Skill UI

A comprehensive checklist for deploying Shopify apps to production or submitting to the App Store. It covers critical areas including API versioning, mandatory GDPR compliance webhooks, webhook security best practices, rate limit resilience, and App Store listing requirements. Use this guide when preparing for a major launch or auditing existing compliance gaps to ensure maximum stability and security.

This skill provides comprehensive guidance on implementing security best practices for Shopify applications. It covers critical topics such as secure API credential storage, verifying incoming webhooks using HMAC signatures, enforcing least-privilege access scopes, and setting Content Security Policies (CSP). Use this guide when building, auditing, or scaling a secure e-commerce integration.

This guide identifies and provides solutions for common anti-patterns and mistakes when working with Snowflake. It covers best practices in SQL writing, warehouse resource management, data loading strategies (e.g., using MERGE), and access control setup. It is essential for auditing existing deployments, onboarding new users, or performing code reviews to ensure cost efficiency and data integrity.

This guide details essential security best practices for Snowflake data warehouses. It covers implementing network policies, managing key rotation, enabling Multi-Factor Authentication (MFA), and securing credentials using secret managers. Use this comprehensive resource to audit security configurations, restrict network access, and enforce least-privilege access within your Snowflake environment.

This comprehensive, guided 4-phase workflow helps teams establish clear identity, boundaries, and strategic positioning. It guides users through absorbing existing context, auditing current capabilities versus claimed responsibilities, articulating a defined mission, and finally achieving stakeholder alignment. Use this framework when starting a new role, inheriting ambiguity, or needing to define clear operational boundaries.

This utility conducts a thorough audit of project documentation against the current codebase to ensure complete consistency. It supports 'delta' (detecting changes since merge-base) or 'full' auditing modes. By utilizing Impact Mapping and verifying cross-reference pairs, it identifies outdated specs, missing documentation, or inconsistent references across the entire project ecosystem.

This skill provides a comprehensive framework for security auditing LLM agents that possess external tools (file system access, command execution, network calls). It employs advanced dialogue probing techniques—such as command injection, path traversal, and SSRF attempts—to identify vulnerabilities where the agent might be induced to execute unexpected or malicious code, or access sensitive resources. Essential for red teaming and securing agent functionalities.

This guide details the process of deploying and configuring the WizTelemetry Data Pipeline using Vector. It is essential for establishing data collection, transformation, and routing capabilities for comprehensive observability data, including logs, auditing records, events, and notifications within a Kubernetes environment.

This guide details comprehensive security best practices for Webflow Data API v2. It covers crucial topics such as selecting the correct token type, implementing least privilege access scopes, secure secret rotation, and verifying webhook signatures. Use this knowledge when building or auditing Webflow integrations to ensure robust data security and system reliability.

This component is an essential extension for KubeSphere Observability Platform, designed for comprehensive collection, processing, and storage of Kubernetes and KubeSphere audit events. It supports various sinks, including OpenSearch and Doris, and provides an API for querying historical audit data, ensuring robust auditing capabilities for platform operations.

This tool functions as a post-task epilogue, designed to audit and record the entire research journey. It scans the conversation history at the end of a coding or research session to extract critical research artifacts, including decisions, experiments, dead ends, claims, heuristics, and major pivots. It systematically writes this provenance data into the structured `ara/` directory, ensuring a faithful and auditable trace of how the project truly evolved.

This framework enforces high output quality, intellectual honesty, and continuous improvement across all AppSec agents. It mandates structured processes, including self-critique loops, anti-rationalization guards, and self-reflection quality gates (≥8 scoring). Applicable during code review, SAST, SCA, and threat modeling, it ensures rigorous and verifiable security analysis.