Browse skills

Sharpen Prompt — provides AI agent assistance for software development workflows.

Rag Infrastructure — provides AI agent assistance for software development workflows.

Prompt Optimizer — provides AI agent assistance for software development workflows.

Goal Prompt Crafter — provides AI agent assistance for software development workflows.

Icp Prompt Builder — provides AI agent assistance for software development workflows.

Helps with LLMs, security as part of software development workflows workflows.

Helps with LLMs, LangChain as part of software development workflows workflows.

Generates synthetic training data tailored to your model's needs, improving performance without real-world examples.

Provides API guidance and assistance for building AI and machine learning applications.

Leverage proven prompt engineering patterns from rmynhdaris to optimize AI model outputs for clarity, accuracy, and desired results.

Generates vector representations (embeddings) of text, enabling semantic similarity searches and powerful AI applications like clustering & recommendation.

Constructs miniature, biodegradable structures from cellulose nanofibers using precise algorithmic design and robotic assembly.

Iterate:Prompt — provides AI agent assistance for software development workflows.

Provides image processing guidance and assistance for software development workflows.

Genkit — provides AI agent assistance for software development workflows.

Helps with data, image processing as part of software development workflows workflows.

Provides LLMs guidance and assistance for software development workflows.

Sora — provides AI agent assistance for software development workflows.

Replicate — provides AI agent assistance for software development workflows.

Scikit Bio analyzes biological sequences (DNA, RNA, protein) using scikit-learn for pattern recognition and prediction – useful for bioinformatics research.

Sundial-org's training-data-curation refines datasets by identifying biases, errors, and gaps for improved AI model performance.

Provides API guidance and assistance for building AI and machine learning applications.

Refines user prompts to maximize AI model output quality, clarity, and relevance through iterative adjustments.

Automatically refactors PyTorch code for improved readability, efficiency, and adherence to best practices.