Skill UI

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 meta-skill guides guardians and children through planning educational projects, including science fair entries, DIY kits, and school assignments. It assesses feasibility based on age and budget, generates age-appropriate step-by-step plans, advises on material substitutes, and crucially, surfaces safety considerations and parent-facing learning objectives.

A specialized internal helper for deep meta-stack trace investigation in Python environments. This tool guides users through generating Python-specific root-cause checks, creating minimal reproducible test cases using pytest, and identifying precise targets for defensive patches (e.g., validation or guard clauses). It ensures robust debugging and testing practices.

This skill enables the creation of a robust 'harness' system for coding agents within a repository. It addresses the need to prevent repeated AI-generated coding mistakes by implementing durable instructions, guardrails, regression tests, and failure memory. It treats the target repository as the source of truth, ensuring consistency and maintaining high reliability across all automated contributions.

This skill guides the design of statistically rigorous A/B tests for optimizing product features, UI/UX changes, onboarding flows, and pricing models. It generates a complete test plan, including formulating hypotheses, calculating required sample sizes, estimating test duration, defining primary and guardrail metrics, and providing a detailed guide on interpreting results (ship, iterate, or reject).

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.

This guide teaches security teams how to proactively detect and respond to unauthorized cryptocurrency mining operations across major cloud platforms (AWS, Azure). It utilizes a multi-layered approach by analyzing compute cost anomalies, monitoring GuardDuty findings, inspecting network traffic to known mining pools, and analyzing runtime process execution in EC2, ECS, and EKS environments.

This skill provides a comprehensive solution for monitoring brand impersonation attacks across multiple digital vectors. It systematically scans domains, social media platforms, mobile app stores, and the dark web to detect phishing campaigns, typosquatting, and unauthorized brand usage. It is essential for security teams conducting proactive threat intelligence gathering and vulnerability assessments to safeguard brand integrity.

A comprehensive guide to achieving compliance with the HIPAA Security Rule (45 CFR Part 164). This skill outlines the mandatory steps to protect electronic Protected Health Information (ePHI), including conducting thorough risk analyses, deploying administrative, physical, and technical safeguards, managing Business Associate Agreements (BAAs), and preparing for breach notifications and OCR audits. Essential for Covered Entities and Business Associates.

This skill outlines the implementation of advanced runtime defenses for production Large Language Model (LLM) applications. It covers using multiple industry-leading guardrail systems—including Llama Guard, NeMo Guardrails, and LLM Guard—to detect and block adversarial attacks such as prompt injection, jailbreaks, and toxic content. It provides a comprehensive defense-in-depth strategy for ensuring model safety and output integrity in real-world deployments.

Provides a comprehensive workflow and tooling (GuardDog) to triage npm packages and dependency trees for signs of malicious activity. It focuses on static analysis of install scripts, detecting credential exfiltration, reverse shells, and worming behavior, thereby safeguarding against software supply-chain attacks.

Stratus Red Team is an open-source tool designed for detection engineering and purple teaming. It programmatically detonates granular, documented offensive techniques across major cloud platforms (AWS, Azure, GCP, and Kubernetes). It validates existing security detections (like CloudTrail/GuardDuty) by simulating real attacker activity in a controlled, reversible environment. The tool ensures deterministic lifecycles, guaranteeing that all created resources are cleaned up after testing.