Skill UI

This skill conducts deep, structured competitor analysis using Browserbase's advanced discovery and enrichment tools. It generates a comprehensive HTML report that includes market overviews, detailed per-competitor deep dives (covering marketing, social, news, and technical aspects), side-by-side feature/pricing matrices, and comparative mentions feeds. Ideal for market researchers, product managers, and strategists needing actionable competitive intelligence.

This skill outlines a systematic, multi-phase workflow for diagnosing hard bugs and performance regressions in complex codebases. It emphasizes the critical necessity of building a tight, deterministic feedback loop (Phase 1) before moving to hypothesis generation. The process guides users through reproducing the failure, minimizing the scope of the issue, and forming actionable, ranked hypotheses.

A comprehensive skill for systematically building, refining, and documenting a project's domain model. It helps define core terminology, establish a ubiquitous language, and record critical architectural decisions (ADRs). Use this when you need to challenge ambiguous language, invent edge-case scenarios, or maintain architectural consistency throughout the development lifecycle.

This skill provides a comprehensive workflow for generating, editing, and manipulating images using Google's Gemini Nano Banana Pro model (gemini-3-pro-image-preview). It is designed for tasks such as creating visuals, generating logos, modifying photos, or creating product mockups, offering a robust, file-based approach to handle complex image data and API interactions.

This skill implements the LLM Council concept, enabling multiple open-weight language models to collaborate on complex queries. The process follows a three-stage deliberation: 1) Parallel independent responses from selected models; 2) Peer-to-peer ranking of the responses; and 3) Final synthesis by a designated Chairman LLM. Powered by Fireworks AI, it ensures deep, multi-faceted analysis and consensus building for high-stakes decision support.

This skill assists users in defining, adapting, and designing bounded, structured feedback loops for AI agents. Whether you need to find a suitable existing workflow, fine-tune a published loop, or design a new process from scratch, this tool guides you through a safe, iterative methodology. It emphasizes setting clear stopping rules, guardrails, and verifiable, measurable steps to ensure the automation remains controllable and focused.

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 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 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.

This skill generates comprehensive, academic-style survey papers as a single, self-contained HTML file. By reading an anchor resource and curating research data, it structures the content and utilizes advanced LLMs (like Kimi K2.6 via Fireworks) to generate all prose, figures, and bibliographies, suitable for rapid academic literature review.