Futuresearch Futuresearch Python
- 49 repo stars
- Updated July 27, 2026
- futuresearch/futuresearch-python
futuresearch-futuresearch-python is a Claude Code plugin that equips your agent with Python research-agent utilities for screening, ranking, deduping, and transforming dataframe research data.
About
futuresearch-futuresearch-python is a Claude Code plugin that packages Python utilities and agent-oriented workflows for serious desk research. developers drowning in CSVs, scraped lists, or survey exports can use it to screen, rank, dedupe, merge, and transform dataframes with AI-assisted steps instead of fragile spreadsheet macros. It fits the early journey when you are still proving what market slice matters, and it remains useful when you integrate research pipelines into backend or agent tooling. The repo positions the offering as giving your AI its own researchers—useful for competitive scans, lead lists, literature-style triage, and any job where every row needs a consistent judgment. Expect a Python-centric setup rather than a no-code UI; you register the plugin in Claude Code and invoke the bundled capabilities from your agent sessions. With one plugin in the bundle and a modest community footprint, it is a specialized research-acceleration layer, not a general codegen assistant.
- Python plugin bundle aimed at AI-powered tabular research (dataframes, screening, ranking, deduping, merging).
- Everyrow-style row processing for batch agent judgments over large datasets.
- Transform and utility helpers for cleaning research exports before analysis.
- Designed to act as a team of research agents—or attach those researchers to your coding agent.
- Single-plugin bundle from futuresearch/futuresearch-python (pluginCount: 1).
Futuresearch Futuresearch Python by the numbers
- Data as of Jul 28, 2026 (Skillselion catalog sync)
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| repo stars | ★ 49 |
|---|---|
| Last updated | July 27, 2026 |
| Repository | futuresearch/futuresearch-python ↗ |
What it does
Give Claude Code a Python toolkit of research agents for screening, ranking, deduping, and transforming tabular research data before you commit to a product direction.
Who is it for?
Best when you're doing competitor lists, survey screening, or lead research in Python and want agent-driven row operations instead of manual filtering.
Skip if: Skip if you only need one-off web search summaries with no tabular data, or anyone unwilling to run a Python research toolchain inside Claude Code.
What you get
After you add the plugin, Claude can run consistent AI-assisted dataframe research steps so evidence tables stay clean and decision-ready before you build.
- Agent-invokable Python research processing utilities in Claude Code
- Cleaner ranked or deduped research tables for decision docs
- Repeatable screening and transform steps over large row sets
By the numbers
- pluginCount: 1
- repository: futuresearch/futuresearch-python
- catalog stars snapshot: 27
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Research dataframe agent toolkit, not a generic code-review or MCP browser integration.
FAQ
Who is Futuresearch Futuresearch Python for?
It is for developers using Claude Code who run market or product research on dataframes and want agent helpers for screening, ranking, deduping, and merging rows.
When should I use Futuresearch Futuresearch Python?
Use it during Idea and Validate when you are synthesizing competitors, surveys, or scraped lists, and again in Build if you embed those research steps in a Python pipeline.
How do I add Futuresearch Futuresearch Python to my agent?
Install the plugin from the futuresearch/futuresearch-python repository into Claude Code, ensure your Python environment matches the project expectations, then enable the plugin in your session before research tasks.