Skill UI

This skill provides a comprehensive framework for the continuous self-improvement of makepad-skills. It outlines automatic skill triggering via hooks, context-aware skill routing, and a structured process for capturing new patterns, error solutions, and best practices. It ensures the entire skill library remains robust and up-to-date throughout the development lifecycle.

Analyze dietary and nutrient data, identify nutrition patterns, assess nutritional status, and generate personalized improvement advice. Also supports correlation analysis with exercise, sleep, weight, blood pressure, and blood sugar data.

A rigorous, blameless framework for conducting post-mortems after major failures, such as missed quarterly targets, failed launches, or poor hires. It guides users through defining the event, applying the 5 Whys to find root causes, distinguishing between contributing factors and core causes, identifying ignored warning signs, and creating actionable, owned change registers to ensure systemic improvement and prevent recurrence.

This comprehensive tool analyzes rehabilitation data to track progress, assess recovery, and generate detailed reports. It tracks metrics like range of motion, pain levels, and strength improvements, providing actionable insights for patients and therapists to optimize therapy plans.

This skill provides a systematic methodology for iteratively improving complex skill documentation. By utilizing a reviewer agent, it identifies and categorizes issues (Critical, Major, Minor) in a structured loop. The process ensures that the skill meets high standards of quality, reliability, and functional completeness before deployment, moving beyond simple manual edits.

A comprehensive, canonical workflow for defining, writing, and improving complex AI skills. It guides users through a structured, multi-step process, including resolving targets, synthesizing information, enforcing depth gates, authoring artifacts, optimizing descriptions, and conducting thorough evaluation and validation.

This comprehensive skill analyzes sleep data to identify patterns, assess quality, and detect potential sleep disorders. It tracks trends in sleep duration, efficiency, and consistency, and performs advanced correlation analysis with other health metrics like exercise, diet, and mood. The output provides actionable, personalized recommendations based on scientific data, helping users improve their overall sleep health.

A scientific, customer-centric framework for systematically improving conversion rates on websites and landing pages. This methodology guides users through funnel mapping, identifying core visitor objections, and conducting evidence-based A/B testing. It is essential for auditing underperforming funnels, optimizing checkout flows, and transforming general marketing hypotheses into measurable, statistically significant improvements.

A comprehensive, systematic framework for auditing and improving web UI designs and frontend code. It teaches core principles like grayscale-first design, constrained scaling (for spacing, type, and color), and establishing clear visual hierarchy. Use this guide when needing to refine an existing UI that 'looks off,' or requires professional structural and aesthetic improvements.

Autonomous experiment loop that optimizes any file by a measurable metric. The agent edits a target file, runs a fixed evaluation, keeps improvements (git commit), discards failures (git reset), and loops indefinitely. Ideal for optimizing code speed, reducing bundle size, improving test pass rates, enhancing prompts, or boosting content quality through iterative measured attempts.

Autonomously improve a generated academic paper through multi-round external LLM review, fix implementation, and recompilation. Use after paper writing to iteratively polish drafts, fix inconsistencies, soften overclaims, and refine presentation.

This skill implements an autonomous, multi-round research review loop, simulating the rigorous peer-review process of top-tier conferences. It iteratively reviews, identifies weaknesses, suggests fixes, and re-reviews a research document using the MiniMax API. The system manages state persistence across multiple rounds, ensuring continuous improvement until a 'ready' assessment is achieved or the maximum round limit is reached. Ideal for academic writing, thesis refinement, or comprehensive project documentation.