Skill UI

A comprehensive skill for managing sensitive data within Miro boards. It covers detecting Personally Identifiable Information (PII) like emails, phone numbers, and credit cards, ensuring compliance with regulations such as GDPR and CCPA. Functionality includes robust data export for Data Subject Access Requests (DSAR), implementing data retention policies, and automatically redacting PII in logs to maintain maximum data security.

Configure comprehensive, enterprise-grade access control for Miro via REST API v2. This module manages organization structure, team membership, and granular board permissions (RBAC). It supports advanced features like automated user provisioning using SCIM 2.0 and SSO integration, making it essential for implementing secure, scalable collaboration platforms in large corporate environments.

A comprehensive guide for migrating complex Miro board data across teams and organizations. It covers exporting board content—including items, connectors, tags, and members—to structured JSON files, and bulk-importing data into Miro using the REST API v2. Ideal for re-platforming from competing whiteboard tools or updating large-scale, legacy v1 integrations.

This skill guides the identification and search for specialized crew members (such as production controllers, costume designers, music directors) in South Asian cinema. It is essential when a question focuses on technical roles rather than just the director or lead actors. By using specific search queries on reliable databases (like IMDb or Wikipedia) after identifying the film, users can efficiently locate detailed production credits.

This comprehensive workflow provides core CRUD (Create, Read, Update, Delete) operations for Notion integrations. It allows users to perform complex database queries using nested filters (AND/OR) across various property types (select, date, number, etc.). Furthermore, it facilitates the structured creation and updating of pages, making it essential for automating data management, content generation, and complex information retrieval within Notion.

This skill provides robust methods for handling sensitive data within Notion integrations. It systematically detects Personally Identifiable Information (PII), such as emails, phone numbers, SSNs, and credit cards, within both page properties and rich text content. Users can implement data redaction mechanisms before logging or exporting, ensuring the data handling process fully complies with major privacy regulations like GDPR and CCPA.

A comprehensive guide detailing advanced offensive fuzzing methodologies. It covers the full lifecycle from target identification (parsers, network protocols, kernels) to tool selection (AFL++, libFuzzer, Honggfuzz, syzkaller), building harnesses, curating seed corpora, executing fuzz campaigns, and finally, performing crash triage and vulnerability analysis. Essential for security researchers and embedded systems developers.

Zero-context verification system that checks every number, comparison, and scope claim in research papers against raw result files. Uses a fresh cross-model reviewer with no prior context to prevent confirmation bias. Ideal for academic integrity, paper submission, and ensuring paper-to-evidence fidelity before publication.

This guide provides a complete, end-to-end workflow for implementing Know Your Customer (KYC) identity verification using the Persona API. It details both backend implementation (creating inquiries, handling completion callbacks, resuming flows) and frontend integration (embedding the verification UI into web applications). Ideal for secure user onboarding and identity validation processes.

This guide provides a comprehensive walkthrough of the identity verification lifecycle using the Persona REST API. It covers the full process: creating a new inquiry, generating hosted or embedded verification URLs, polling the inquiry status until completion, and finally retrieving detailed KYC results. This is essential for developers building secure, automated user onboarding, and identity verification flows.

Provides comprehensive strategies for migrating embedding models within Qdrant. This guide covers zero-downtime alias swapping, side-by-side A/B testing, and transitioning from dense to hybrid search. It is essential for production environments requiring continuous availability when updating models, dimensions, or switching providers.

A comprehensive guide to diagnosing and enhancing search relevance within Qdrant. This skill addresses reported issues such as low precision, low recall, or irrelevant matches. It guides users through determining if the problem lies in the embedding model, Qdrant configuration, or the query strategy. Techniques covered include optimizing chunk splitting, tuning HNSW parameters, implementing hybrid search, and utilizing reranking for superior result quality.