Data Cog - Your Data Has Answers, CellCog Finds Them

Your data has answers. CellCog asks the right questions. #1 on DeepResearch Bench (Feb 2026) + frontier coding agent.

Most AI tools return code when you ask about data. CellCog returns answers — actual charts, clean datasets, statistical reports, and visual dashboards. Upload messy CSVs with a minimal prompt, and CellCog's coding agent explores your data, finds the patterns, and presents them beautifully. Full Python access for everything from data cleaning to ML model evaluation.

Prerequisites

This skill requires the cellcog skill for SDK setup and API calls.

clawhub install cellcog

Read the cellcog skill first for SDK setup. This skill shows you what's possible.

Quick pattern (v1.0+):

# Fire-and-forget - returns immediately
result = client.create_chat(
    prompt="Analyze this dataset: <SHOW_FILE>/path/to/data.csv</SHOW_FILE>",
    notify_session_key="agent:main:main",
    task_label="data-analysis",
    chat_mode="agent"  # Agent mode for most data work
)
# Daemon notifies you when complete - do NOT poll

What Makes Data-Cog Different

Code as Tool, Not as Output

Other AI tools give you Python code and say "run this." CellCog runs the code for you and delivers the results:

You upload data. You get answers. The code runs behind the scenes.

What Data Work You Can Do

Exploratory Data Analysis

Understand your data fast:

• Dataset Profiling: "Analyze this CSV — distributions, missing values, outliers, correlations, and data quality summary"
• Pattern Discovery: "What patterns and trends exist in this sales data? Surprise me."
• Anomaly Detection: "Find unusual patterns in this server log data — what looks abnormal?"
• Relationship Analysis: "What factors most strongly correlate with customer churn in this dataset?"

Example prompt:

"Analyze this dataset: <SHOW_FILE>/path/to/customer_data.csv</SHOW_FILE>

I don't know much about this data yet. Give me:

• Overview: rows, columns, data types, missing values
• Key distributions and summary statistics
• Most interesting correlations
• Any outliers or data quality issues
• 3-5 insights that jump out

Present findings as an interactive HTML report with charts."

Data Cleaning & Transformation

Wrangle messy data into shape: