Agent skill

Shopify Admin Rfm Customer Segmentation

by 40RTY-ai in 40RTY-ai/shopify-admin-skills

Read-only: scores every customer on Recency, Frequency, and Monetary value to segment them into actionable groups (Champions, Loyal, At-Risk, Lost).

MITAuto-check passed

Install Shopify Admin Rfm Customer Segmentation

skills CLI

$ npx skills add 40RTY-ai/shopify-admin-skills --skill shopify-admin-rfm-customer-segmentation -a claude-code

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

GitHub CLI

$ gh skill install 40RTY-ai/shopify-admin-skills shopify-admin-rfm-customer-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/40RTY-ai/shopify-admin-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/customer-ops/shopify-admin-rfm-customer-segmentation .claude/skills/shopify-admin-rfm-customer-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/

Paste into Claude Code

Install the "shopify-admin-rfm-customer-segmentation" agent skill from https://github.com/40RTY-ai/shopify-admin-skills/tree/main/skills/customer-ops/shopify-admin-rfm-customer-segmentation into .claude/skills/shopify-admin-rfm-customer-segmentation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "shopify-admin-rfm-customer-segmentation", then confirm the skill loads.

Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

$skill-installer

$skill-installer install https://github.com/40RTY-ai/shopify-admin-skills/tree/main/skills/customer-ops/shopify-admin-rfm-customer-segmentation

Type this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.

skills CLI

$ npx skills add 40RTY-ai/shopify-admin-skills --skill shopify-admin-rfm-customer-segmentation -a codex

Project install goes to .agents/skills/; add -g for ~/.codex/skills/.

GitHub CLI

$ gh skill install 40RTY-ai/shopify-admin-skills shopify-admin-rfm-customer-segmentation --agent codex

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/40RTY-ai/shopify-admin-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/customer-ops/shopify-admin-rfm-customer-segmentation .agents/skills/shopify-admin-rfm-customer-segmentation && rm -rf skills-src

Use ~/.agents/skills/ instead of .agents/skills for a personal install.

Codex skills documentation · loads skills from .agents/skills/

Paste into Codex

Install the "shopify-admin-rfm-customer-segmentation" agent skill from https://github.com/40RTY-ai/shopify-admin-skills/tree/main/skills/customer-ops/shopify-admin-rfm-customer-segmentation into .agents/skills/shopify-admin-rfm-customer-segmentation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "shopify-admin-rfm-customer-segmentation", then confirm the skill loads.

Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add 40RTY-ai/shopify-admin-skills --skill shopify-admin-rfm-customer-segmentation -a cursor

Project install goes to .agents/skills/; add -g for ~/.cursor/skills/.

GitHub CLI

$ gh skill install 40RTY-ai/shopify-admin-skills shopify-admin-rfm-customer-segmentation --agent cursor

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/40RTY-ai/shopify-admin-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/customer-ops/shopify-admin-rfm-customer-segmentation .cursor/skills/shopify-admin-rfm-customer-segmentation && rm -rf skills-src

Use ~/.cursor/skills/ instead of .cursor/skills for a personal install.

Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/

Paste into Cursor

Install the "shopify-admin-rfm-customer-segmentation" agent skill from https://github.com/40RTY-ai/shopify-admin-skills/tree/main/skills/customer-ops/shopify-admin-rfm-customer-segmentation into .cursor/skills/shopify-admin-rfm-customer-segmentation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "shopify-admin-rfm-customer-segmentation", then confirm the skill loads.

Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

gemini skills install

$ gemini skills install https://github.com/40RTY-ai/shopify-admin-skills.git --path skills/customer-ops/shopify-admin-rfm-customer-segmentation

--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.

skills CLI

$ npx skills add 40RTY-ai/shopify-admin-skills --skill shopify-admin-rfm-customer-segmentation -a gemini-cli

Project install goes to .agents/skills/; add -g for ~/.gemini/skills/.

GitHub CLI

$ gh skill install 40RTY-ai/shopify-admin-skills shopify-admin-rfm-customer-segmentation --agent gemini-cli

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/40RTY-ai/shopify-admin-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/customer-ops/shopify-admin-rfm-customer-segmentation .gemini/skills/shopify-admin-rfm-customer-segmentation && rm -rf skills-src

Use ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.

Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/

Paste into Gemini CLI

Install the "shopify-admin-rfm-customer-segmentation" agent skill from https://github.com/40RTY-ai/shopify-admin-skills/tree/main/skills/customer-ops/shopify-admin-rfm-customer-segmentation into .gemini/skills/shopify-admin-rfm-customer-segmentation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "shopify-admin-rfm-customer-segmentation", then confirm the skill loads.

Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

GitHub CLI

$ gh skill install 40RTY-ai/shopify-admin-skills shopify-admin-rfm-customer-segmentation

Installs for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).

skills CLI

$ npx skills add 40RTY-ai/shopify-admin-skills --skill shopify-admin-rfm-customer-segmentation -a github-copilot

Project install goes to .agents/skills/; add -g for ~/.copilot/skills/.

Manual copy

$ git clone --depth 1 https://github.com/40RTY-ai/shopify-admin-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/customer-ops/shopify-admin-rfm-customer-segmentation .github/skills/shopify-admin-rfm-customer-segmentation && rm -rf skills-src

Use ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.

GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/

Paste into GitHub Copilot

Install the "shopify-admin-rfm-customer-segmentation" agent skill from https://github.com/40RTY-ai/shopify-admin-skills/tree/main/skills/customer-ops/shopify-admin-rfm-customer-segmentation into .github/skills/shopify-admin-rfm-customer-segmentation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "shopify-admin-rfm-customer-segmentation", then confirm the skill loads.

GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add 40RTY-ai/shopify-admin-skills --skill shopify-admin-rfm-customer-segmentation -a opencode

OpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.

GitHub CLI

$ gh skill install 40RTY-ai/shopify-admin-skills shopify-admin-rfm-customer-segmentation --agent opencode

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/40RTY-ai/shopify-admin-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/customer-ops/shopify-admin-rfm-customer-segmentation .opencode/skills/shopify-admin-rfm-customer-segmentation && rm -rf skills-src

Use ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.

OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/

Paste into OpenCode

Install the "shopify-admin-rfm-customer-segmentation" agent skill from https://github.com/40RTY-ai/shopify-admin-skills/tree/main/skills/customer-ops/shopify-admin-rfm-customer-segmentation into .opencode/skills/shopify-admin-rfm-customer-segmentation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "shopify-admin-rfm-customer-segmentation", then confirm the skill loads.

OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

Facts

Skill name: shopify-admin-rfm-customer-segmentation
GitHub stars: 194
Token cost: ~1.9k tokens
SKILL.md length: 574 words
Files: 1
Skills in repo: 116
Repo updated: Aug 14, 2026
First seen: Oct 7, 2026
Licence: MIT

At a glance

Read-only: scores every customer on Recency, Frequency, and Monetary value to segment them into actionable groups (Champions, Loyal, At-Risk, Lost).

Works in 5 steps: OPERATION: orders — query → Aggregate per customer → Score each dimension 1-5 using quintile… → …
SKILL.md covers Purpose, Prerequisites, Parameters and Safety, plus 7 more sections
Calls shopify

What it does

Shopify Admin Rfm Customer Segmentation is an agent skill from 40RTY-ai/shopify-admin-skills. Read-only: scores every customer on Recency, Frequency, and Monetary value to segment them into actionable groups (Champions, Loyal, At-Risk, Lost).

Its SKILL.md is about 1.9k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts. Compatibility notes: Claude Code, Cursor, Codex, Gemini CLI

It works with Shopify. The repository describes itself as: Community-maintained AI agent skills for operating Shopify stores — workflows, optimization, reports and more. The licence is MIT.

Example prompts

“/shopify-admin-rfm-customer-segmentation”

Requirements

Compatibility (from SKILL.md): Claude Code, Cursor, Codex, Gemini CLI

Workflow steps

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

OPERATION: orders — query
Aggregate per customer
Score each dimension 1-5 using quintile bucketing
Map (R, F, M) score combination to named segment using the definitions above
OPERATION: customers — query (enrichment)

What it can do on your machine

Read from SKILL.md and the folder at commit 6765cb4. 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
Shell commands in SKILL.md call:
- shopify
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
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.
Compatibility
Claude Code, Cursor, Codex, Gemini CLI
From compatibility in the SKILL.md frontmatter.

Context cost

Shopify Admin Rfm Customer Segmentation loads about 1.9k tokens when it runs. Until then it costs about 47 tokens; SKILL.md has 574 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it: ~47
When it runs · the whole SKILL.md, loaded when a task matches: ~1.9k

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 40RTY-ai/shopify-admin-skills at commit 6765cb4, republished under its MIT licence (© 40RTY-ai). 574 words, ~1,877 tokens.

Download SKILL.mdSave it as .claude/skills/shopify-admin-rfm-customer-segmentation/SKILL.md (or your agent's skills folder).

name: shopify-admin-rfm-customer-segmentation
description: Read-only: scores every customer on Recency, Frequency, and Monetary value to segment them into actionable groups (Champions, Loyal, At-Risk, Lost).
compatibility: Claude Code, Cursor, Codex, Gemini CLI
role: customer-ops
toolkit: shopify-admin, shopify-admin-execution
api_version: 2025-01
graphql_operations: customers:query, orders:query
status: stable

Purpose

Performs full RFM (Recency, Frequency, Monetary) analysis across the entire customer base. Each customer is scored 1-5 on three dimensions — how recently they purchased, how often they purchase, and how much they spend — then classified into actionable segments: Champions, Loyal Customers, Potential Loyalists, At-Risk, Hibernating, and Lost. Read-only — no mutations.

Prerequisites

Authenticated Shopify CLI session: shopify store auth --store <domain> --scopes read_orders,read_customers
API scopes: read_orders, read_customers

Parameters

Parameter	Type	Required	Default	Description
store	string	yes	—	Store domain (e.g., mystore.myshopify.com)
days_back	integer	no	365	Lookback window for order history
segments	integer	no	5	Number of quintile buckets per dimension (3 or 5)
min_orders	integer	no	1	Minimum orders for a customer to be scored
tag_customers	boolean	no	false	If true, add RFM segment tag to customer (requires write_customers scope)
format	string	no	human	Output format: `human` or `json`

Safety

ℹ️ Read-only by default. If tag_customers: true, will add tags via customerUpdate mutation — use dry_run: true first.

RFM Segment Definitions

Segment	R Score	F Score	M Score	Description
Champions	5	5	5	Best customers — recent, frequent, high spend
Loyal Customers	3-5	4-5	4-5	Consistent buyers with strong spend
Potential Loyalists	4-5	2-3	2-3	Recent buyers who could become loyal
New Customers	5	1	1-2	Just made first purchase
Promising	4	1-2	1-2	Recent but low frequency — nurture them
Need Attention	3	3	3	Average across all dimensions — slipping
About to Sleep	2-3	2	2	Below average recency and frequency
At Risk	1-2	4-5	4-5	Were great customers, haven't bought recently
Hibernating	1-2	1-2	1-3	Low on all dimensions — nearly lost
Lost	1	1-2	1-5	Haven't bought in a very long time

Workflow Steps

OPERATION: orders — query Inputs: query: "created_at:>='<NOW - days_back days>'", first: 250, select createdAt, totalPriceSet, customer { id, email, firstName, lastName, numberOfOrders }, pagination cursor Expected output: All orders in window with customer linkage; paginate until complete
Aggregate per customer:
- Recency = days since last order
- Frequency = total number of orders in window
- Monetary = total spend in window
Score each dimension 1-5 using quintile bucketing:
- Sort all customers by each metric
- Divide into N equal-sized groups (quintiles)
- Assign scores (5 = best for recency [most recent], frequency [most frequent], monetary [highest spend])
Map (R, F, M) score combination to named segment using the definitions above
OPERATION: customers — query (enrichment) Inputs: Customer IDs from each segment for contact details Expected output: Email, name, tags for top customers in each segment

Show full SKILL.md (174 more words)Show less

GraphQL Operations

graphql

# orders:query — validated against api_version 2025-01
query OrdersForRFM($query: String!, $after: String) {
  orders(first: 250, after: $after, query: $query) {
    edges {
      node {
        id
        createdAt
        totalPriceSet { shopMoney { amount currencyCode } }
        customer {
          id
          email
          firstName
          lastName
          numberOfOrders
        }
      }
    }
    pageInfo { hasNextPage endCursor }
  }
}

graphql

# customers:query — validated against api_version 2025-01
query CustomerDetails($query: String, $after: String) {
  customers(first: 250, after: $after, query: $query) {
    edges {
      node {
        id
        email
        firstName
        lastName
        numberOfOrders
        totalSpentV2 { amount currencyCode }
        tags
        createdAt
      }
    }
    pageInfo { hasNextPage endCursor }
  }
}

Session Tracking

Claude MUST emit the following output at each stage. This is mandatory.

On start, emit:

╔══════════════════════════════════════════════╗
║  SKILL: RFM Customer Segmentation           ║
║  Store: <store domain>                       ║
║  Started: <YYYY-MM-DD HH:MM UTC>             ║
╚══════════════════════════════════════════════╝

After each step, emit:

[N/TOTAL] <QUERY|MUTATION>  <OperationName>
          → Params: <brief summary of key inputs>
          → Result: <count or outcome>

On completion, emit:

For format: human (default):

══════════════════════════════════════════════
RFM SEGMENTATION REPORT  (<days_back> days)
  Customers scored:     <n>
  ─────────────────────────────
  Champions:            <n> (<pct>%)  Avg spend: $<n>
  Loyal Customers:      <n> (<pct>%)  Avg spend: $<n>
  Potential Loyalists:  <n> (<pct>%)  Avg spend: $<n>
  At Risk:              <n> (<pct>%)  Avg spend: $<n>
  Hibernating:          <n> (<pct>%)  Avg spend: $<n>
  Lost:                 <n> (<pct>%)  Avg spend: $<n>

  Top Champions:
    <name> (<email>)  R:<n> F:<n> M:<n>  Spend: $<n>
  Top At-Risk (win-back candidates):
    <name> (<email>)  Last order: <date>  Lifetime: $<n>
  Output: rfm_segments_<date>.csv
══════════════════════════════════════════════

For format: json, emit:

json

{
  "skill": "rfm-customer-segmentation",
  "store": "<domain>",
  "period_days": 365,
  "customers_scored": 0,
  "segments": {
    "champions": { "count": 0, "pct": 0, "avg_spend": 0 },
    "loyal": { "count": 0, "pct": 0, "avg_spend": 0 },
    "at_risk": { "count": 0, "pct": 0, "avg_spend": 0 },
    "lost": { "count": 0, "pct": 0, "avg_spend": 0 }
  },
  "output_file": "rfm_segments_<date>.csv"
}

Output Format

CSV file rfm_segments_<YYYY-MM-DD>.csv with columns: customer_id, email, first_name, last_name, recency_days, frequency, monetary, r_score, f_score, m_score, rfm_segment

Error Handling

Error	Cause	Recovery
`THROTTLED`	API rate limit exceeded	Wait 2 seconds, retry up to 3 times
Guest orders	Orders without customer	Skip — cannot attribute to RFM profile
Single-order customers	New or one-time buyers	Include with F=1; they'll naturally score low on frequency

Best Practices

Use days_back: 365 for most stores to capture seasonal buying patterns. Use days_back: 180 for fast-fashion or consumables.
Champions and Loyal segments are ideal targets for exclusive offers and early access campaigns.
At-Risk customers should receive win-back campaigns immediately — use with customer-win-back skill.
Export Lost segment to an exclusion list to stop wasting ad spend on them.
Cross-reference with customer-cohort-analysis for cohort-level RFM trends over time.
Use with customer-spend-tier-tagger to auto-tag customers based on RFM segment.

Files

Just SKILL.md in skills/customer-ops/shopify-admin-rfm-customer-segmentation of 40RTY-ai/shopify-admin-skills.

Open the folder on GitHubat commit 6765cb4

Compare with similar skills

Shopify Admin Rfm Customer 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.

Shopify Admin Rfm Customer Segmentation compared with similar skills
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Shopify Admin Rfm Customer Segmentation this skill40RTY-ai/shopify-admin-skills	194	—	~1.9k	Automated safety check: Pass	MIT	1 mo ago
ShopifyShopify/Shopify-AI-Toolkit	592	—	~4.2k	Automated safety check: Pass	MIT	3 days ago
E-commerce Visual Copywritingfeichanggege/ecommerce-visual-copywriting-skill	867	—	~1.3k	Automated safety check: Pass	MIT	24 days ago
Reviewing Pull RequestsShopify/shopify-app-js	541	—	~1.9k	Automated safety check: Pass	MIT	yesterday
Better Designmarvkr/better-design	254	—	~1.2k	Automated safety check: Pass	MIT	18 days ago
Liquid Theme A11ybenjaminsehl/liquid-skills	120	—	~3.2k	Automated safety check: Pass	None	2 mo ago

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Works with

Shopify

Questions about Shopify Admin Rfm Customer Segmentation

What does Shopify Admin Rfm Customer Segmentation do?

Read-only: scores every customer on Recency, Frequency, and Monetary value to segment them into actionable groups (Champions, Loyal, At-Risk, Lost). Shopify Admin Rfm Customer Segmentation is an agent skill from 40RTY-ai/shopify-admin-skills. Read-only: scores every customer on Recency, Frequency, and Monetary value to segment them into actionable groups (Champions, Loyal, At-Risk, Lost).

How do I install Shopify Admin Rfm Customer Segmentation in Claude Code?

Run `npx skills add 40RTY-ai/shopify-admin-skills --skill shopify-admin-rfm-customer-segmentation -a claude-code`. Or copy the skill folder (skills/customer-ops/shopify-admin-rfm-customer-segmentation in 40RTY-ai/shopify-admin-skills) into .claude/skills/shopify-admin-rfm-customer-segmentation in your project. Claude Code loads it when a task matches its description.

How do I install Shopify Admin Rfm Customer Segmentation in Codex?

Run `npx skills add 40RTY-ai/shopify-admin-skills --skill shopify-admin-rfm-customer-segmentation -a codex`. Or copy the skill folder (skills/customer-ops/shopify-admin-rfm-customer-segmentation in 40RTY-ai/shopify-admin-skills) into .agents/skills/shopify-admin-rfm-customer-segmentation in your project. Codex loads it when a task matches its description.

Can I use Shopify Admin Rfm Customer 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 40RTY-ai/shopify-admin-skills --skill shopify-admin-rfm-customer-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/shopify-admin-rfm-customer-segmentation, .gemini/skills/shopify-admin-rfm-customer-segmentation, .github/skills/shopify-admin-rfm-customer-segmentation and .opencode/skills/shopify-admin-rfm-customer-segmentation in your project.

What does Shopify Admin Rfm Customer Segmentation need to run?

Going by SKILL.md and its folder, Shopify Admin Rfm Customer Segmentation needs the command-line tools its instructions call (shopify). Compatibility (from SKILL.md): Claude Code, Cursor, Codex, Gemini CLI.

Does Shopify Admin Rfm Customer Segmentation access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Shopify Admin Rfm Customer 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 Shopify Admin Rfm Customer Segmentation use?

Shopify Admin Rfm Customer 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 Shopify Admin Rfm Customer Segmentation use?

About 1.9k tokens (SKILL.md is roughly 7.5k 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 Shopify Admin Rfm Customer Segmentation?

Skills that share tags, products or a category with Shopify Admin Rfm Customer Segmentation: Shopify (Shopify/Shopify-AI-Toolkit, 592 stars), E-commerce Visual Copywriting (feichanggege/ecommerce-visual-copywriting-skill, 867 stars), Reviewing Pull Requests (Shopify/shopify-app-js, 541 stars) and Better Design (marvkr/better-design, 254 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Shopify Admin Rfm Customer Segmentation?

40RTY-ai (a GitHub organization) maintains it in 40RTY-ai/shopify-admin-skills, which has 194 GitHub stars. The repository holds 116 skills in this directory. The repository was last updated on August 14, 2026.

Source: 40RTY-ai/shopify-admin-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.

Install Shopify Admin Rfm Customer Segmentation

Facts

At a glance

What it does

Example prompts

Requirements

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What it can do on your machine

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Runs code

Network

Credentials

Compatibility

Context cost

Safety

SKILL.md

Purpose

Prerequisites

Parameters

Safety

RFM Segment Definitions

Workflow Steps

GraphQL Operations

Session Tracking

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