yooreekz/yooreekz-first-assistant icon
public
Published on 5/5/2025
My First Assistant

This is an example custom assistant that will help you complete the Python onboarding in VS Code. After trying it out, feel free to experiment with other blocks or create your own custom assistant.

Rules
Prompts
Models
Context
ollama deepseek-r1 8b model icon

deepseek-r1 8b

ollama

ollama nomic-embed-text latest model icon

nomic-embed-text latest

ollama

ollama qwen2.5-coder 1.5b model icon

qwen2.5-coder 1.5b

ollama

You are a Python coding assistant. You should always try to - Use type hints consistently - Write concise docstrings on functions and classes - Follow the PEP8 style guide
Pythonhttps://docs.python.org/3/
PyTorchhttps://pytorch.org/docs/stable/index.html
Next.jshttps://nextjs.org/docs/app
Zodhttps://zod.dev/
Pandashttps://pandas.pydata.org/docs/
NumPyhttps://numpy.org/doc/stable/
Reacthttps://react.dev/reference/
Rust docshttps://doc.rust-lang.org/book/
Vercel AI SDK Docshttps://sdk.vercel.ai/docs/
Streamlithttps://docs.streamlit.io
FastAPIhttps://fastapi.tiangolo.com/

Prompts

Learn more
Write Cargo test
Write unit test with Cargo
Use Cargo to write a comprehensive suite of unit tests for this function
New Module
Create a new PyTorch module
Please create a new PyTorch module following these guidelines:
- Include docstrings for the model class and methods
- Add type hints for all parameters
- Add basic validation in __init__
Page
Creates a new Next.js page based on the description provided.
Create a new Next.js page based on the following description.
Exploratory Data Analysis
Initial data exploration and key insights
Create an exploratory data analysis workflow that includes:

Data Overview:
- Basic statistics (mean, median, std, quartiles)
- Missing values and data types
- Unique value distributions

Visualizations:
- Numerical: histograms, box plots
- Categorical: bar charts, frequency plots
- Relationships: correlation matrices
- Temporal patterns (if applicable)

Quality Assessment:
- Outlier detection
- Data inconsistencies
- Value range validation

Insights & Documentation:
- Key findings summary
- Data quality issues
- Variable relationships
- Next steps recommendations
- Reproducible Jupyter notebook

The user has provided the following information:
RAG Pipeline Design
Comprehensive retrieval-augmented generation system design
Design a RAG (Retrieval-Augmented Generation) system with:

Document Processing:
- Text extraction strategy
- Chunking approach with size and overlap parameters
- Metadata extraction and enrichment
- Document hierarchy preservation

Vector Store Integration:
- Embedding model selection and rationale
- Vector database architecture
- Indexing strategy
- Query optimization

Retrieval Strategy:
- Hybrid search (vector + keyword)
- Re-ranking methodology
- Metadata filtering capabilities
- Multi-query reformulation

LLM Integration:
- Context window optimization
- Prompt engineering for retrieval
- Citation and source tracking
- Hallucination mitigation strategies

Evaluation Framework:
- Retrieval relevance metrics
- Answer accuracy measures
- Ground truth comparison
- End-to-end benchmarking

Deployment Architecture:
- Caching strategies
- Scaling considerations
- Latency optimization
- Monitoring approach

The user's knowledge base has the following characteristics:
API route inspection
Analyzes API routes for security issues
Review this API route for security vulnerabilities. Ask questions about the context, data flow, and potential attack vectors. Be thorough in your investigation.
Client component
Create a client component.
Create a client component with the following functionality. If writing this as a server component is not possible, explain why.

Context

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@code
Reference specific functions or classes from throughout your project
@docs
Reference the contents from any documentation site
@diff
Reference all of the changes you've made to your current branch
@terminal
Reference the last command you ran in your IDE's terminal and its output
@problems
Get Problems from the current file
@folder
Uses the same retrieval mechanism as @Codebase, but only on a single folder
@codebase
Reference the most relevant snippets from your codebase

No Data configured

MCP Servers

Learn more

Tavily Search

npx -y tavily-mcp@0.1.4

Browser MCP

npx -y @browsermcp/mcp@latest

Memory

npx -y @modelcontextprotocol/server-memory