Agent skill

User Segmentation

by phuryn in phuryn/pm-skills

Segment users from feedback data based on behavior, JTBD, and needs.

MITAuto-check passedProduct & Project Management

Install User Segmentation

skills CLI
$ npx skills add phuryn/pm-skills --skill user-segmentation -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install phuryn/pm-skills user-segmentation --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/phuryn/pm-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/pm-market-research/skills/user-segmentation .claude/skills/user-segmentation && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
user-segmentation
GitHub stars
27k
Token cost
~1k tokens
SKILL.md length
463 words
Files
1
Skills in repo
62
Repo updated
First seen
Licence
MIT

At a glance

Segment users from feedback data based on behavior, JTBD, and needs.

  • Works in 6 steps: Data Preparation: Read and organize all… → Behavior Extraction: Identify key… → Needs Analysis: Map jobs-to-be-done,… → …
  • Segmenting a user base
  • SKILL.md covers Purpose, Instructions and Best Practices
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

User Segmentation is an agent skill from phuryn/pm-skills. Segment users from feedback data based on behavior, JTBD, and needs. Identifies at least 3 distinct user segments. Use when segmenting a user base, analyzing diverse user feedback, or building a segmentation model.

Its SKILL.md is about 1k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Product & Project Management, covering User stories. The repository describes itself as: PM Skills Marketplace: 100+ agentic skills, commands, and plugins — from discovery to strategy, execution, launch, and growth. The licence is MIT.

When your agent uses it

  • Segmenting a user base
  • Analyzing diverse user feedback
  • Building a segmentation model

Example prompts

  • “/user-segmentation”

Workflow steps

6 steps, taken from the first numbered list in SKILL.md.

  1. Data Preparation: Read and organize all provided user feedback and data
  2. Behavior Extraction: Identify key behavioral patterns, usage modes, and user journeys
  3. Needs Analysis: Map jobs-to-be-done, desired outcomes, and pain points for each user
  4. Clustering: Group users into distinct segments based on behavior and needs similarity
  5. Validation: Ensure segments are coherent, non-overlapping, and actionable
  6. Characterization: Develop rich profiles for each segment with representative quotes

What it can do on your machine

Read from SKILL.md and the folder at commit 8607e3b. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Links to these hosts (documentation or services it may open):

    • productcompass.pm

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

User Segmentation loads about 1k tokens when it runs. Until then it costs about 58 tokens; SKILL.md has 463 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~58
When it runs · the whole SKILL.md, loaded when a task matches
~1k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from phuryn/pm-skills at commit 8607e3b, republished under its MIT licence (© phuryn). 463 words, ~1,026 tokens.

Download SKILL.mdSave it as .claude/skills/user-segmentation/SKILL.md (or your agent's skills folder).
name
user-segmentation
description
Segment users from feedback data based on behavior, JTBD, and needs. Identifies at least 3 distinct user segments. Use when segmenting a user base, analyzing diverse user feedback, or building a segmentation model.

User Segmentation

Purpose

Analyze diverse user feedback to identify at least 3 distinct behavioral and needs-based user segments. This skill surfaces hidden customer groups based on jobs-to-be-done, behaviors, and motivations rather than demographics alone, enabling targeted product strategy.

Instructions

You are an expert behavioral researcher and data analyst specializing in user segmentation and behavioral clustering.

Input

Your task is to segment users for $ARGUMENTS based on behavior, jobs-to-be-done, and unmet needs.

If the user provides feedback data, interviews, support tickets, product usage logs, surveys, or other user data, read and analyze them directly. Extract behavioral patterns, motivations, and needs across the user base.

Analysis Steps (Think Step by Step)
  1. Data Preparation: Read and organize all provided user feedback and data
  2. Behavior Extraction: Identify key behavioral patterns, usage modes, and user journeys
  3. Needs Analysis: Map jobs-to-be-done, desired outcomes, and pain points for each user
  4. Clustering: Group users into distinct segments based on behavior and needs similarity
  5. Validation: Ensure segments are coherent, non-overlapping, and actionable
  6. Characterization: Develop rich profiles for each segment with representative quotes
Output Structure

For each identified segment (minimum 3):

Segment Name & Overview

  • Clear, descriptive segment identifier
  • Size: estimated number or percentage of user base
  • Brief one-sentence characterization

Behavioral Characteristics

  • How this segment uses $ARGUMENTS (primary use cases, frequency, depth)
  • Typical user journey and key touchpoints
  • Technical proficiency or sophistication level
  • Integration with other tools or workflows

Jobs-to-be-Done & Motivations

  • Core job(s) this segment is trying to accomplish
  • Underlying motivations and desired outcomes
  • Context and frequency of the job
  • What success looks like for this segment

Key Needs & Pain Points

  • Unmet needs specific to this segment's behavior
  • Obstacles preventing effective job completion
  • Current workarounds or alternative solutions they employ
  • Severity and frequency of pain points
Show full SKILL.md (172 more words)Show less

Current Product Fit

  • How well $ARGUMENTS currently serves this segment
  • Features or capabilities this segment values most
  • Gaps or limitations most frustrating to this segment
  • Likelihood to continue using vs. churn risk

Differentiated Value Proposition

  • What unique value could be unlocked for this segment
  • Feature or experience improvements that would maximize fit
  • Messaging and positioning most resonant with this segment

Segment Prioritization

  • Strategic importance: growth potential, revenue impact, alignment with vision
  • Implementation difficulty: ease of serving this segment's needs
  • Recommendation: invest, maintain, or de-prioritize

Best Practices

  • Ground segmentation in behavioral and motivational data, not just demographics
  • Use representative quotes and examples from actual user feedback
  • Ensure segments are distinct and serve different core needs
  • Consider interdependencies between segments and prioritization tradeoffs
  • Flag any segments that may be underrepresented in feedback data
  • Validate emerging segments against product usage or customer data when available
  • Consider adjacent behaviors and cross-segment patterns

Further Reading

© phuryn, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in pm-market-research/skills/user-segmentation of phuryn/pm-skills.

Open the folder on GitHubat commit 8607e3b

Compare with similar skills

User Segmentation next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

User Segmentation compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
User Segmentation this skillphuryn/pm-skills27k—~1kAutomated safety check: PassMIT
User Story Writerdeanpeters/Product-Manager-Skills7.2k2 repos~2.9kAutomated safety check: PassCustom licence
Ralph Tui Create Beadssubsy/ralph-tui2.5k1 repos~2.6kAutomated safety check: PassMIT
Agile Product Owneralirezarezvani/claude-skills28k3 repos~3.2kAutomated safety check: PassMIT
Ralph Tui Create Beads Rustsubsy/ralph-tui2.5k1 repos~2.8kAutomated safety check: PassMIT
Ralph Tui Create JSONsubsy/ralph-tui2.5k1 repos~2.6kAutomated safety check: PassMIT

Similar skills

  • User Story Writer

    deanpeters/Product-Manager-Skills

    Writes user stories in Mike Cohn's format with Gherkin acceptance criteria, turning user needs into development-ready work with testable conditions.

    7.2k GitHub starsUsed in 2 repos~2.9k tokens
    Product & Project ManagementAuto-check passed
  • Ralph Tui Create Beads

    subsy/ralph-tui

    Convert PRDs to beads for ralph-tui execution. An agent skill from subsy/ralph-tui.

    2.5k GitHub starsUsed in 1 repo~2.6k tokens
    Product & Project ManagementAuto-check passed
  • Agile Product Owner

    alirezarezvani/claude-skills

    Writes INVEST-checked user stories with acceptance criteria, splits epics, plans sprints from velocity and ranks the backlog with a weighted score.

    28k GitHub starsUsed in 3 repos~3.2k tokens
    Product & Project ManagementAuto-check passed
  • Convert PRDs to beads for ralph-tui execution using beads-rust (br CLI).

    2.5k GitHub starsUsed in 1 repo~2.8k tokens
    Product & Project ManagementAuto-check passed
  • Ralph Tui Create JSON

    subsy/ralph-tui

    Convert PRDs to prd.json format for ralph-tui execution. An agent skill from subsy/ralph-tui.

    2.5k GitHub starsUsed in 1 repo~2.6k tokens
    Product & Project ManagementAuto-check passed
  • Check

    VibiumDev/vibium

    Independently check application acceptance criteria in a live browser or saved recording with the Vibium CLI.

    2.9k GitHub stars~2k tokensUpdated yesterday
    Product & Project ManagementAuto-check passed

More from phuryn/pm-skills

All 62 skills in this repo
  • Reviews a diff by anchoring on agreements between two sides of a boundary, forcing a concrete violating execution, and refuting each finding before reporting it.

    27k GitHub stars~3.6k tokensUpdated 23 days ago
    Auto-check passed
  • A/B Test Analysis

    phuryn/pm-skills

    Validates an experiment's setup, works out lift, p-value and confidence interval from A/B test data, and recommends whether to ship, extend or stop.

    27k GitHub stars~893 tokensUpdated 23 days ago
    Auto-check passed
  • Team OKR Brainstorm

    phuryn/pm-skills

    Drafts three alternative sets of team OKRs, each with an inspiring objective and measurable key results, tied to the company strategy you provide.

    27k GitHub stars~1.1k tokensUpdated 23 days ago
    Auto-check passed
  • Analyzes uploaded cohort data to compute retention curves and feature adoption trends, builds heatmaps and charts, and suggests qualitative follow-up research.

    27k GitHub stars~1.3k tokensUpdated 23 days ago
    Auto-check passed
  • Dummy Dataset Generator

    phuryn/pm-skills

    Generates realistic test datasets with custom columns, row counts and business constraints, output as CSV, JSON, SQL inserts or a runnable Python script.

    27k GitHub stars~983 tokensUpdated 23 days ago
    Auto-check passed
  • Grammar and Flow Checker

    phuryn/pm-skills

    Reviews a draft for grammar, logic and flow problems and returns located, prioritized fix suggestions without rewriting the whole text.

    27k GitHub stars~2.4k tokensUpdated 23 days ago
    Auto-check passed

Questions about User Segmentation

What does User Segmentation do?

Segment users from feedback data based on behavior, JTBD, and needs. User Segmentation is an agent skill from phuryn/pm-skills. Segment users from feedback data based on behavior, JTBD, and needs.

When should I use User Segmentation?

User Segmentation fits situations like: segmenting a user base; analyzing diverse user feedback; building a segmentation model.

How do I install User Segmentation in Claude Code?

Run `npx skills add phuryn/pm-skills --skill user-segmentation -a claude-code`. Or copy the skill folder (pm-market-research/skills/user-segmentation in phuryn/pm-skills) into .claude/skills/user-segmentation in your project. Claude Code loads it when a task matches its description.

How do I install User Segmentation in Codex?

Run `npx skills add phuryn/pm-skills --skill user-segmentation -a codex`. Or copy the skill folder (pm-market-research/skills/user-segmentation in phuryn/pm-skills) into .agents/skills/user-segmentation in your project. Codex loads it when a task matches its description.

Can I use User Segmentation in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add phuryn/pm-skills --skill user-segmentation -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/user-segmentation, .gemini/skills/user-segmentation, .github/skills/user-segmentation and .opencode/skills/user-segmentation in your project.

What does User Segmentation need to run?

SKILL.md names no scripts, command-line tools or credentials: User Segmentation is instructions for the agent only.

Does User Segmentation access the network?

SKILL.md names 1 domain. As links in the text: productcompass.pm. This is read from the text; nothing was executed.

Is User Segmentation safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does User Segmentation use?

User Segmentation is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does User Segmentation use?

About 1k tokens (SKILL.md is roughly 4.1k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to User Segmentation?

Skills that share tags, products or a category with User Segmentation: User Story Writer (deanpeters/Product-Manager-Skills, 7.2k stars), Ralph Tui Create Beads (subsy/ralph-tui, 2.5k stars), Agile Product Owner (alirezarezvani/claude-skills, 28k stars) and Ralph Tui Create Beads Rust (subsy/ralph-tui, 2.5k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains User Segmentation?

phuryn (a GitHub user) maintains it in phuryn/pm-skills, which has 26,809 GitHub stars. The repository holds 62 skills in this directory. The repository was last updated on September 14, 2026.

Source: phuryn/pm-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.