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Li Dm

CommunityPopular
Jakeschincariol
li-dm

Write connection notes and DM follow-ups that get replies - the 200-character invite, the first message, and the two follow-ups. Use when the user says "write a connection request", "DM this person", "outreach message", "how do I follow up", or is reaching out to someone specific on LinkedIn.

Overview

PublisherJakeschincariol
Repositorylinkedin-agent-skill
Skill nameli-dm
Stars
1.3K
Forks
192
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 Jakeschincariol on GitHub. Read the source before you install it.

Installation

Install the Li Dm 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/Jakeschincariol/linkedin-agent-skill/tree/main/skills/li-dm
  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/Jakeschincariol/linkedin-agent-skill.git /tmp/linkedin-agent-skill
mkdir -p .claude/skills
cp -r /tmp/linkedin-agent-skill/skills/li-dm .claude/skills/li-dm
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Li Dm 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 Dm 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 Dm 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-dm

The invite note is 200 characters. The first DM decides whether there is a second one. Neither is a pitch.

Before writing, get the specifics

Ask for, in one batched question:

  1. Who - name, role, company.
  2. The hook - the actual reason to reach out now. A post they wrote, a thing their company shipped, a mutual connection, a talk they gave. Not "they fit my ICP".
  3. What the user wants - a conversation, a referral, a job, a sale. Be honest internally, even if the message does not lead with it.

If there is no specific reason to message this person today, say so. A message with no reason is what everyone else sends, and it is why their reply rate is 2%.

The invite note (200 characters)

{one specific reference to them} + {one line of who you are} + {no ask}

The note asks for nothing. It exists to make the accept obvious. Under 200 characters including spaces - count them and show the count.

Saw your post on killing the discovery call - we did the same thing in March
and it worked. I run ops at a 12-person studio. Would like to follow along.
                                                                    [187/200]

The first message, after they accept

Wait a day. Then:

  • Two to four sentences. A screen of text is a delete.
  • Reference the specific thing from the note - continuity is the whole reason the note was specific.
  • Give something before asking. A number, a template, a name, an answer.
  • One ask, and make it small. "Worth a 15-minute call?" beats "let me walk you through our platform".
  • No calendar link in message one. It reads as a funnel, because it is.

Follow-ups

Two. That is the number.

  • +4 days - add something new. Never "just bumping this" or "following up on my last message". If you have nothing new, you have no follow-up.
  • +10 days - the close-the-loop message. Say you will stop, and mean it. This one gets a surprising share of the total replies, because it removes the pressure.

Then stop. A third follow-up converts nobody and costs the relationship.

Never

  • Never send an automated connection or message sequence. Automated outreach tools violate LinkedIn's User Agreement and get accounts restricted.
  • Never fabricate a mutual connection, a shared school, or having read something the user has not read.
  • Never write the message that opens "I hope this message finds you well".
  • Never send more than 20 invites a day. Beyond that, LinkedIn throttles the account, and a throttled account is a dead one.

Output

The invite note with its character count, the first message, and both follow-ups with the day they go out. All humanized through /li-human. The user sends every one of them by hand.

Frequently asked questions

What does the Li Dm AI skill do?

Write connection notes and DM follow-ups that get replies - the 200-character invite, the first message, and the two follow-ups. Use when the user says "write a connection request", "DM this person", "outreach message", "how do I follow up", or is reaching out to someone specific on LinkedIn.

Why use Li Dm on TypingMind?

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

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

Which AI models can use Li Dm?

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 Dm?

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

Is the Li Dm 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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