CSVBrain enables users to query CSV files using natural language, powered by cloud-based or local AI models without any SQL requirements.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install csv-brain
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install csv-brain using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is CSVBrain Natural Language Data Queries?
CSVBrain is a specialized Node.js tool designed to transform raw tabular data into an interactive, conversational experience. By adding this capability to your Openclaw Skills library, you can parse CSV, TSV, and semicolon-delimited files with zero external dependencies. The tool automatically profiles your data—calculating averages, identifying types, and detecting missing values—to provide the necessary context for AI models to answer complex questions about your datasets in plain English.
CSVBrain Natural Language Data Queries Use Cases
- Building conversational data interfaces within Openclaw Skills projects for non-technical users.
- Generating instant statistical summaries of marketing, sales, or financial CSV exports.
- Querying sensitive data locally using Ollama to maintain privacy while leveraging LLM intelligence.
- Rapidly filtering and aggregating large datasets using structured programmatic queries or natural language.
How CSVBrain Natural Language Data Queries Works
- The user loads a CSV or TSV file into the CSVBrain instance, where delimiters are automatically detected.
- The system generates a comprehensive profile of the data, including column types and basic statistics (min, max, average).
- When a natural language question is asked, the tool sends the data schema and sample rows to a configured AI provider.
- The AI (Anthropic, OpenAI, or local Ollama) analyzes the metadata to formulate a precise answer.
- The results are returned as a structured object containing the human-readable answer and the specific data points used.
CSVBrain Natural Language Data Queries Setup
To integrate this into your environment, copy the source file and configure your preferred AI provider. This flexibility makes it a highly adaptable part of the Openclaw Skills ecosystem.
# To use Anthropic models
export ANTHROPIC_API_KEY="your-api-key"
# To use OpenAI models
export OPENAI_API_KEY="your-api-key"
# To use local models via Ollama
ollama serve
ollama pull llama3
CSVBrain Natural Language Data Queries Data Schema & Taxonomy
CSVBrain maintains an internal representation of your dataset to facilitate accurate queries. This schema is vital for Openclaw Skills that require structured data insights.
| Component | Details |
|---|---|
| Data Profiling | Stores count, missing values, and unique value counts for every column. |
| Numeric Stats | Tracks min, max, and avg for columns identified as number types. |
| Type Inference | Automatically categorizes columns as 'text' or 'number' based on content. |
| Query Result | Returns structured JSON with answers, supporting data, and the model utilized. |
CSVBrain Natural Language Data Queries Advanced Features
- Multi-provider AI support allowing seamless switching between Claude, GPT, and local Llama models.
- Zero-dependency implementation using native Node.js HTTP/HTTPS modules for maximum portability.
- Automatic delimiter detection handling comma, tab, and semicolon formats used in different locales.
- Robust error handling that provides graceful fallbacks if an AI provider is unreachable.
- Programmatic query engine for developers who need to combine structured filters with natural language within their Openclaw Skills workflows.
SKILL.md
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