runcell (Jupyter AI agent) is an AI copilot built for notebooks. It understands your current kernel stateโvariables, DataFrame schemas, imports, outputsโand proposes the next best cell to move your work forward. With one command, it can draft code, execute it safely, validate the output, and automatically refine on errors. You get productionโquality cells (with comments and docstrings) and a clear audit trail of changes.
Whether youโre exploring data, transforming pipelines, or teaching with notebooks, runcell eliminates โsearchโcopyโpasteโdebugโ loops. It nudges work toward best practices (tests, assertions, checkpoints), and documents decisions for future youโor your teammates. Bring your own LLM keys, keep data in your environment, and control exactly what leaves your notebook.
Core capabilities
Naturalโlanguage to code
Drafts new cells or refactors existing ones from plainโEnglish prompts.
Incorporates notebook context (imports, variables, DataFrame dtypes, shapes) to produce runnable code.
Run, validate, iterate
Executes proposed cells, inspects outputs/exceptions, and autoโfixes common issues (missing imports, dtype mismatches, offโbyโone, plotting errors).
Contextโaware assistance
Explain cell: summarizes what a cell does and why.
Suggest next step: proposes analysis steps, visualizations, or checks based on your artifacts.
Inline docs: inserts comments, docstrings, and markdown rationale.
Environment & reproducibility
Detects missing packages and (optionally) generates a safe install cell; can export requirements.txt or environment.yml.
Data & visualization helpers
Quick EDA: profiling, missingโvalue maps, summary stats.
Transformations: joins, groupby, window ops, feature engineering.
Visuals: histograms, pairplots, line/bar charts, residual plots, interactive charts (e.g., Plotly).
Works smoothly with pandas, numpy, polars, matplotlib/plotly, and visualization helpers like pygwalker.
Runcell's answer
Runcell is the AI Agent designed for Jupyter users. It is not a simple chatbot, but an agent that can take control of your jupyter and work for you.
Runcell's answer
Comparing with Code agent, like cursor, claude code, which are designed for software enginner, those agent does not understand data, visualization, very well. And when they coding, they directly generate all code without considering how the data distribute, what is the result of previous cells execution which are important for data science.
Based on our record, Augment Code seems to be more popular. It has been mentiond 3 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Augment Code Works in VS Code and JetBrains. Built for coders. Can execute code, run terminal, find issues, and analyze the code. Find performance optimization ideas in production. - Source: dev.to / 4 months ago
At Augment (https://augmentcode.com) we were one of the partner who tested 3.7 pre-launch. And it has been a pretty significant increase in quality and code understanding. Happy to answer some questions FYI, We use Claude 3.7 has part of the new features we are shipping around Code Agent & more. - Source: Hacker News / 7 months ago
IMHO, I would agree with you. I think chat is a nice intermediary evolution between the CLI (that we use every day) and whatever comes next. I work at Augment (https://augmentcode.com), which, surprise surprise, is an AI coding assistant. We think about the new modality required to interact with code and AI on a daily basis. Beside increase productivity (and happiness, as you don't have to do mundane tasks like... - Source: Hacker News / 8 months ago
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