Skill UI

This skill generates a structured, non-advisory worksheet for planning trade ideas, basket adjustments, or comparing prediction markets. It helps users methodically review venues, underliers, constraints, and manual execution steps without placing any trades or providing financial advice. Ideal for the research phase of quantitative finance workflows.

This skill guides the design and rigorous review of goal-oriented feedback loops for autonomous agents. It helps users define machine-decidable exit criteria, select the appropriate loop type (e.g., servo, regulator), and test the workflow against common failure modes like spinning, goal-gaming, or running past the correct answer. Use it when building complex, iterative, or self-correcting agent workflows.

A comprehensive framework for planning and executing multi-channel product launch campaigns. This skill guides users through audience research, positioning definition, content strategy (landing pages, emails, social, video), and rigorous review gates to ensure every asset drives conversion and maintains brand consistency across all platforms. Ideal for orchestrating major product releases.

This tool orchestrates the end-to-end process of building a brand-new feature. It automates the entire lifecycle, including initial research, planning, Test-Driven Development (TDD) implementation, code review, and gated commit. Use this when adding a capability that does not currently exist in the system.

This advanced orchestration tool streamlines the process of building a Minimum Viable Product (MVP). By ingesting high-level design documents (SDD/PRD), it automatically plans thin, end-to-end vertical slices. The system then scaffolds, executes TDD implementation, and manages gated commits, transforming theoretical specifications into a functional, reviewable starting point, dramatically accelerating initial development cycles.

This tool is designed to manage the process of altering an existing, functional feature to meet a new desired specification. It ensures a structured workflow: first, update the existing test cases to reflect the new behavior; second, modify the underlying implementation to pass these updated tests; finally, complete through review and gated commit. Use this when the feature works but its behavior needs adjustment.

This tool orchestrates the complete workflow for addressing defects, ensuring a robust fix process. It guides the user through reproducing a bug as a failing regression test, applying the necessary fix until the test passes (goes green), and managing the subsequent code review and gated commit phases. Ideal for systems where existing functionality is broken, incorrect, or exhibiting regression.

This engine serves as a shared, comprehensive orchestration layer for the entire development lifecycle (orch-* skills). It defines a rigorous, gated pipeline—including Research, Plan, TDD Implementation, Review, and Commit—ensuring consistency regardless of the specific operation (e.g., feature addition, defect fixing). It also includes a size classifier to accurately scope the required effort and gates for mandatory human review.

This skill reviews prediction market, basket, oracle, and trading-agent workflows to ensure compliance, safety, data quality, and privacy. It must be run before any workflow handles user portfolio data, venue authentication, API keys, or trade planning to mitigate execution and regulatory risks across multiple domains.

This guide provides a comprehensive workflow for searching and retrieving biomedical literature from PubMed and NCBI. It covers advanced query construction using MeSH terms and specific field tags, advanced filtering (date, publication type), and a repeatable programmatic workflow using NCBI E-utilities (esearch, efetch). Essential for researchers conducting systematic reviews and literature monitoring.

A comprehensive guide detailing advanced performance optimization patterns for React 18/19 and Next.js. Adapted from Vercel Engineering's best practices, this skill organizes 70+ critical rules across eight categories—including eliminating waterfalls, optimizing bundle size, improving server-side rendering, and managing client-side re-renders. Use this when developing, reviewing, or refactoring high-performance React applications.

The Santa Method is a multi-agent adversarial verification framework designed to improve output quality by requiring two independent reviewers (Agent B and Agent C) to pass the content before publication. It eliminates single-agent bias and systematically improves outputs through iterative refinement loops until convergence or manual escalation.