linkedin-first-dm
Skill9 starsChanged 4 months agoMITView on GitHub
Write the first DM under 150 characters once a connection is accepted, two variants, value-first and asking for nothing. Use right after a target accepts your request.
In this repository28 other files it gives its agents.
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- linkedin-comment-engineSkill
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- linkedin-engage-planSkill
- linkedin-engager-analyticsSkill
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- linkedin-hook-labSkill
- linkedin-humanizerSkill
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- linkedin-onboardSkill
- linkedin-outreachSkill
- linkedin-post-autopsySkill
- linkedin-post-writerSkill
- linkedin-profile-auditorSkill
- linkedin-reply-triagerSkill
- linkedin-repurposerSkill
- linkedin-sell-by-chatSkill
- linkedin-signal-stackSkill
- linkedin-story-minerSkill
- linkedin-strategistSkill
- linkedin-voice-profilerSkill
- linkedin-warm-list-builderSkill
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The file
We split this skill into the rules it gives an agent
5 rules. About 0 are common, 5 are distinctive, and 0 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈5
Distinctive · estimate
This author's own choices. Worth a look.
0
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 16
Write two first-DM variants so the operator can pick:
- Distinctive: line 23
If the operator wants the message smoothed before sending, run /linkedin-humanizer on the draft.
- Distinctive: line 27
No ask, no pitch, no link.
- Distinctive: line 28
Every variant ends on an open question about their world.
- Distinctive: line 29
No em-dashes, no exclamation marks, no "hope you're well", no "I came across your profile".
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
LinkedIn First DM
The accept is not the win, the conversation is. This skill writes the opener that earns a reply without asking for anything.
Inputs
- The accepted target and the hook that connected you (a post, a comment thread, a mutual, a shared signal): $ARGUMENTS
- The brief (persona tone, pains, offer) loads automatically.
Do this
Write two first-DM variants so the operator can pick:
- Variant A - value-first. Reference the real hook, give one genuine, specific observation about their world, then end on an open question.
- Variant B - genuinely curious. Lead with curiosity about something specific to them, no observation needed, then end on a different open question. Both must be UNDER 150 characters. Count every character. Ask for nothing: no call, no offer, no link, no pitch. End each on an open question they would actually want to answer.
Output
Variant A and Variant B, each labelled with its exact character count. After both, a one-line note: stop-on-reply (do not send a follow-up until they reply). If the operator wants the message smoothed before sending, run /linkedin-humanizer on the draft. When replies land, hand them to /linkedin-reply-triager.
Rules
- Under 150 characters, counted and shown. If over, cut and recount.
- No ask, no pitch, no link. Value or curiosity only.
- Every variant ends on an open question about their world.
- No em-dashes, no exclamation marks, no "hope you're well", no "I came across your profile".
- Reads like a text from a peer, references one real, specific hook.
- Draft only. Claude drafts, the operator approves. Nothing is sent without explicit approval, and sending happens only through the connected CLI/MCP layer wired to your own LinkedIn session or a provider key, hard-capped at 20 actions per day for new accounts.
Does it work?
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Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
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Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

