li-dm

Solid

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.

AI & Automation 131 stars 20 forks Updated 3 days ago MIT

Install

View on GitHub

Quality Score: 87/100

Stars 20%
71
Recency 20%
100
Frontmatter 20%
70
Documentation 15%
100
Issue Health 10%
50
License 10%
100
Description 5%
100

Skill Content

# 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. - *...

Details

Author
Jakeschincariol
Repository
Jakeschincariol/linkedin-agent-skill
Created
3 days ago
Last Updated
3 days ago
Language
Python
License
MIT

Similar Skills

Semantically similar based on skill content — not just same category