Skill UI

This skill manages the end-to-end Navan expense reporting workflow. It allows users to retrieve detailed transaction data via API, automate multi-level approval workflows based on configured policies, and map expenses to specific General Ledger (GL) codes. It is designed to generate journal entry payloads for seamless synchronization with major accounting systems like NetSuite, Xero, and QuickBooks, streamlining financial reconciliation.

This skill integrates the Notion API directly into CI/CD pipelines (e.g., GitHub Actions). It automates critical developer workflows such as synchronizing release notes and changelogs, updating deployment status trackers, creating incident reports automatically, and reading feature flags for configuration management. It is essential for modern DevOps practices and improving documentation synchronization.

This skill provides a comprehensive, production-grade reference architecture for building robust Notion integrations. It defines a multi-layered structure, including client singletons, repository patterns, service orchestration, and caching mechanisms. It is essential for migrating ad-hoc API calls to scalable, event-driven, and highly reliable enterprise applications that incorporate rate limiting, sophisticated error handling, and comprehensive testing strategies.

A comprehensive guide detailing the reference architecture for connecting to OneNote via the Microsoft Graph API. It covers the distinct API paths, permission models, and object hierarchies for personal (OneDrive), SharePoint, and Microsoft 365 Group notebooks, ensuring seamless design for multi-tenant, enterprise-level integrations.

This comprehensive bundle collects all necessary diagnostic artifacts for troubleshooting Palantir Foundry issues. It gathers SDK versions, environment variables (with secrets automatically redacted), API connectivity status, and recent application error logs. This structured output is essential for creating detailed, actionable support tickets when reporting persistent platform malfunctions.

This skill performs a zero-context verification audit, ensuring that every quantitative claim, comparison, and scope statement within a research paper precisely matches the provided raw result files. It is designed to eliminate confirmation bias, catching discrepancies such as incorrect rounding, cherry-picked best seeds, or misreported performance deltas before publication. Ideal for validating paper-to-evidence fidelity.

A comprehensive toolkit for advanced web intelligence workflows. It facilitates deep research, structured data enrichment, URL extraction, entity discovery, and continuous web monitoring. Ideal for scientific topics, academic source discovery, and generating exhaustive, evidence-based reports.

This skill performs rigorous mathematical proof verification using an adversarial, cross-model review process. It reads a LaTeX proof, systematically identifies logical gaps (e.g., unjustified assertions, quantifier errors) and theoretical flaws (e.g., illegal interchanges, non-uniform convergence). It then iteratively fixes these gaps with full derivations, re-reviews, and generates a comprehensive audit report, ensuring mathematical rigor and completeness. Use this when seeking deep, academic verification of a theory paper.

This skill facilitates an interactive Quality Assurance (QA) session. Users can conversationally describe encountered bugs or issues. The agent clarifies the problem, explores the codebase for context and domain language, and then meticulously files durable GitHub issues. It supports both single-issue reports and breaking down complex problems into multiple, independently verifiable tickets, ensuring developers receive actionable, high-quality reports written from the user's perspective.

A comprehensive guide for diagnosing and reducing high memory consumption in Qdrant. This resource is crucial when dealing with reports of 'memory leak', 'out of memory', or excessive RAM growth. It details how Qdrant manages resident memory and OS page cache, and provides advanced techniques such as quantization, using float16/int8 data types, and strategically storing components on disk (like HNSW indexes or sparse vectors) to minimize the memory footprint and ensure stable, scalable operation.

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.

This skill provides integration patterns for the Ramp Developer API, enabling comprehensive data handling for corporate cards and expense management. It covers the full workflow, including OAuth2 authentication, retrieving card details, and syncing financial data. Use it for automating expense reports, accounting reconciliation, and building robust financial SaaS workflows.