Profiling Tables
This skill analyzes tabular data to identify patterns and relationships, offering insights for data exploration and understanding.
Install on your platform
We auto-selected Claude Code based on this skill’s supported platforms.
Run in terminal (recommended)
claude mcp add profiling-tables npx -- -y @trustedskills/profiling-tables
Or manually add to ~/.claude/settings.json
{
"mcpServers": {
"profiling-tables": {
"command": "npx",
"args": [
"-y",
"@trustedskills/profiling-tables"
]
}
}
}Requires Claude Code (claude CLI). Run claude --version to verify your install.
About This Skill
What it does
The profiling-tables skill enables AI agents to analyze and summarize data from tables, identifying patterns, trends, and key insights. It can extract metadata such as column types, value distributions, and relationships between fields, making it useful for understanding the structure and content of tabular datasets.
When to use it
- To quickly understand the contents and structure of a new dataset before further analysis.
- When preparing data for visualization or modeling by identifying missing values or inconsistencies.
- During exploratory data analysis (EDA) to generate summaries that guide decision-making.
Key capabilities
- Extract metadata from tables, including column types and value distributions.
- Identify patterns and relationships between fields in the table.
- Generate high-level summaries of dataset contents for quick understanding.
Example prompts
- "Analyze this table and summarize its structure and key insights."
- "What are the most common values in each column of this dataset?"
- "Identify any missing data or inconsistencies in this table."
Tips & gotchas
- Ensure that the input is a well-formatted table for accurate results.
- This skill may not handle very large tables efficiently, so consider sampling or chunking data if needed.
Tags
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