Skills DirectorySkills Directory
SkillsLearnSecurityCategoriesDocsCommunityBlog
Sign InSubmit Skill
Skills Directory

Security-tested agent skills for Claude, coding agents, and AI workflows.

Directory

  • Browse Skills
  • All Skills Aโ€“Z
  • Claude Skills
  • Claude Code Skills
  • Agent Skills
  • Categories
  • Submit a Skill

Learn

  • Learn Hub
  • Install Claude Skills
  • Write SKILL.md
  • Skills vs MCP
  • Directories Compared

Security

  • Security
  • Methodology
  • Secure Claude Skills
  • Security Badges

Company

  • About
  • Community
  • Blog
  • API Docs
  • Advertise

2026 Skills Directory. All rights reserved.

Back to skills

Li Comment

ASecurity

Write comments on other people's LinkedIn posts that read as a person with an opinion, not a bot. Use when the user pastes a post and wants a comment, says "comment on this", "engage with this", "what do I say here", or wants a batch of comments for their engagement round.

409 stars
0 votes
0 copies
0 views
Added 9/19/2026
ai-agentsgoreactapi

Works with

api

Security Analysis

A100/100

Scanned 9/19/2026

Install to Claude Code

$npx -y skills add Jakeschincariol/linkedin-agent-skill --skill li-comment --agent claude-code

Installs into .claude/skills of the current project.

Are you the author of Li Comment?

Add the live security badge to your README โ€” it updates automatically with every re-scan.

Security grade badge for Li Comment
[![Security: A โ€” Skills Directory](https://www.skillsdirectory.com/api/skills/jakeschincariol-li-comment/badge)](https://www.skillsdirectory.com/skills/jakeschincariol-li-comment)

More formats (shields.io, HTML) on the badges page.

Download Zip
Files
SKILL.md
---
name: li-comment
description: >-
  Write comments on other people's LinkedIn posts that read as a person with an
  opinion, not a bot. Use when the user pastes a post and wants a comment, says
  "comment on this", "engage with this", "what do I say here", or wants a batch
  of comments for their engagement round.
---

# li-comment

Commenting is the highest-leverage thing on LinkedIn and the easiest to do
badly. A comment on a post with 400 reactions gets seen by more people than
most of your own posts. A generic one gets seen by nobody and costs you
credibility with the author.

## Input

The user pastes the post text (and the author's name and role if they have
it). If they paste a screenshot, read it. If they give you a URL you cannot
open, ask them to paste the text - do not guess what the post said, and do not
use browser automation to scrape the feed.

## The nine comment types

Pick by what the post actually is. Never default to type 1.

| # | type | when | shape |
| --- | --- | --- | --- |
| 1 | **Add a datum** | post makes a claim you can support with a number | "We saw the same thing: 40% of our..." |
| 2 | **Add the missing case** | post is right but incomplete | "This holds until {condition}. Then..." |
| 3 | **Respectful disagree** | you genuinely think it is wrong | name the agreement first, then the fork |
| 4 | **Extend one line** | one sentence in the post is the good one | quote it, then build on it |
| 5 | **Ask the real question** | post skipped the hard part | one question, specific, no "curious to hear" |
| 6 | **The receipt** | you have done the thing they described | what happened, in two sentences |
| 7 | **The correction** | there is a factual error | be right, be brief, be kind, be sure |
| 8 | **The reframe** | the post has the right facts and the wrong frame | "Another way to read this:" |
| 9 | **The one-liner** | the post needs nothing, you want presence | under 12 words, must be funny or true |

## Rules

- **2 to 4 sentences.** Longer reads as a hijack. Shorter reads as filler.
- **Never open with "Great post"**, "Love this", "So true", "Couldn't agree
  more", "This resonates", or the author's first name followed by an
  exclamation mark. All six are invisible.
- **No emoji openers.** No ๐Ÿ”ฅ or ๐Ÿ‘ as a first character.
- **Never restate the post.** The author knows what they wrote and so does
  everyone reading.
- **One idea.** A comment with two points reads as a blog attempt.
- **Say the specific thing.** If the comment could sit under any post on the
  topic, it is not a comment, it is noise.
- **Disagreement is allowed and works**, but the agreement has to come first
  and be real.

## Output

Give **two options of different types**, labelled, plus a one-line reason for
the one you would post. Run both through `/li-human` first - a comment with an
em dash in it is more obviously machine-written than a post, because comments
are short and people read them closely.

```
COMMENT OPTIONS  (on @author's post about hiring)

[6 ยท Receipt]
We tried the no-resume version of this for 3 hires last year. Two were the
best hires we made. The third was a disaster, and the difference was whether
they had done the actual job before, not how they interviewed.

[3 ยท Respectful disagree]
Agree on the signal problem. But the fix that worked for us was not removing
the resume, it was giving every candidate the same 90-minute paid task. Same
outcome, far less argument internally.

Post the first. It is your own data and it concedes a failure, which is the
part people reply to.
```

## Batch mode

If the user wants an engagement round, ask for the 5-10 posts as pasted text
in one message, return one comment each in a single block, and keep a running
note of who they have already commented on this week in
`~/.claude/linkedin/log.md`. Commenting on the same three people every day is
visible and it looks like what it is.

## Never

Do not auto-post. Do not use a browser tool to publish comments on the user's
behalf. Automated posting and scraping both violate LinkedIn's User Agreement
and put the account at risk. This skill writes the comment. The user posts it.

Attribution

JakeschincariolJakeschincariol
View sourceMore from Jakeschincariol โ†’
SSkills DirectorySkills Directory

Ship a skill? Prove it's safe.

Free 120-pattern security scan, letter grade, and an embeddable README badge.

Submit a skill

Is this your skill, or is something wrong with this listing? Request removal or report an issue. Author removals are honored within 72 hours.

Comments (0)

No comments yet. Be the first to comment!

SSkills DirectorySkills Directory

Ship a skill? Prove it's safe.

Free 120-pattern security scan, letter grade, and an embeddable README badge.

Submit a skill

Related Skills

Caveman

Ultra-compressed communication mode. Cuts token usage ~75% by speaking like caveman while keeping full technical accuracy. Supports intensity levels: lite, full (default), ultra, wenyan-lite, wenyan-full, wenyan-ultra. Use when user says "caveman mode", "talk like caveman", "use caveman", "less tokens", "be brief", or invokes /caveman. Also auto-triggers when token efficiency is requested.

1023331 votes

Hyperplan

Adversarial multi-agent planning skill. Self-orchestrates 5 hostile category members (unspecified-low, unspecified-high, deep, ultrabrain, artistry) via team-mode for ruthless cross-critique debate, distills only the defensible insights, then MANDATORILY hands the distilled insight bundle to the `plan` agent for executable plan formalization. Use when planning needs maximum rigor and surfacing of weak assumptions, blind spots, and over-engineering. Triggers: 'hyperplan', 'hpp', '/hyperplan', ...

686011 votes

Mcp Code Execution

Routes multi-tool workflows through MCP servers for large datasets and pipelines. Use when Bash tool overhead is limiting throughput on data-heavy tasks.

3331 votes

catchup

Recovers prior coding-agent session context by running `catchup <agent> --since-compact`, which extracts a clean summary of a previous Codex, Claude Code, Antigravity, OpenCode, or Pi Agent session. Use when the user says "catch up", "what did the last session do", "get me up to speed", "I switched agents", or asks to recover/summarize a previous session before continuing. Do NOT use for the current conversation, git history, or any non-agent log.

611 votes

math-skill

A comprehensive mathematical reasoning skill for AI assistants โ€” handles arithmetic to research-level problems with rigorous step-by-step reasoning, systematic verification, and transparent uncertainty handling

381 votes
View all in ai-agents โ†’