Databases

Token-efficient library documentation fetcher using Context7 MCP with 86.8% token savings through intelligent shell pipeline filtering. Fetches code examples, API references, and best practices for JavaScript, Python, Go, Rust, and other libraries. Use when users ask about library documentation, need code examples, want API usage patterns, are learning a new framework, need syntax reference, or troubleshooting with library-specific information. Triggers include questions like "Show me React hooks", "How do I use Prisma", "What's the Next.js routing syntax", or any request for library/framework documentation.

Performs thorough code reviews with focus on best practices, security, performance, and maintainability. Use this skill when reviewing pull requests, auditing code quality, or getting feedback on implementations.

Conversational GDB debugging for Breenix kernel. Use for interactive debugging sessions - set breakpoints, inspect registers, examine memory, step through code, investigate crashes.

Process external code review feedback with technical rigor. Use when receiving feedback from another LLM, human reviewer, or CI tool. Verifies claims before implementing, tracks disposition.

Database migration patterns using Flyway with versioned SQL scripts

This skill should be used when performing fast iterative kernel debugging, running time-bound kernel sessions to detect specific log signals or test kernel behavior. Use for rapid feedback cycles during kernel development, boot sequence analysis, or feature verification.

Comprehensive software architecture skill for designing scalable, maintainable systems using ReactJS, NextJS, NodeJS, Express, React Native, Swift, Kotlin, Flutter, Postgres, GraphQL, Go, Python. Includes architecture diagram generation, system design patterns, tech stack decision frameworks, and dependency analysis. Use when designing system architecture, making technical decisions, creating architecture diagrams, evaluating trade-offs, or defining integration patterns.

Reviews PostgreSQL code for indexing strategies, JSONB operations, connection pooling, and transaction safety. Use when reviewing SQL queries, database schemas, JSONB usage, or connection management.

This skill should be used when the user asks to "create UI component", "build Blazor page", "add MudBlazor component", "style MudBlazor", "fix CSS isolation", "use ::deep selector", "customize theme", "support dark mode", "migrate MudBlazor v8", "use OnAfterRenderAsync", or needs guidance on Blazor component lifecycle, MudBlazor styling patterns, CSS isolation, theme customization, or offline UI requirements in the MoLibrary framework.

Elasticsearch 5.2 operations using HTTP API - searching, indexing, bulk operations, scroll API, and alias management

Use when debugging the Breenix kernel at assembly or C-level using GDB - investigating CPU exceptions, page faults, triple faults, examining register state during interrupt handling, stepping through boot sequence, analyzing syscall entry/exit paths, debugging context switches, or inspecting memory layout and page tables.

SQL workflow guidelines. Activate when working with SQL files (.sql), database queries, migrations, or SQLFluff.

Comprehensive code review skill for TypeScript, JavaScript, Python, Swift, Kotlin, Go. Includes automated code analysis, best practice checking, security scanning, and review checklist generation. Use when reviewing pull requests, providing code feedback, identifying issues, or ensuring code quality standards.

sqlite-vec extension for vector similarity search in SQLite. Use when storing embeddings, performing KNN queries, or building semantic search features. Triggers on sqlite-vec, vec0, MATCH, vec_distance, partition key, float[N], int8[N], bit[N], serialize_float32, serialize_int8, vec_f32, vec_int8, vec_bit, vec_normalize, vec_quantize_binary, distance_metric, metadata columns, auxiliary columns.

SAP HANA Machine Learning Python Client (hana-ml) development skill. Use when: Building ML solutions with SAP HANA's in-database machine learning using Python hana-ml library for PAL/APL algorithms, DataFrame operations, AutoML, model persistence, and visualization. Keywords: hana-ml, SAP HANA, machine learning, PAL, APL, predictive analytics, HANA DataFrame, ConnectionContext, classification, regression, clustering, time series, ARIMA, gradient boosting, AutoML, SHAP, model storage

LangGraph human-in-the-loop patterns. Use when implementing approval workflows, manual review gates, user feedback integration, or interactive agent supervision.

Use when managing Linear issues, creating tasks from conversations, tracking work items, or querying project status - provides bash scripts to interact with Linear's GraphQL API without writing queries directly (project, gitignored)

BigQuery Expert Engineer Skill - Comprehensive guide for GoogleSQL queries, data management, performance optimization, and cost management

Schema for tracking code review outcomes to enable feedback-driven skill improvement. Use when logging review results or analyzing review quality.

LLM cost tracking with Langfuse for cached responses. Use when monitoring cache effectiveness, tracking cost savings, or attributing costs to agents in multi-agent systems.