Skill UI

A comprehensive guide for developers on creating custom bulk actions for a Headless CMS. Learn how to implement the `EntriesBulkAction` interface using `loadData` (for fetching batches) and `processData` (for performing updates). This allows developers to add administrative batch tasks, such as applying discounts or transforming entries, directly from the CMS admin UI, while managing background task convergence and complex field filtering.

This skill helps secure Large Language Model (LLM) and AI deployments against various threats including prompt injection, data exfiltration, model theft, and supply chain attacks. It covers implementing guardrails, output filtering, PII scrubbing, and API security measures to ensure compliance with standards like SOC2 or ISO 27001.

Build TypeScript applications with Azure AI Search SDK for vector, hybrid, and semantic search, including index management, document indexing, filtering, facets, and autocomplete.

Scan container images for vulnerabilities and misconfigurations using tools like Trivy, Grype, and Docker Scout. Integrates with CI/CD pipelines and cloud registries (ECR, ACR, GCR) to ensure compliance and security before deployment. Supports filtering by severity and generating SARIF reports.

Expert guidance for using ffuf in authorized web penetration testing: content discovery, subdomain and parameter fuzzing, authenticated raw requests, auto-calibration, filtering, and result analysis.

This skill covers configuring host-based and cloud firewalls using iptables, nftables, and UFW. It includes implementing network segmentation, traffic filtering, and security zone policies. Suitable for securing server perimeters, migrating firewall technologies, and responding to security incidents. Requires Linux root access and network knowledge.

Query structured food data for nutrition facts, food comparisons, portion conversions, classification filtering, and database-driven dietary analysis. Use when tasks require retrieval or analysis of food records rather than free-text nutrition advice.

This skill guides the creation and maintenance of a `.geminiignore` file. By systematically filtering out machine-generated noise—such as build artifacts, dependency lock files, logs, and caches—it significantly optimizes the AI agent's context window. This process improves processing speed and, critically, reduces token consumption costs (FinOps).

This comprehensive tool automates nearly every aspect of Google Sheets management. Users can programmatically read, write, update, and append data across multiple ranges. Key functionalities include creating new spreadsheets, managing tabs (renaming, hiding), applying cell formatting, filtering data, performing lookups, and performing 'upsert' operations (update or insert records based on a unique key). Ideal for integrating spreadsheet data into automated workflows.

Explore and extract Hugging Face datasets using the Dataset Viewer API. Perform read-only operations like validating datasets, listing splits, previewing rows, paginating, searching text, filtering, retrieving parquet links, and getting statistics. Ideal for data exploration and retrieval tasks.

Create, configure, and manage Hugging Face Hub datasets. Supports SQL querying, transformation, filtering, exporting, and pushing subsets or custom datasets to the Hub.

This skill enforces a rigorous data validation protocol by establishing hard boundaries at every point data enters the system (API requests, user input, environment variables, webhooks, etc.). It mandates a four-phase process: detection, trust classification, mandatory filtering (schema validation, sanitization, type checking), and final verification. This prevents untrusted data from reaching core business logic, mitigating risks like SQL injection and XSS.