Skill UI

This skill provides comprehensive tools for managing Apollo.io contact data governance and compliance. It supports critical data lifecycle tasks, including executing GDPR Subject Access Requests (SAR), enforcing the Right to Erasure, implementing data retention policies, and performing field-level encryption. Ideal for legal, data privacy, or engineering teams handling PII.

A comprehensive guide to building robust, production-ready GraphQL APIs. This skill covers schema design (SDL/code-first), implementing efficient resolvers with DataLoader for batching, handling real-time subscriptions via WebSockets, and integrating field-level authorization and complexity limiting. Supports major runtimes like Node.js and Python.

Provides comprehensive tools for managing enriched lead data in compliance with global privacy regulations like GDPR and CCPA. This skill guides practitioners through data classification (identifying PII sensitivity), input validation, deduplication, implementing data retention metadata, and anonymizing sensitive fields for secure reporting and analytics.

An expert architect specializing in designing, optimizing, and scaling entire data layers from inception (greenfield) to re-architecture. Proficient in selecting the optimal database technology (SQL, NoSQL, Graph, Time-series), designing robust schemas, implementing sophisticated indexing strategies, and planning complex migration paths. Suitable for defining data storage solutions that meet high performance, scalability, and data integrity requirements.

A comprehensive guide detailing best practices for optimizing GraphQL queries against external APIs, demonstrated using Fireflies.ai. Learn advanced techniques such as requesting minimum required fields (field selection), implementing robust caching strategies (LRU/Redis), and managing rate limits through controlled batch processing and pagination. This ensures stable, fast, and scalable data retrieval.

This skill provides comprehensive guidelines for handling sensitive people datasets from Juicebox AI. It covers critical data classification (PII, search results), required technical controls (AES-256 encryption, field-level masking), and adherence to international privacy regulations like GDPR and CCPA. It ensures users implement lawful data processing, proper consent tracking, and secure data export mechanisms.

This skill demonstrates the multi-model pattern for creating robust and clean API contracts using Pydantic. It guides the creation of separate models for creation requests (Create), updates (Update), responses (Response), and database documents (InDB), ensuring type safety and clear data validation for Python backends. It also covers best practices like handling camelCase aliases and optional fields.

A specialized security testing skill designed to identify excessive data exposure in REST or GraphQL APIs, adhering to OWASP API3:2023 guidelines. It works by intercepting raw API responses and systematically comparing the returned data against what the frontend UI actually displays. This helps auditors detect leaked PII, internal identifiers, debug fields, or other sensitive business data that should have been filtered out by the endpoint response. Use cases include auditing microservice boundaries, assessing mobile API responses designed for multiple clients, and verifying proper respons...

Perform comprehensive security audits on Bluetooth Low Energy (BLE) devices, identifying potential vulnerabilities in IoT, healthcare, and smart home applications. This skill uses Python to discover devices, enumerate GATT services, and flag unencrypted or unauthenticated read/write access to sensitive data fields, helping organizations validate security controls.

This script automates the testing of API endpoints for mass assignment (over-posting) vulnerabilities, adhering to OWASP API3:2023 guidelines. It systematically injects undocumented, privileged fields (like 'role', 'isAdmin', 'balance', 'price') into request bodies of typical endpoints (e.g., profile updates, order creation). It checks if the server binds these unexpected fields to the data model without proper filtering, potentially allowing unauthorized privilege escalation or data manipulation.

Generates implementation-ready JSON-LD schema markup for 10 types (e.g., FAQPage, Product, Article). It validates all fields against Google rich result eligibility rules, flags missing data with fix instructions, and provides clean, ready-to-paste script blocks to optimize search engine visibility and achieve rich results.

This skill demonstrates how to use Playwright MCP to programmatically automate the process of inputting data into a web form. It covers various input types, including text fields, date selection, time setting, and file uploads. The process simulates realistic user interaction for data entry or form submission testing, emphasizing the ability to fill data without final submission for review purposes.