Skill UI

This skill utilizes the Gemini Nano Banana Pro model to generate and edit high-quality images. It is ideal for users needing to create visuals, generate product mockups, design logos, or perform complex photo editing tasks based on text prompts. Supports file-based API calls for robust operation.

This skill guides users through structured, adaptive learning experiences for any topic. It diagnoses the user's current knowledge level and goal to create a personalized study path. It utilizes techniques like worked examples, retrieval questions, and spaced repetition to ensure deep understanding, making it ideal for self-study, skill acquisition, or subject review.

This skill generates compact, standalone, multi-lesson course artifacts suitable for study guides or mini-courses. It structures content with clear lesson plans, learning objectives, flashcards, quizzes, and source links, creating a self-contained, browser-ready learning experience optimized for knowledge retention.

This skill executes an LLM Council workflow, allowing multiple open-weight large language models (LLMs) to independently answer a prompt. The process involves parallel deliberation, peer ranking, and final synthesis by a designated Chairman LLM, providing a comprehensive and highly vetted final answer. Ideal for complex problem-solving and critical analysis.

This library manages the entire lifecycle of bounded AI agent feedback loops. It allows users to find existing workflows from a catalog, adapt established loops by modifying parameters or tools, or design entirely new, structured iterative processes through a guided interview. It emphasizes safety by enforcing explicit checks, stop rules, guardrails, and measurable terminal states, preventing endless, uncontrolled autonomy.

Programmatically manage your entire contact database within Mailtrap. This guide covers using the API to create, update, delete, and bulk import contacts. It is essential for synchronizing contact data with CRMs, triggering custom automation events, building targeted segments, or performing large-scale list cleanups.

This comprehensive guide details how to configure, integrate, and troubleshoot live email sending using Mailtrap. It covers two primary methods: the Email API (REST) and SMTP. Learn the differences between core email streams—transactional (app-generated notifications), bulk (promotional marketing), and batch requests (high-volume efficiency)—along with recommended integration patterns and specific technical endpoints.

This guide details the process of adding, verifying, and publishing necessary DNS records (SPF, DKIM, DMARC) for a custom sending domain in Mailtrap. It covers both manual compliance steps via the UI and programmatic automation through the Sending Domains API. Essential for ensuring high email deliverability and authentication compliance.

Use Mailtrap Email Sandbox to capture and inspect outbound emails without sending them to real recipients. This is crucial for development, staging, and CI/CD environments. It allows developers to test email content, headers, attachments, and spam scores using dedicated APIs, SMTP settings, or SDKs, ensuring mail integrity before deployment. Ideal for automation and rigorous quality checks.

This workflow helps developers quickly build throwaway prototypes to answer specific design or functionality questions. It can generate interactive terminal applications to test complex state/business logic, or create multiple radically different UI variations toggleable from a single view, allowing for rapid validation of ideas before committing to production code.

This skill scaffolds the necessary configurations for advanced engineering workflows. It guides the user through setting up the issue tracking system (GitHub, GitLab, or local markdown), defining the canonical triage label vocabulary, and establishing the domain documentation context (single or multi-context). It must be run once to initialize the repository for subsequent agent-driven development skills.

This tool evaluates how thoroughly a feature implementation meets product requirements (PRDs) or specifications. It scores acceptance criteria case-by-case, independently grading both the code implementation and the associated test coverage (unit and E2E). Ideal for benchmarking multiple development efforts, auditing adherence to specifications, or determining if a feature is 100% complete and compliant with the ground truth PRD.