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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

Stars
944
Forks
144
Language
Python
License
Apache-2.0
Last commit
updated Nov 2026
Hidden gemActive
product-analyticsuser-trajectories-analysismachine-learningpredictive-analyticspredictive-modelingclickstreamsegmentationgraph-visualizer

Straight from GitHub

Nobody has written up this repo. Everything on this page comes straight from the GitHub API, so there is no founder write-up, no pros and cons, and no difficulty rating — rather than a generated guess at them.

Maintenance

Pushed within three months of the last stats read (as of Nov 6, 2026).

Licence

Apache-2.0

Tech stack

Primary language: Python. GitHub reports only the dominant language, so this is not the whole stack.

Install

No install command has been verified for this repo. Follow the README rather than a guess.

Quality score

Computed by the discovery import when this entry was added.

0.93out of 1.00
Recent activity×0.30
1.00

How recently the default branch was pushed to.

Adoption×0.20
0.63

Stars on a log scale, so adoption counts without dominating.

Description and topics×0.15
1.00

Whether the repo describes itself: description, topics, homepage.

README present×0.15
1.00

Whether the repository has a README at all.

Licence clarity×0.10
1.00

Whether GitHub can resolve the licence to a recognised SPDX id.

Issue health×0.10
1.00

Open issues relative to adoption, as a rough maintenance signal.

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Stats updated Nov 6, 2026. Stars, forks, issue counts, and dates are a snapshot read from the GitHub REST API, not a live figure. This site makes no requests to GitHub when you load a page.

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