Skill UI

This utility automatically collects comprehensive diagnostic data for the Granola application, including system specifications, audio configurations, network connectivity tests, and application metadata. It packages all findings into a single ZIP file for support teams. Use this when preparing a detailed support ticket or troubleshooting complex, persistent issues. The process is designed to collect diagnostic context without exposing sensitive meeting content, transcripts, or private API keys.

Guides building and selling Notion templates as sustainable digital product businesses, covering template design, pricing tiers, marketplaces like Gumroad or Lemon Squeezy, marketing tactics, and scaling support systems.

A sophisticated, file-based system designed for organizing and tracking complex, multi-step projects. It utilizes structured Markdown files (task_plan.md, progress.md, findings.md) to maintain a complete record of plans, research findings, and progress updates. Ideal for project analysis, workflow management, and ensuring data integrity throughout the planning lifecycle.

WizTelemetry Logging is a core extension component within the KubeSphere Observability Platform, designed for comprehensive log collection, processing, and storage. It supports advanced log collection architectures, including collecting container stdout/stderr logs (via vector-logging) and collecting logs directly from the container filesystem (via logsidecar-injector). Use this guide to understand its configuration, dependencies, and how to query logs using the dedicated API.

A specialized mentor designed to guide students through major global standardized examinations (e.g., SAT, ACT, 高考, IB, A-Level, 中考). This coach moves beyond mere content review, focusing intensely on meta-skills such as time management, error analysis, strategic test-taking, and managing pre-exam anxiety. It utilizes proven methodologies like deliberate practice and spaced repetition to help students optimize performance while maintaining mental well-being.

This skill acts as a specialized prompt engineer for AI design tools. It transforms vague, rough UI/UX ideas into polished, highly optimized prompts. It systematically enhances prompts by injecting missing details such as specific components, design system adherence (colors, typography), page structure, and platform context, ensuring the resulting command is professional and ready for superior AI generation.

This guide provides comprehensive strategies to optimize financial workflows within the Fondo system. Key areas covered include accelerating the month-end close process through auto-categorization rule setup, streamlining vendor communications with CPAs via batch processing, and implementing efficient data export caching mechanisms. It is designed to help finance teams achieve faster, more accurate, and highly automated financial reporting.

This tool functions as a post-task epilogue, designed to audit and record the entire research journey. It scans the conversation history at the end of a coding or research session to extract critical research artifacts, including decisions, experiments, dead ends, claims, heuristics, and major pivots. It systematically writes this provenance data into the structured `ara/` directory, ensuring a faithful and auditable trace of how the project truly evolved.

This skill analyzes the user's local screen history captured by the screenpipe daemon. It detects repeated research patterns and workflows, compares them against known skills, and drafts actionable proposals for new or combined skills (composition recipes). It is designed to help users systematize their ongoing work habits and formalize repeatable processes into reusable skills.

Converts complex, long-form markdown (like RFCs, specs, or reports) into a single, polished, and lightly interactive HTML file. It features a sticky Table of Contents, search functionality, advanced code-copy buttons, and integrates with design systems for professional branding, all without needing a build step or framework runtime.

A specialized tool designed to strip out predictable, statistical patterns common in AI-generated writing. It systematically rewrites overly polished or uniform text—such as blog posts, emails, or social media captions—by injecting genuine human signals, ensuring the final output reads like it was written by a real person.

This workflow is designed to rigorously stress-test any plan, design, or architectural concept before implementation. It acts as a demanding interviewer, asking deep, cascading questions one at a time to identify hidden dependencies, resolve ambiguities, and ensure comprehensive coverage. Use this when you need to validate a concept against all possible failure modes or explore every corner of a complex system design.