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DataPython

Product Analysis

by nimadorostkar

Product Analysis is a Data skill for Claude Code, published by nimadorostkar in Claude-Skills-collection.

25 stars3 forkson nimadorostkar/Claude-Skills-collectionAdded 2026/08/12Repository updated 2026/07/26
aiclaudeclaude-skillsskills
Install in seconds
Install Product Analysis
Copy Product Analysis into your Claude Code skills folder. Run the command in your terminal, or review the source on GitHub before installing.
terminal
npx degit https://github.com/nimadorostkar/Claude-Skills-collection/tree/main/skills/business/product-analysis ~/.claude/skills/product-analysis

Requires Node.js. Downloads this skill only — not the rest of the repository — into your Claude Code skills folder.

Without Node.js

git clone https://github.com/nimadorostkar/Claude-Skills-collection.git

Clones the whole repository, then copy the skill’s own directory into your skills folder yourself.

In this catalog

Source file
skills/business/product-analysis/SKILL.md in nimadorostkar/Claude-Skills-collection
Installs to
~/.claude/skills/product-analysis
Collection
One of 50 skills cataloged from this repository
Category
Data668 skills

What Product Analysis does

Product Analysis helps assess product performance and decide what to build using metrics, funnels, retention, and feature adoption data. It is used to separate signal from noise and turn analysis into a prioritized recommendation.

Product Analysis is cataloged under Data on DirSkills. Product Analysis comes from a repository tagged ai, claude, claude-skills and skills.

Documentation

README

Product Analysis

Purpose

Understand how a product is actually used and decide what to do about it. The failure mode is a dashboard full of numbers that go up, none of which are connected to whether the product is working.

When to Use

  • Deciding what to build next.
  • A metric moved and nobody knows why.
  • Assessing whether a feature worked.
  • Setting up product analytics.

Capabilities

  • Metric selection: the one that matters versus the ones that flatter.
  • Funnel analysis and drop-off diagnosis.
  • Retention and cohort analysis.
  • Feature-adoption measurement.
  • Prioritization on evidence.

Inputs

  • Usage data, at the event level.
  • What the product is meant to do for the user.
  • The decision this analysis informs.

Outputs

This is the opening of the README. Read the full README on GitHub.

Frequently asked about Product Analysis

  • What else does nimadorostkar publish alongside Product Analysis?

    Product Analysis is one of 50 skills that DirSkills catalogs from nimadorostkar/Claude-Skills-collection, the repository it ships in. Its siblings there include API Design, Agent Design and Agent Instructions. Each one is a separate skill with its own page in this directory, installs the same way Product Analysis does, and is maintained by nimadorostkar in that same repository. The rest of the collection is listed on the nimadorostkar/Claude-Skills-collection page.

  • How does Product Analysis compare to other Data skills?

    Product Analysis ranks #648 by stars among the 668 Data skills in this catalog. The most-starred ones next to it are Benchmark Methodology, Jupyter Notebook and Solana. DirSkills ranks by the star count of the repository each skill ships in, so that order reflects how popular those repositories are rather than any review of Product Analysis against them. Open each page to compare what they document and how they install.

More from nimadorostkar/Claude-Skills-collection

Product Analysis is one of 50 skills cataloged on DirSkills from nimadorostkar/Claude-Skills-collection.

See all 50 skills