Packs
7 packs@dotnet
Dotnet Experimental
Dotnet Experimental skills from dotnet/skills.
3 skills · pack
curated
Prioritize Assumptions and Experiment
Install this pack to prioritize assumptions and design targeted experiments.
3 skills · pack
curated
Experimentation Pipeline
From hypothesis to impact reporting, this pack enables rigorous experimentation and evidence-based decisions.
4 skills · pack
@phuryn
Product Discovery
Product discovery skills for PMs: ideation, experiments, assumption testing, feature prioritization, and customer interview synthesis.
13 skills · pack
curated
Validate Product Idea
Validate a product idea by clarifying intent, identifying risky assumptions, and designing experiments to test them.
4 skills · pack
curated
Validate New Product Idea
Stress-test assumptions, design experiments, and validate a new product idea using lean startup methods.
3 skills · pack
@alirezarezvani
Product Team
13 product skills with 17 Python tools: product manager toolkit (RICE, PRDs), agile product owner, product strategist, UX researcher, UI design system, competitive teardown, landing page generator, SaaS scaffolder, product analytics, experiment designer, product discovery, roadmap communicator, code-to-prd, research summarizer, apple-hig-expert.
10 skills · pack
Results for “experiment”
5 skillsexperiment-readout
Transforms A/B test and product experiment data into actionable readouts with hypothesis, metrics, interpretation, and decision.
· bundle
experiment-tracking-swanlab
Track ML experiments with open-source run logging, local or self-hosted dashboards, and media visualization using SwanLab.
10.4k · bundle
More results
jupyter-notebook
Create, scaffold, and edit Jupyter notebooks for experiments, exploratory analysis, or tutorials using bundled templates and a helper script.
23.3k · bundle
tensorboard
Visualize training metrics, debug models with histograms, compare experiments, visualize model graphs, and profile performance with TensorBoard.
3 · bundle
deeptools
Process and analyze high-throughput sequencing data with deepTools for quality control, normalization, comparison, and publication-quality visualizations of ChIP-seq, RNA-seq, and ATAC-seq experiments.
30.2k · bundle