Skill UI

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.

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 skill transforms the current workspace into a comprehensive, stateful teaching environment. It guides the user through deep, multi-session learning by structuring content into core components: a defined mission, reference materials, curated resources, structured lessons, and continuous learning records. It employs educational best practices (spaced repetition, retrieval practice) to ensure long-term knowledge retention.

This skill guides the systematic triage of project issues and external pull requests (PRs). It moves development items through a defined state machine using roles (e.g., bug, enhancement) and states (e.g., ready-for-agent, wontfix). The process involves context gathering, cross-codebase verification, deep questioning (grilling), and generating comprehensive, agent-ready briefs or marking them for human implementation.

This document provides a comprehensive guide to the principles and vocabulary needed to write high-quality, predictable, and effective skills. It covers advanced concepts like model-invoked vs. user-invoked skills, managing context load, structuring information hierarchies (steps vs. reference), and implementing progressive disclosure to improve agent predictability.