Skill UI

Adds existing Dataverse tables to Power Apps code apps with generated TypeScript models and services, or creates new Dataverse tables via API. Supports schema planning, dependency ordering, CRUD, and file/image uploads. Use when connecting to Dataverse or querying table data.

Adds Office 365 Outlook connector to a Power Apps code app. Use when accessing calendars, sending emails, reading inbox, or managing Outlook events. Covers finding connection IDs, running CLI commands, reviewing generated services, configuring operations, building the app, and updating the memory bank.

Post-generation editor for existing Power Apps mobile apps. Iterate on Application Insights configuration, plan, data model, native capabilities, design, screens, and generated code, with verification and preview.

This skill is the final step in the plugin build pipeline. It takes the generated manifest and all staged binary artifacts (Android/iOS) from prior build steps. Its core function is to reconcile the declared entrypoints against the actual existence of binaries, ensuring consistency. It then zips these verified components into a single, statically verified, and ready-to-deliver .ppmplugin bundle.

This skill processes raw, report-only optimization observations generated by Caveman tools. It guides the user through an evidence-first, rigorous evaluation process, requiring explicit operator choice, designing a minimal candidate change, and performing a paired baseline evaluation using identical fixed inputs. It ensures that any proposed code change is validated against quality checks and established performance metrics before implementation.

This skill provides a comprehensive audit of legal AI outputs, documents, and prompts before they are trusted or used in professional contexts. It checks for seven critical 'fault lines,' including grounding, causality, metacognition, and adherence to authority boundaries. Use this for legal memos, contract reviews, compliance reports, or any AI-generated content requiring high reliability.

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 tool allows users to retrieve the complete, up-to-date metadata and audio URL for a specific music production ID. It is essential for checking the current processing status, such as whether stems, MIDI, or mastering have been successfully generated, ensuring the user has the latest information before proceeding to the next workflow step.

This tool extracts structured MIDI data and potential sheet music scores from an existing, generated music production. It is essential for users who need to transcribe, arrange, or import the music into a Digital Audio Workstation (DAW). Processing requires a valid production ID.

This tool separates an already generated music production into four isolated stems: vocals, drums, bass, and other. It is ideal for users needing to remix tracks, create karaoke versions, or perform music sampling. Requires an existing production ID, and the resulting stems are accessible via the primary dashboard.

This skill provides a comprehensive guide to drafting legally compliant termination notices under French labor law. It walks users through collecting detailed information regarding the company, employee, and specific misconduct (such as gross misconduct or personal reasons). The generated letter structure ensures all mandatory components, including detailed, factual, and exhaustive reasons, are included, thereby protecting the employer in potential legal disputes.

This internal, deterministic gate enforces academic rigor before manuscript compilation. It audits the input, rejecting unsupported empirical claims, missing citation verdicts, or concrete outcome numbers that lack user evidence. It ensures that generated scientific papers only present validated results, blocking unsupported quantitative or qualitative assertions.