πŸ› οΈ
Atomic Agents tool by Eigenwise
⭐ 64.3
πŸ› οΈ
Tool

Atomic Agents

by Eigenwise eigenwise/atomic-agents
Free2AITools Nexus Index
64.3
S: Semantic 50

Query-time baseline · scored live at search

A: Authority 60
P: Popularity 66
R: Recency 99
Q: Quality 70
Tech Context
Vital Performance —
Source β†’
Python Lang
Open Source 6.2K Stars
Alpha Reliability
Tool Information Summary
Entity Passport
Registry ID eigenwise/atomic-agents
License MIT
Provider github
πŸ“œ

Cite this tool

Academic & Research Attribution

BibTeX 
@misc{gh_tool_eigenwise_atomic_agents,
  author = {Eigenwise},
  title = {Atomic Agents Tool},
  year = {2024},
  howpublished = {\url{https://github.com/Eigenwise/atomic-agents}},
  note = {Accessed via Free2AITools.}
}
APA Style
Eigenwise. (2024). Atomic Agents [Tool]. Free2AITools. https://github.com/Eigenwise/atomic-agents

πŸ”¬Technical Deep Dive

Full Specifications [+]

Quick Commands

πŸ™ GitHub Clone
git clone https://github.com/Eigenwise/atomic-agents
🐍 PIP Install
pip install atomic-agents

βš–οΈ Free2AITools Nexus Index V2.0

Methodology How FNI works
Semantic (S) 50

Query-time baseline · scored live at search

Authority (A) 60
Popularity (P) 66
Recency (R) 99
Quality (Q) 70

πŸ’¬ Index Insight

FNI V2.0 for Atomic Agents: Authority (A:60), Popularity (P:66), Recency (R:99), Quality (Q:70). Semantic (S) is a query-time baseline scored live at search.

Free2AITools Nexus Index

Data Sources / Provenance

HuggingFace API GitHub Metadata Arxiv Citation DB Methodology
Open data Updated: Live data

πŸ“‹ Specs

Language
Python
License
MIT
Version
β€”
Explore Source Node
CODE

πŸ”Œ Usage & Integration

Quick Start

pip install atomic-agents

Technical Documentation

Atomic Agents

Atomic Agents

PyPI version Documentation Build Docs Code Quality Discord PyPI downloads Python Versions License: MIT GitHub Stars GitHub Forks Ask DeepWiki

What is Atomic Agents?

The Atomic Agents framework is designed around the concept of atomicity to be an extremely lightweight and modular framework for building Agentic AI pipelines and applications without sacrificing developer experience and maintainability.

Think of it like building AI applications with LEGO blocks - each component (agent, tool, context provider) is:

  • Single-purpose: Does one thing well
  • Reusable: Can be used in multiple pipelines
  • **C

Social Proof

GitHub Repository
6.2KStars
535Forks
Repo Issues
πŸ™ Data Source: GitHub β†—
πŸ”„ Updated daily

Source summary: Based on GitHub metadata. Not a recommendation.

πŸ“Š FNI Methodology πŸ“š Knowledge Baseℹ️ Verify with original source

πŸ›‘οΈ Tool Transparency Report

Technical metadata sourced from upstream repositories.

Open Metadata

πŸ†” Identity & Source

id
gh-tool--eigenwise--atomic-agents
slug
eigenwise--atomic-agents
source
github
author
Eigenwise
license
MIT
tags
ai, artificial-intelligence, large-language-model, large-language-models, llms, openai, openai-api, python

βš™οΈ Technical Specs

pipeline tag
other

πŸ“Š Engagement & Metrics

downloads
0
stars
6,195
forks
535
github stars
6,195

Data indexed from public sources. Updated daily.