft's official tool.

This skill provides a comprehensive, reproducible rubric for evaluating scholarly and scientific work. It covers nine critical dimensions—including problem statement, methodology, data evidence, analysis rigor, and citation quality—making it ideal for reviewing research papers, grant proposals, literature reviews, and academic theses. Use it to provide structured, actionable, and professional feedback to enhance scholarly output.

OpenSquilla-compatible adapter that generates browser-playable AI audio such as voiceovers, narration, music, and sound effects through OpenRouter audio models. It streams OpenAI gpt-audio output, writes WAV assets, and reports structured AUDIO_READY manifests for webpage integration.

The Diagram Generator converts complex, unstructured inputs—such as natural language, code snippets, schemas, and notes—into professional, editable visual diagrams. It supports diverse standards including Mermaid, PlantUML, and Graphviz, enabling the creation of flowcharts, sequence diagrams, UML models, ER diagrams, architecture maps, and more. Outputs are designed to be reviewable, version-controllable, and highly precise.

This skill provides a structured way to understand complex codebases, functions, or architectural concepts. It allows the user to specify the depth of explanation (Simple, Standard, Deep), ensuring the output covers purpose, step-by-step flow, key decisions, and trade-offs for maximum learning efficiency.

Converts raw OpenMed NER outputs (text spans) into structured, standards-compliant FHIR R4 resources (e.g., Condition, Observation, MedicationStatement). It provides mechanical helpers for building CodeableConcepts using major coding systems like SNOMED, LOINC, and ICD-10, ensuring high interoperability with EHR systems and registries.

This utility separates clinical entity extraction from clinical coding. It processes de-identified text, utilizing OpenMed to identify key clinical spans. These spans are then programmatically mapped into structured FHIR R4 resources (like Condition, Observation, and MedicationStatement) and assembled into a Bundle. This process ensures deterministic, standardized data output suitable for interoperability and medical record structuring.

This skill parses complex, free-text clinical trial eligibility criteria from sources like ClinicalTrials.gov into structured, machine-readable rules. It then evaluates these criteria against a comprehensive patient profile (derived from OpenMed data) to determine potential eligibility. The output provides an explainable verdict (eligible, ineligible, or unknown) for every criterion, serving as a critical decision support tool for clinicians and researchers.

This robust pipeline guides development teams through a rigorous, five-phase planning process *before* writing any code. It systematically analyzes PRDs, design specifications (UX, accessibility), and existing architecture to produce a comprehensive implementation plan. Key outputs include Architecture Decision Records (ADRs), detailed task breakdowns, and verification strategies, ensuring all technical and design decisions are documented and scoped.

This skill manages complex, stateful proof projects as a local-first pipeline. It guides the user through drafting, rigorous verification, and source bookkeeping. It systematically handles proof continuation across runs, maintaining a full audit trail. When local attempts stall, it orchestrates handoffs to external AI models (like GPT Pro) or performs optional deep audits (DeepSeek), ensuring a structured, traceable, and verifiable output suitable for academic or technical submission.

This skill processes raw mentions of conditions and diagnoses extracted from clinical notes. It performs synonym deduplication, filters out negated or hypothetical mentions, and assigns a structured clinical status (active, resolved, or historical). The output is a clean, reconciled problem list, structured for USCDI Problem or FHIR Condition elements.

Streamlines the complex process of documenting software releases. This tool scans Git history, categorizes changes (features, fixes, performance), and generates multiple outputs—including a structured CHANGELOG, PR body, and user-friendly communication announcements—while also detecting necessary database migrations. Ideal for professional software teams preparing for production deployments.