Skill UI

This utility executes an autonomous, iterative loop, simulating a comprehensive agent workflow. It systematically manages tasks by checking current status, predicting the optimal next action using specialized tools, executing the required task (e.g., coding, testing), logging the progress, and scheduling the next iteration. It supports task discovery from multiple sources, including team tasks, swarm tasks, and file checklists, ensuring continuous, automated progress towards a defined goal.

This skill provides a rigorous, structured method for inspecting animated 3D characters, rigs, and motion retargeting in Blender. It moves beyond visual evidence (screenshots) by extracting and comparing structured data points such as bone transformations, bounding box changes, ground contacts, and axis conventions. Ideal for diagnosing subtle animation flaws like foot sliding, ground penetration, or incorrect orientation that are invisible in still images.

This skill provides comprehensive web browser automation capabilities for agents. It utilizes AI-optimized snapshots, reducing context size by 93% by using element references instead of full DOM. Functions include navigation, interactive element extraction, form filling, data scraping, and state management across multiple isolated sessions. Ideal for complex web testing and data extraction workflows.

This skill performs an adversarial audit of web application authentication flows. It systematically probes for critical security vulnerabilities such as missing CSRF protection, insecure session cookies (lacking Secure/HttpOnly flags), risky cross-origin redirects, and OAuth misconfigurations. It generates a structured report detailing findings and severity levels, making it ideal for pre-deployment security audits and regression testing.

Automates the process of filling out web forms using a structured field map (field_name → value). This tool supports using stored templates for known forms, or falling back to analyzing the page accessibility snapshot if no template exists. It includes mandatory PII screening (aidefence_has_pii) and handles form submission, making it ideal for automating sign-ups, checkouts, and data entry tasks.

This powerful utility automates the initial authentication process against a target website. It captures the resulting session cookies, sanitizes them rigorously using AIDefence to protect raw secrets, and then securely vaults a reusable cookie handle. This enables subsequent automation skills to seamlessly continue operations using the authenticated session context without needing to re-run the entire login flow.

This skill is a compatibility shim for the older browser-scrape function. It is deprecated and advises users to migrate to the more robust `browser-extract` skill. The new skill offers advanced features like cognitive containers, PII detection, and automatic selector management for reliable web scraping.

Compares two recorded browser sessions step-by-step by matching steps via shared step IDs. It performs both pixel-level diffing on screenshots (for visual regression) and node-by-node diffing on accessible DOM snapshots (for structural changes). Ideal for visual regression testing, comparing A/B flow variants, and verifying replay consistency in UI development.

A comprehensive guide to building highly performant and reusable UIs across multiple platforms (Android, iOS, Desktop, Web) using Compose Multiplatform and Jetpack Compose. It details advanced patterns for state management (Single State Object, Event Sink), type-safe navigation, slot-based composables, platform adaptation (Expect/Actual), and crucial performance optimization techniques.

This tool detects cost regressions by comparing two cost-summary JSON snapshots (baseline vs. current). It is essential for PR-gate workflows, checking for unexpected spending increases using three orthogonal signals: total percentage change, absolute dollar increase, and disproportionate growth in specific token classes (e.g., cache writes).

This tool guides the creation of actionable monitoring dashboards for observability platforms like Grafana and SigNoz. Instead of merely displaying raw metrics, it focuses on structuring data to answer critical operational questions: Is the system healthy? Where are the bottlenecks? What changes occurred? And what action should be taken? It transforms raw metrics into decision-making tools.

Use this skill for optimizing large-scale data ingestion, ETL, and data warehouse loading. It helps diagnose bottlenecks (such as extraction speed, network transfer, or loading time) and implements best practices like idempotent writes, native cloud scans, and checkpointing to achieve maximum processing speed while strictly guaranteeing data integrity and traceability.