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Cleanup Lists

Community
TomGranot
cleanup-lists

Audit and remove unused, empty, or duplicate list definitions from HubSpot. Identifies lists with zero members, lists not used by any workflow or email, and overlapping list criteria.

Overview

PublisherTomGranot
Repositoryhubspot-admin-skills
Skill namecleanup-lists
Stars
79
Forks
18
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by TomGranot on GitHub. Read the source before you install it.

Installation

Install the Cleanup Lists AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/TomGranot/hubspot-admin-skills/tree/main/skills/cleanup-lists
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/TomGranot/hubspot-admin-skills.git /tmp/hubspot-admin-skills
mkdir -p .claude/skills
cp -r /tmp/hubspot-admin-skills/skills/cleanup-lists .claude/skills/cleanup-lists
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Cleanup Lists in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Cleanup Lists on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Cleanup Lists is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Cleanup Lists

Audit HubSpot lists to remove clutter. Unused lists slow down the UI, confuse team members, and can mask the lists that actually matter.

Prerequisites

  • A HubSpot service key (HUBSPOT_ACCESS_TOKEN in .env; an existing legacy private app token also works) with crm.lists.read (and crm.lists.write for deletion)
  • Python 3.10+ with uv
  • Note: Lists API access may return 403 on some plan tiers. If so, perform the audit manually in the UI.

Step-by-Step Instructions

Stage 1: Plan

Confirm with the user before starting:

  1. Delete outright, or prefix with "[ARCHIVE]" first and delete next quarter?
  2. Any lists that must never be touched (suppression lists, compliance segments, active campaign audiences)?

Stage 2: Before

Inventory all lists via the Lists API (v3):

python
import os, requests
from dotenv import load_dotenv

load_dotenv()
TOKEN = os.environ["HUBSPOT_ACCESS_TOKEN"]
BASE = "https://api.hubapi.com"
HEADERS = {"Authorization": f"Bearer {TOKEN}", "Content-Type": "application/json"}

lists, offset = [], 0
while True:
    resp = requests.post(f"{BASE}/crm/v3/lists/search", headers=HEADERS,
                         json={"offset": offset, "count": 100})
    resp.raise_for_status()
    data = resp.json()
    lists.extend(data.get("lists", []))
    if not data.get("hasMore"):
        break
    offset = data.get("offset", offset + 100)

For each list, record: list ID, name, processing type (DYNAMIC/MANUAL), member count (additionalProperties), created date, last updated date.

Export to CSV for review.

Stage 3: Execute

Flag lists matching any of these criteria:

  1. Zero members and created more than 30 days ago
  2. Not referenced by any workflow, email, or ad audience
  3. Duplicate names or nearly identical filter criteria
  4. Test/temp lists (names containing "test", "temp", "copy of", "old")
  5. Static lists that have not been updated in 6+ months

Cross-reference with workflows and email campaigns before deleting — a list with zero members might still be used as an enrollment trigger.

Present the candidate list to the user and wait for explicit confirmation, then delete via DELETE /crm/v3/lists/{listId} or the UI.

Stage 4: After

  1. Re-run the inventory and confirm the deleted lists are gone.
  2. Document what was deleted (list name, ID, reason) in a cleanup log.
  3. Inform team members if any lists they created were removed.

Rollback

  • HubSpot does not have a list recycle bin. Deleted lists cannot be restored.
  • Before deleting, export the list definition (filters/criteria) so it can be recreated if needed.
  • Static lists: export member IDs before deletion if the membership data matters.

Tips

  • Run this quarterly as part of the database cleanup routine.
  • Establish a naming convention going forward (e.g., prefix with team name or purpose).
  • Archive lists by prefixing with "[ARCHIVE]" instead of deleting if you are unsure.

Frequently asked questions

What does the Cleanup Lists AI skill do?

Audit and remove unused, empty, or duplicate list definitions from HubSpot. Identifies lists with zero members, lists not used by any workflow or email, and overlapping list criteria.

Why use Cleanup Lists on TypingMind?

Because you install it once and use it with any model. Cleanup Lists is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Cleanup Lists in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/TomGranot/hubspot-admin-skills/tree/main/skills/cleanup-lists. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Cleanup Lists?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Cleanup Lists?

As many as you like. As long as a model supports skills, you can use Cleanup Lists with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Cleanup Lists AI skill free?

Yes. It is published on GitHub by TomGranot under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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