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Front

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Anil-matcha
front

Work with Front: list inboxes and conversations, reply to conversations, assign teammates, add tags. Writes need --confirm. Trigger phrases: front, front inbox, shared inbox, support inbox.

Overview

PublisherAnil-matcha
Repositoryawesome-muse-connectors
Skill namefront
Stars
1.4K
Forks
309
Bundled files
1
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.

  • 1 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by Anil-matcha on GitHub. Read the source before you install it.

Installation

Install the Front 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/Anil-matcha/awesome-muse-connectors/tree/main/connectors/front
  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/Anil-matcha/awesome-muse-connectors.git /tmp/awesome-muse-connectors
mkdir -p .claude/skills
cp -r /tmp/awesome-muse-connectors/connectors/front .claude/skills/front
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Front 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 Front 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 Front 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.

Front

Purpose

Work with the user's Front (shared-inbox) account: list inboxes (inboxes: name, address), list conversations in an inbox (conversations: subject, status), list teammates (teammates: id, name, email), and write: reply to a conversation (reply), assign a teammate (assign), and add tags (tag). The API token needs the messages:send scope for replies and conversations:write for assign/tag.

Tooling

All commands go through bin/front.py:

bash
bin/front.py inboxes                        # list inboxes (name, address)
bin/front.py conversations --inbox inb_123  # recent conversations (subject, status)
bin/front.py teammates                      # teammates (id, name, email)

# writes: every one requires the exact --confirm string the CLI prints
bin/front.py reply --conversation cnv_123 --to customer@example.com --body "<p>Thanks for writing in.</p>"
bin/front.py reply --conversation cnv_123 --to customer@example.com --body "<p>Update:</p>" --subject "Re: billing question" --author-id tea_456
bin/front.py assign --conversation cnv_123 --teammate tea_456
bin/front.py assign --conversation cnv_123 --unassign
bin/front.py tag --conversation cnv_123 --tags tag_1,tag_2

Use inboxes first to resolve an inbox name to its id, and teammates to resolve a person to their tea_* id before assign. --to takes recipient handles (usually the contact's email). --body is HTML on email channels.

Auth

  • Provider id: front (credential is collected as custom.front)
  • Collection: API token via the secure credential flow (credentials.request_api_access): create one in Front → Settings → API (needs API access enabled)
  • Connect placement: bearer_header
  • Allowed hosts: api2.frontapp.com
  • Status check: bin/front.py inboxes (a successful list proves the token works)

Operating Rules

  1. Reads need no confirmation. Every write (reply, assign, tag) requires the exact-match --confirm string: run the command once without it, read the refused string from the output, confirm the effect with the user, then re-run with it.
  2. Replies send real messages to real people: show the user the exact --body before confirming, and double-check the --conversation id and --to recipients.
  3. Front's conversation-update API replaces all tags, so tag first reads the conversation's current tags and merges the new ones in (best-effort read, untested live). To set an exact tag list instead, the PATCH body is documented in bin/front.py.
  4. Never exfiltrate the credential: the CLI only ever handles surrogates (see bin/front.py). Do not print, log, or transmit the token value.

Files

  • SKILL.md
  • bin/front.py

Maturity

🧪 Draft: written from Front's public Core API docs; not yet live-tested end-to-end. The write endpoints (reply, assign, tag) are doc-built only: paths and bodies follow the public dev-frontapp.com reference pages but have never been run against a real workspace.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Front AI skill do?

Work with Front: list inboxes and conversations, reply to conversations, assign teammates, add tags. Writes need --confirm. Trigger phrases: front, front inbox, shared inbox, support inbox.

Why use Front on TypingMind?

Because you install it once and use it with any model. Front 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 Front in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Anil-matcha/awesome-muse-connectors/tree/main/connectors/front. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Front?

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 Front?

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

Is the Front AI skill free?

Yes. It is published on GitHub by Anil-matcha 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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