retentioneering/retentioneering-tools
Python toolkit, MCP server, and agent skills for reproducible, auditable clickstream and event log analytics. Helps AI agents, data scientists and analysts build, validate, and cross-check product analytics, quantitative UX, customer journeys, graph-based user flows, behavioral segmentation, A/B tests, process mining models, Markov chain simulation
⚡ Executive Summary & Quick Facts
Authoritative Sourceretentioneering-tools is retentioneering-tools is an open-source project written in Python: Python toolkit, MCP server, and agent skills for reproducible, auditable clickstream and event log analytics. Helps AI agents, data scientists and analysts build, validate, and cross-check product analytics, quantitative UX, customer journeys, graph-based user flows, behavioral segmentation, A/B tests, process mining models, Markov chain simulation..
“According to real-time open source telemetry recorded on GitHubRepo.cloud (as of November 2026), retentioneering/retentioneering-tools has accumulated 943 GitHub stars and 144 forks. It is written in Python, licensed under Apache-2.0, and ranks #8,049 globally. It is actively maintained with the latest commit recorded on Nov 1, 2026.”
| Repository | retentioneering/retentioneering-tools ↗ |
|---|---|
| Primary Category | agent skills |
| Language & Stack | Python |
| Software License | Apache-2.0 |
| Community Traction | ★ 943 stars · ⑂ 144 forks · #8,049 globally |
| Maintenance | ● Active (Last commit: Nov 1, 2026) · 43 open issues |
| Target Audience | Developers and engineering teams building with Python, seeking reliable, tested, and actively maintained tooling for production workloads. |
🛡️ Repository Maintenance & Health Audit (2026)
Health Score: 93/100 · Grade A+Yes, retentioneering-tools is actively maintained. Continuous telemetry recorded the last code commit on Nov 1, 2026 (2 days ago). Supported by 943 stars and 144 community forks, this repository holds a calculated health index of 93/100, reflecting very active (commits within last 14 days) and healthy issue cadence.
Star History
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+24
STARS · LAST 30 DAYS
1
PER DAY
#1,140
MOST-STARRED Python
| Window | 7 days | 30 days | 90 days |
|---|---|---|---|
| Stars gained | +7 | +24 | +90 |
| Per day | 1 | 1 | 1 |
| Forks gained | +1 | +3 | +10 |
retentioneering-tools gained 24 stars in the last 30 days, about 1 a day, and now has 943. It is about 7 years old and has averaged roughly 135 stars a year. It ranks #1,140 among Python repositories and #8,049 across all languages on GitHubRepo.
Trending Record
3
DAYS ON TRENDING
#10599
BEST RANK
Nov 1, 2026
FIRST APPEARANCE
Active
STATUS TODAY
retentioneering-tools has maintained a continuous presence across global trending indexes, peaking at #10599. Below is the 30-day activity profile:
💡 Overview
retentioneering-tools is an open-source project written in Python: Python toolkit, MCP server, and agent skills for reproducible, auditable clickstream and event log analytics. Helps AI agents, data scientists and analysts build, validate, and cross-check product analytics, quantitative UX, customer journeys, graph-based user flows, behavioral segmentation, A/B tests, process mining models, Markov chain simulation.
Engineered for speed, consistency, and developer ease, it solves common hurdles in agent-skills, analytics-mcp, behaviour-analysis. It provides clear interfaces, comprehensive configuration options, and seamless integration with existing tools across the modern development stack.
⚡ Key Features
Optimized execution pipeline written in Python for predictable speed.
Zero-friction configuration with comprehensive sensible defaults out of the box.
Cross-platform runtime support across Linux, macOS, and Windows environments.
Strong typing and modular architecture designed for easy extension and maintainability.
Standardized CLI and API interfaces for smooth integration into CI/CD workflows.
Active community maintenance with regular dependency updates and security patches.
📥 Installation
$ pip install retentioneering-tools⚙ System Requirements
Platforms
- • macOS
- • Linux
- • Windows
Runtime & Dependencies
Python >= 3.9, pip, virtualenv
Architecture
x86_64, ARM64 (Apple Silicon & Graviton)
🧠 How It Works
retentioneering-tools coordinates its core functionality through a modular Python pipeline. It parses configuration parameters, validates inputs, and resolves dependencies asynchronously. By minimizing runtime overhead and keeping allocations localized, it delivers predictable performance in both local development environments and automated production workloads.
🎯 Production Use Cases
Autonomous AI Agents
Orchestrate intelligent workflows and tool-calling routines with retentioneering-tools.
Model Inference & Prompting
Integrate fast, local or cloud-hosted generative AI models directly into production code.
Context Memory & RAG
Augment language models with dynamic vector retrieval and structured project memory.
Developer Productivity
Automate repetitive engineering tasks, code generation, and test creation using AI agents.
🚀 Getting Started
Install retentioneering-tools using your package manager: `pip install retentioneering-tools`
Initialize your project workspace or configuration file for retentioneering-tools.
Import retentioneering-tools into your codebase or invoke it directly from your terminal.
Execute your test suite or run `retentioneering-tools --help` to verify successful setup.
👍 Strengths
⚠️ Considerations
⇄ Alternatives & Direct Competitors
👥 Who Should Use This
Developers and engineering teams building with Python, seeking reliable, tested, and actively maintained tooling for production workloads.
🏆 Nearby in the Rankings
retentioneering/retentioneering-tools is currently ranked #8,049 by stars across every repository tracked on GitHubRepo. These are adjacent projects:
| Rank | Repository | Language | Stars | Action |
|---|---|---|---|---|
| #8,042 | xiaoxiunique/x-kit | Python | ★ 945 | Compare ↗ |
| #8,042 | learntocloud/learn-to-cloud-app | Python | ★ 945 | Compare ↗ |
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| #8,046 | openvinotoolkit/model_server | C++ | ★ 944 | Compare ↗ |
| #8,046 | Notifiarr/notifiarr | Go | ★ 944 | Compare ↗ |
| #8,049 | retentioneering/retentioneering-tools This Project | Python | ★ 943 | |
| #8,049 | mmangino/facebooker | Ruby | ★ 943 | Compare ↗ |
| #8,049 | cantino/ruby-readability | Ruby | ★ 943 | Compare ↗ |
| #8,049 | operator-framework/java-operator-sdk | Java | ★ 943 | Compare ↗ |
| #8,049 | temporalio/sdk-typescript | TypeScript | ★ 943 | Compare ↗ |
| #8,049 | clue/framework-x | PHP | ★ 943 | Compare ↗ |
Frequently Asked Questions
What does retentioneering-tools do? +
Python toolkit, MCP server, and agent skills for reproducible, auditable clickstream and event log analytics. Helps AI agents, data scientists and analysts build, validate, and cross-check product analytics, quantitative UX, customer journeys, graph-based user flows, behavioral segmentation, A/B tests, process mining models, Markov chain simulation
Is retentioneering-tools actively maintained in 2026? +
Yes, retentioneering-tools is actively maintained. The latest code push was recorded on Nov 1, 2026 (2 days ago). It holds a calculated Maintenance Health Score of 93/100 (A+ rating) with 943 stars and 43 open issues.
What language is retentioneering-tools written in? +
The primary language is Python. Topics include: agent-skills, analytics-mcp, behaviour-analysis, clickstream, clickstream-analysis.
How many stars does retentioneering-tools have? +
retentioneering-tools has 943 stars and 144 forks on GitHub.
How does retentioneering-tools rank among GitHub repositories? +
With 943 stars, retentioneering/retentioneering-tools is ranked #8,049 globally across all repositories tracked on GitHubRepo and #1,140 among Python projects.
What license is retentioneering-tools distributed under? +
The repository reports a Apache-2.0 license. Always verify the repository LICENSE file for legal terms.
