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314 skills found
Advanced QE reporting, quality dashboards, and predictive analytics for test metrics, code coverage, and deployment readiness to drive data-informed quality decisions.
Seamlessly toggle between live and mocked external dependencies using the Model Context Protocol (MCP) for autonomous development environments.
Applies current Go testing best practices, including concurrent testing, mocking, and table-driven design for robust software development.
Implement LlamaExtract for robust structured data extraction from PDF, DOCX, and PPTX files using Pydantic schemas.
Automate pytest execution with built-in environment verification, failure analysis, coverage reporting, and intelligent test discovery.
Full-stack automated paper writing pipeline from research narrative to polished LaTeX/PDF.
Automated quality assurance system that validates markdown deliverables against defined checklists for PB-000 market research workflows.
Validates cryptographic implementations using the Google Wycheproof test vector suite to detect security edge cases and known vulnerabilities.
Keep your technical specifications, test suites, and source code perfectly synchronized during AI-assisted development.
Automated guidance for implementing property-based testing (PBT) in software and smart contracts to improve test coverage and edge case detection.
Anthropic Claude integration patterns: streaming, RAG with pgvector, tool use, model selection (Haiku/Sonnet/Opus), prompt caching, and cost management for AI-powered engineering.
Automates the lifecycle management of ephemeral Neon PostgreSQL databases for testing, CI/CD, and rapid prototyping workflows.