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ZhixiangLuo/10xProductivity

Score: 55.1 Rank #17 AI Tool

AI agent tool connections for 10x productivity

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Overview

ZhixiangLuo/10xProductivity is a Python agent tool licensed under MIT. AI agent tool connections for 10x productivity

Ranked #17 out of 110 indexed tools.

Actively maintained with commits in the last week.

Ecosystem

Python MIT

Score Breakdown

StarsFreshnessIssue HealthContributorsDependents
Stars 15% 3

3 stars → early stage

Freshness 25% today

Last commit today → actively maintained

Issue Health 25% 50%

No issues filed → no history to score

Contributors 10% 3

3 contributors → small team

Dependents 25% 0

No dependents → no downstream usage

npm Downloads N/A
PyPI Downloads N/A
Forks 0
Description Brief
License MIT

Weights: Freshness 25% · Issue Health 25% · Dependents 25% · Stars 15% · Contributors 10% · How we score →

How to Improve

Description low impact

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Dependents medium impact

No downstream dependents detected yet — adoption by other projects is the strongest trust signal

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From the README

# 10xProductivity

> *Every tool you can use as a human on your laptop, your agent can use too — with zero infrastructure, zero cloud services, zero new permissions.*

## The Philosophy

Most "AI integration" approaches ask you to:
- Set up cloud middleware (Zapier, MCP servers, hosted agents)
- Request IT-approved service accounts
- Wait for admin provisioning
- Accept new attack surfaces and vendor lock-in

**10xProductivity flips this completely.**

Apps are built for humans on laptops. Browsers, CLIs, REST APIs — they're all already there. Your agent uses the same surface. No integration layer, no middleware, no new permissions.

### Four principles

**1. Local agent as the universal client**
Your laptop is the platform. The agent is just a smarter version of you running scripts. No new infrastructure required.

**2. Security by locality**
The threat model is identical to you doing it manually. Nothing new is exposed. No cloud service sits between you and your tools holding your cr
Read full README on GitHub →
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