Skill UI

This skill generates Robot Framework tests using keyword-driven syntax with Python. It supports SeleniumLibrary for web UI testing and RequestsLibrary for API testing. Users can define custom keywords and create data-driven test cases. Ideal for automation engineers needing structured test scripts for web applications and backend services. Supports cloud integration and CI/CD pipelines.

A critical discipline for managing expenses when integrating paid AI or inference APIs. This guard treats dollar cost as a third complexity dimension, mandating the definition of cost contracts (max calls per run, max budget per run, max budget per day). It enforces best practices for bounding loops, retries, and fan-out, ensuring that code bugs cannot lead to unexpected overspending. Best practice requires configuring hard caps both in the code and at the provider dashboard for defense in depth.

This skill generates a minimal yet enforceable security policy document for applications handling sensitive data. It creates a coherent Blue Book using MUST/SHOULD/CAN language, defining explicit assumptions, scope, and security gates. It helps establish threat models, data classification, trust boundaries, and incident response guidelines tailored to specific operational security defaults.

This skill specializes in transforming theoretical threat models, risk assessments, and business context into concrete, actionable security requirements. It is essential for writing detailed security user stories, defining robust acceptance criteria, building comprehensive security test cases, and ensuring compliance requirement mapping. Use it when bridging the gap between identifying a vulnerability and specifying how the system must be secured.

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 enables the creation, improvement, and management of AI agent capabilities following specific specifications. It guides users through synthesizing sources, iterating on examples, authoring artifacts, and evaluating outcomes. Use it when tasked with defining new agent workflows, updating existing skill documentation, or optimizing trigger precision for better performance.

Framework for defining and implementing Service Level Indicators (SLIs), Service Level Objectives (SLOs), and error budgets to balance reliability with innovation velocity. Includes Prometheus recording rules, alerting configurations, and error budget policies for measuring service reliability targets.

This skill guides the mastery of smart contract security best practices for Solidity. It is essential for writing robust, secure, and efficient contracts, auditing existing code for common vulnerabilities (such as reentrancy, overflow, and access control issues), and implementing secure DeFi protocols. It focuses on preventing common attack vectors while optimizing gas usage.

This skill generates comprehensive market opportunity analysis for startups, calculating Total Addressable Market (TAM), Serviceable Available Market (SAM), and Serviceable Obtainable Market (SOM) using bottom-up and top-down methodologies. It guides users through defining target markets, gathering data, validating assumptions, and creating detailed reports to assess venture potential and investment thesis.

Guides the TDD red phase by generating comprehensive failing tests that define expected behavior, edge cases, and error handling across multiple frameworks (Jest, pytest, JUnit, Go, RSpec). Ensures failures are meaningful and test isolation.

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 provides a robust system for tracking all code modifications using structured JSON records and enforcing a defined state machine (e.g., planned -> deployed). It is critical for AI coding workflows, ensuring that if a session expires or is abandoned, the next session receives the full context, progress summary, and blockers to resume seamlessly. Ideal for complex, multi-stage development projects and onboarding new codebases.