Skill UI

This skill provides a comprehensive framework for the continuous self-improvement of makepad-skills. It outlines automatic skill triggering via hooks, context-aware skill routing, and a structured process for capturing new patterns, error solutions, and best practices. It ensures the entire skill library remains robust and up-to-date throughout the development lifecycle.

Generates and reviews Odoo XML definitions for Form, List, Kanban, Search, Calendar, and Graph views across versions 14–17, handling visibility, groups, domains, contexts, and widget rules with migration-aware syntax so you can deliver production-ready view XML.

Attempts to expose an open-source context resource, but the current skill metadata only yields a 404 response, indicating the referenced content is unavailable or missing from the system.

Varlock provides secure, default environment variable management, ensuring that sensitive secrets (like API keys and passwords) are never exposed in logs, terminal output, or the AI context. It validates environments, reads schemas, and executes commands in a secure manner, promoting best practices for handling secrets in modern development workflows.

Automates project-aware diary maintenance by recording status from conversations, refreshing context, extracting global and project progress, and syncing to Notion/Obsidian while enforcing strict workflow steps.

This utility converts a single, high-level objective into a comprehensive, step-by-step build plan suitable for complex, multi-agent, or multi-session engineering projects. It automatically handles dependency mapping, detects parallel steps, and structures each step with self-contained context briefs, ensuring any new agent can execute it without prior knowledge. Ideal for large-scale refactoring or feature development spanning multiple PRs.

A comprehensive collection of six expert-level, structured workflows designed to elevate AI assistance from ad-hoc querying to repeatable, production-grade engineering practices. Users can evaluate prompts, design RAG architectures, plan context budgets, run security audits, build eval harnesses, and coach product strategy.

This skill details the architecture and implementation of an automated Indicator of Compromise (IOC) enrichment pipeline using OpenCTI. It demonstrates how to connect OpenCTI to various external threat intelligence services (like VirusTotal, Shodan, AbuseIPDB) to automatically gather context, correlate indicators, and assign confidence scores. This is crucial for enhancing security monitoring and prioritizing threats for cyber analysts.

This guide details how to build automated threat intelligence enrichment pipelines within Splunk Enterprise Security. By leveraging the Threat Intelligence Framework, users can ingest, normalize, and correlate Indicators of Compromise (IOCs) from diverse external sources (such as TAXII, CSV, and custom APIs). The process uses KV Store collections and lookup searches to enrich raw security events with critical threat context, significantly reducing triage time for SOC teams.

This guide outlines how to implement Google Cloud Identity-Aware Proxy (IAP) to enforce zero-trust, identity-based access control across various Google Cloud services (App Engine, Cloud Run, GKE, Compute Engine). It details configuring per-request authentication, context-aware policies (like device posture and location), and programmatic access management for highly secure internal applications.

This skill fetches the latest, live documentation and code examples for specific libraries and frameworks (e.g., Next.js, React, Prisma). Instead of relying on static or outdated training data, it utilizes the Context7 MCP to provide accurate, up-to-date answers for setup questions, API references, and code generation based on current best practices.

This guide details the implementation of robust API abuse detection mechanisms. It covers advanced rate limiting techniques, such as the Token Bucket and Sliding Window algorithms, to defend APIs against DDoS attacks, brute force attempts, and credential stuffing. It emphasizes using distributed stores like Redis for accurate, scalable, and adaptive security controls in an API gateway context.