Can I preview an operation before processing an entire dataframe?

Yes, operations like rank, screen, and merge support a preview=True parameter, allowing you to test your AI instructions on a few rows before committing to the full task.

Can Everyrow handle large datasets?

Yes, the SDK includes batch processing via agent_map and async variants of all operations to handle larger datasets and background processing.

How does semantic deduplication differ from standard deduping?

Standard deduping looks for exact matches, while Everyrow uses AI to understand that 'AbbVie Inc' and 'AbbVie Pharmaceutical' represent the same entity, grouping them semantically.

What does the Everyrow SDK skill do?

It provides Claude with the specialized knowledge to write Python code that uses AI agents to sort, filter, deduplicate, and join pandas dataframes based on qualitative criteria.

Do I need an API key to use Everyrow?

Yes, Everyrow requires an API key which can be obtained at everyrow.io. The skill will prompt you to set the EVERYROW_API_KEY environment variable if it's missing.

Everyrow AI Data Processor

Name: Everyrow AI Data Processor
Author: futuresearch

byfuturesearch

•

Data Science & ML

Transforms pandas dataframes using AI-powered qualitative ranking, semantic deduplication, and research-based filtering.

The Everyrow SDK skill enables Claude to perform sophisticated data operations that traditional programmatic logic cannot handle, such as scoring rows based on subjective criteria or merging datasets with inconsistent keys. By integrating AI agents directly into the pandas workflow, it allows developers to automate research-heavy tasks like lead scoring, legal entity resolution, and complex thematic filtering using natural language instructions. This skill is essential for data scientists and developers who need to bridge the gap between unstructured qualitative analysis and structured data processing.

Key Features

01Support for batch processing and asynchronous long-running data tasks

02Qualitative ranking and scoring of dataframe rows using AI agents

0312 GitHub stars

04Semantic deduplication to identify and group records with varied naming conventions

05AI-powered table merging for datasets without exact matching keys

06Complex row screening based on research-intensive natural language criteria

Use Cases

01Filtering financial datasets for companies meeting specific, nuanced investment themes

02Cleaning CRM or supplier data by merging duplicate records for the same legal entities

03Scoring sales leads based on qualitative indicators of product-market fit

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add futuresearch/everyrow-sdk everyrow-sdk

For use in Claude.ai and ChatGPT

Download Skill