Li Inbox

CommunityPopular

Jakeschincariol

li-inbox

Triage the LinkedIn inbox - sort connection requests and DMs into leads, recruiters, peers and spam, and draft the replies worth sending. Use when the user says "my inbox is a mess", "triage my DMs", "should I reply to this", pastes a batch of LinkedIn messages, or is drowning in connection requests.

Overview

Publisher	Jakeschincariol
Repository	`linkedin-agent-skill`
Skill name	`li-inbox`
Stars	1.3K
Forks	192
Bundled files	Instructions only
License	MIT
Links	Skill source Repository Homepage

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 Jakeschincariol on GitHub. Read the source before you install it.

Installation

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

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.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/Jakeschincariol/linkedin-agent-skill/tree/main/skills/li-inbox
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.

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/Jakeschincariol/linkedin-agent-skill.git /tmp/linkedin-agent-skill
mkdir -p .claude/skills
cp -r /tmp/linkedin-agent-skill/skills/li-inbox .claude/skills/li-inbox

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Li Inbox 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 Li Inbox 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 Li Inbox 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.

li-inbox

Most LinkedIn inboxes are 80% noise, and the cost of that noise is that the 20% goes unanswered for a week. This skill separates them, then writes only what is worth writing.

Input

The user pastes the messages. Screenshots are fine. Do not log into their account or read their inbox with a browser tool.

Sort into five

bucket	signal	action
LEAD	describes a problem the user solves, or asks about working together	reply today, full answer
RECRUITER	a role, a company, a salary band	reply if the role is real, one line if not
PEER	someone in the same field with something to say	reply this week, keep it human
ASK	wants advice, time, an intro, a favour	reply if it is cheap and specific, decline cleanly if not
SPAM	agency pitch, lead-gen sequence, crypto, "quick question" with no question	archive, no reply

Print the counts first. Seeing "3 leads, 2 recruiters, 41 spam" is most of the value.

Detecting a sequence

Automated outreach has a shape: an invite note with no specifics, a message that arrives within minutes of the accept, "quick question", "I noticed you're in {industry}", a calendar link in message one, then a bump exactly four days later. When you see it, mark it SPAM and say which tell gave it away. The user does not owe a reply to a script.

Replies

LEAD - answer the actual question in the message, in full, for free. If it is a fit, the offer is one sentence at the end. If it is not, say so and point them somewhere useful. Both outcomes are good.
RECRUITER - if the role is genuinely interesting, ask the three things the message left out: comp band, level, and whether it is in-office. If it is not, one line: not looking, happy to refer, and mean the refer.
ASK - if it costs under ten minutes and is specific, do it. If it is "can I pick your brain", decline in one warm sentence and give them the one answer you would have given on the call. That is the polite version and it is also the more useful one.
DECLINES are short, warm and final. No "let's revisit in Q3" if there is no Q3.

Output

Grouped by bucket, counts first, drafts only for the buckets that get replies, each one humanized. Then the gate: the user sends them.


INBOX  ·  52 items  ·  3 LEAD, 2 RECRUITER, 4 PEER, 2 ASK, 41 SPAM

SPAM  (41) - archive. 38 are the same sequence: no-specifics invite,
"quick question" within 4 minutes of accept, calendar link in message one.

Frequently asked questions

What does the Li Inbox AI skill do?

Why use Li Inbox on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Jakeschincariol/linkedin-agent-skill/tree/main/skills/li-inbox. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Li Inbox?

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 Li Inbox?

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

Is the Li Inbox AI skill free?

Yes. It is published on GitHub by Jakeschincariol 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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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

li-inbox

Input

Sort into five

Detecting a sequence

Replies

Output

Frequently asked questions

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