li-comment
Skill2 starsChanged 43 days agoMITView on GitHub
Write a LinkedIn comment on someone else's post in the user's voice, picked from nine comment types matched to what the post actually is. Use when the user wants to comment on a post, pastes a post and says "comment on this", or asks for engagement ideas. Never writes "Great post!". Never posts the comment itself.
8 other projects use a version of this.
Adopted by
Most recently taken up by
- furkanbilalakyuz/linkedin-agent-skill-trtheir own version, first seen Nov 8, 2026
- mkmlabs-ai/linkedin-agenttheir own version, first seen Nov 8, 2026
- mubaid/dsh-linkedin-agenttheir own version, first seen Oct 25, 2026
- robbiehaynes/job-searchtheir own version, first seen Oct 20, 2026
- postzen-dev/linkedin-agent-skilltheir own version, first seen Oct 15, 2026
- avi691/linkedin-agent-skilltheir own version, first seen Oct 8, 2026
Other versions8 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 8
- Jakeschincariol/linkedin-agent-skill★ 514same name
- avi691/linkedin-agent-skill★ 5same name
- mkmlabs-ai/linkedin-agent★ 4same name
- nessalazne/linkedin-agent-skill★ 3same name
- postzen-dev/linkedin-agent-skill★ 3same name
- furkanbilalakyuz/linkedin-agent-skill-tr★ 0same name
- mubaid/dsh-linkedin-agent★ 0same name
- robbiehaynes/job-search★ 0same name
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository12 other files it gives its agents.
- AGENTS.mdAGENTS.md
- li-auditSkill
- li-carouselSkill
- li-dmSkill
- li-humanSkill
- li-inboxSkill
- li-planSkill
- li-postSkill
- li-profileSkill
- li-replySkill
- li-repurposeSkill
- li-voiceSkill
The file
We split this skill into the rules it gives an agent
6 rules. 0 are common, 6 are distinctive, and 0 are very specific to this project.
0
Common
Most of the 8 edited versions we read keep these.
6
Distinctive
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 21
Read the target post twice.
- Distinctive: line 50
No hashtags in comments. No links unless the poster asked for one.
- Distinctive: line 70
Never pitch, never link-drop, never "check out my post on this".
- Distinctive: line 71
Never argue to win. A counter comment that humiliates the poster costs more audience than it gains.
- Distinctive: line 73
Never comment-bait the algorithm ("comment X and I'll DM you") under someone else's post.
- Distinctive: line 75
If the post is rage bait, grief, or a layoff announcement, say so and offer type 9 or decline.
“Common” is measured: kept by at least 6 in 10 of the 8 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
li-comment
Comments are the cheapest distribution on LinkedIn: a good one is read by the poster's entire audience. This skill writes the comment. The user posts it. It never publishes anything itself.
Before you write
- Load the voice profile (see
li-post:~/.agents/linkedin/voice.mdfirst, then the Claude/Copilot fallbacks; if missing, invokeli-voice). - Read the target post twice. Identify what it actually is: a story, a data drop, a hot take, a question, a milestone, advice, a contrarian claim, a how-to, or a personal moment. The type decides the comment.
The nine types
| # | Type | Use when the post is... | The move |
| 1 | Extend | advice / how-to | Add the missing step or the exception |
| 2 | Counter | hot take / contrarian | Steelman it, then add the boundary condition |
| 3 | Evidence | data drop / claim | Add your own number that confirms or complicates |
| 4 | Story | personal story | One short parallel story, then out |
| 5 | Question | any strong post | Ask the question the post made you genuinely curious about |
| 6 | Reframe | milestone / announcement | Name what the milestone actually proves |
| 7 | Distill | long advice post | Compress their point into one quotable line, then add one nuance |
| 8 | Bridge | question post | Answer it briefly, then connect it to your own experience |
| 9 | Witness | personal moment | Acknowledge it like a person, not a brand |
The loop
1. Name the type. Say which of the nine you picked and why, in one line.
2. Draft it. Rules:
- 40-120 words. A comment is not a post.
- Open with the substance, not the greeting. No "Great post!" and no "Thanks for sharing" anywhere in it.
- One idea. The comment makes one point and stops.
- Match the poster's energy but keep the user's voice.
- No hashtags in comments. No links unless the poster asked for one.
3. Humanize it. Invoke the li-human skill before showing the draft.
4. Print the block. Copy-ready in a fenced block, then:
COMMENT READY
type: #3 Evidence
length: 68 words
humanizer: 2 artefacts stripped, human score 88 PASS
Paste it yourself. Reply "yes" to log it.5. Never publish. On "yes", append to ~/.agents/linkedin/log.md with
the date and the commented post's author and first line.
What not to do
- Never pitch, never link-drop, never "check out my post on this".
- Never argue to win. A counter comment that humiliates the poster costs more audience than it gains.
- Never comment-bait the algorithm ("comment X and I'll DM you") under someone else's post.
- If the post is rage bait, grief, or a layoff announcement, say so and offer type 9 or decline. Not every post deserves engagement.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
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
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
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.

