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Operations
Skill

/shopify-admin-customer-note-bulk-annotator

Adds internal notes to customer records in bulk — useful for post-campaign flags, import annotations, or support context.

From plugin
shopify-admin-skills
175116 skills
Install
$ npx -y skills add 40rty-ai/shopify-admin-skills --skill shopify-admin-customer-note-bulk-annotator --agent claude-code

How it fires

How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/shopify-admin-customer-note-bulk-annotator

Context preview

The summary Claude sees to decide when to auto-load this skill.

Adds internal notes to customer records in bulk — useful for post-campaign flags, import annotations, or support context.

SKILL.md

shopify-admin-customer-note-bulk-annotator.SKILL.md
name: shopify-admin-customer-note-bulk-annotator
role: customer-ops
description: "Adds internal notes to customer records in bulk — useful for post-campaign flags, import annotations, or support context."
toolkit: shopify-admin, shopify-admin-execution
api_version: "2025-01"
graphql_operations:
  - customers:query
  - customerUpdate:mutation
status: stable
compatibility: Claude Code, Cursor, Codex, Gemini CLI

Purpose

Queries customers matching a filter (tag, email list, or spend threshold) and appends a note to each customer record. Internal notes are visible to staff in Shopify Admin but not to customers. Used for post-campaign annotation, import source tracking, VIP flags, or support context.

Prerequisites

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

Parameters

| Parameter | Type | Required | Default | Description | |-----------|------|----------|---------|-------------| | store | string | yes | — | Store domain (e.g., mystore.myshopify.com) | | filter | string | yes | — | Customer filter query (e.g., `tag:vip`, `total_spent:>=500`) | | note | string | yes | — | Note text to append to matching customers | | append | bool | no | true | Append to existing note (true) or replace entirely (false) | | dry_run | bool | no | true | Preview matching customers without executing mutations | | format | string | no | human | Output format: `human` or `json` |

Safety

> ⚠️ If `append: false`, this overwrites the existing customer note entirely. Existing notes will be lost. Default is `append: true` which safely appends with a timestamp prefix. Run with `dry_run: true` to confirm the customer list before committing.

Workflow Steps

1. **OPERATION:** `customers` — query **Inputs:** `query: <filter>`, `first: 250`, select `id`, `displayName`, `note`, pagination cursor **Expected output:** Matching customers with existing notes; paginate until `hasNextPage: false`

2. Construct new note: if `append: true`, prepend `[YYYY-MM-DD] <note>` to existing note (newline-separated); if `append: false`, replace with `<note>`

3. **OPERATION:** `customerUpdate` — mutation **Inputs:** `id: <customer_id>`, `note: <new_note>` **Expected output:** `customer { id, note }`, `userErrors`

GraphQL Operations

# customers:query — validated against api_version 2025-01
query CustomersByFilter($query: String!, $after: String) {
  customers(first: 250, after: $after, query: $query) {
    edges {
      node {
        id
        displayName
        defaultEmailAddress {
          emailAddress
        }
        note
        tags
      }
    }
    pageInfo {
      hasNextPage
      endCursor
    }
  }
}
# customerUpdate:mutation — validated against api_version 2025-01
mutation CustomerUpdateNote($input: CustomerInput!) {
  customerUpdate(input: $input) {
    customer {
      id
      displayName
      note
    }
    userErrors {
      field
      message
    }
  }
}

Session Tracking

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

**On start**, emit:

╔══════════════════════════════════════════════╗
║  SKILL: Customer Note Bulk Annotator         ║
║  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>

If `dry_run: true`, prefix every mutation step with `[DRY RUN]` and do not execute it.

**On completion**, emit:

For `format: human` (default):

══════════════════════════════════════════════
OUTCOME SUMMARY
  Customers matched:   <n>
  Notes updated:       <n>
  Errors:              <n>
  Output:              annotation_log_<date>.csv
══════════════════════════════════════════════

For `format: json`, emit:

{
  "skill": "customer-note-bulk-annotator",
  "store": "<domain>",
  "started_at": "<ISO8601>",
  "dry_run": true,
  "filter": "<query>",
  "note": "<text>",
  "append": true,
  "outcome": {
    "matched": 0,
    "updated": 0,
    "errors": 0,
    "output_file": "annotation_log_<date>.csv"
  }
}

Output Format

CSV file `annotation_log_<YYYY-MM-DD>.csv` with columns: `customer_id`, `name`, `email`, `previous_note`, `new_note`

Error Handling

| Error | Cause | Recovery | |-------|-------|----------| | `THROTTLED` | API rate limit exceeded | Wait 2 seconds, retry up to 3 times | | `userErrors` on customerUpdate | Invalid input or read-only customer | Log error, skip customer, continue | | No customers match filter | Filter too narrow | Exit with 0 matches |

Best Practices

  • Always use `append: true` unless you explicitly intend to overwrite existing notes — staff notes may contain important history.
  • Include a datestamp in the `note` text itself (e.g., `"2026-04-11: Campaign X participant"`) so notes remain interpretable months later.
  • Use `dry_run: true` to confirm the customer count before annotating — a broad filter can match thousands of customers unexpectedly.
  • For import-source tracking, annotate immediately after the import run to maintain a clear audit trail.
Read more
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