prompt-engineering-patterns
Master advanced prompt engineering techniques to maximize LLM performance, reliability, and controllability in production applications.
Discover reusable agent skills, browse implementation details, and find the right skill for your workflow.
139 skills found
Master advanced prompt engineering techniques to maximize LLM performance, reliability, and controllability in production applications.
Evaluate code generation models using BigCode Evaluation Harness. Benchmarks include HumanEval, MBPP, and MultiPL-E with pass@k metrics for multi-language coding models.
Process and generate multimedia with Google Gemini. Analyze audio, images, videos, and PDFs with high-context windows. Supports transcription, visual QA, OCR, and AI-driven image creation.
Build production-grade RAG systems using vector databases, semantic search, and LangGraph to ground LLMs in external knowledge.
Implement adaptive learning with ReasoningBank for pattern recognition, strategy optimization, and continuous improvement in AI agents.
Design professional-grade brand identities using geometric primitives, negative space, and flat vector-style aesthetics via AI-driven branding logic.
Analyze AppWorld task failures to extract specific API patterns and generate actionable playbook bullets with concrete code examples.
Normalizes testing defect logs by correcting typos, abbreviations, and ambiguous descriptions based on product-specific codebooks and station validation.
Robot perception system design, configuration, and optimization for cameras, LiDAR, and sensor fusion pipelines. Includes camera calibration, 3D reconstruction, and production deployment best practices.
Applies cognitive science frameworks for creative thinking to generate genuinely novel research directions in computer science and AI.
A structured prompting framework to transform casual inputs into professional, modular LLM prompts with persona, context, task, format, and guardrails.
Generate realistic virtual product try-on visualizations to help customers evaluate fit, drape, and scale before purchasing.