linkedin-skills is a collection of Claude Code and Codex skills for creating and managing LinkedIn content from a terminal. It helps users draft posts, comments, and replies, review their feeds, and plan a publishing cadence while requiring approval before publication. The catalogue entries are the project's skills, instructions, and plugin for using these workflows with coding agents.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add sergebulaev/linkedin-skills --skill linkedin-employee-advocacygit clone --depth 1 https://github.com/sergebulaev/linkedin-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/sergebulaev/linkedin-skills/linkedin-employee-advocacy)<a href="https://agentmods.dev/skills/sergebulaev/linkedin-skills/linkedin-employee-advocacy"><img src="https://agentmods.dev/badge/skills/sergebulaev/linkedin-skills/linkedin-employee-advocacy/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/sergebulaev/linkedin-skills/linkedin-employee-advocacy"><img src="https://agentmods.dev/badge/skills/sergebulaev/linkedin-skills/linkedin-employee-advocacy.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00082 | $0.01372 |
| Opus 5 | $0.00041 | $0.00686 |
| Sonnet 5 | $0.00016 | $0.00274 |
| Haiku 4.5 | $0.00008 | $0.00137 |
Grade A, and why
linkedin-employee-advocacy scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 129 lines — stays where its author put it; the contents beside it link to each section on GitHub.
LinkedIn Employee Advocacy
Stand up a marketing-team LinkedIn advocacy program that scales without killing authenticity. Employee posts get 8x more engagement than brand-page posts — this skill operationalizes that advantage.
When to use
- Marketing leader wants to get their team posting on LinkedIn
- User is planning an advocacy program launch
- Team is posting but output is inconsistent / off-brand / low-engagement
- Need ROI measurement framework for an existing program
- Requests: "how do I get the team posting", "launch advocacy", "scale LinkedIn across 10 people"
Input
- Team size (5-50 typical)
- Marketing goal (reach / pipeline / recruiting / thought leadership)
- Current state (everyone silent / some active / inconsistent)
- Brand guideline constraints
Output
- 14-day launch plan (if cold-starting)
- Operating model (voice capture, ideation, approval, posting, measurement)
- Cadence targets per team member (realistic, not punishing)
- KPI dashboard spec (team reach, engagement, pipeline attribution)
- Governance playbook (brand safety without blocking velocity)
Four operating principles
- Scale authentically. Individuals compose in their own voice, not corporate language. Corporate-tone team posts underperform authentic voice 3x.
- Maintain control. Brand guidelines integrated into the workflow. Review step is optional, not blocking — high-trust roles bypass review entirely.
- Remove friction. Per-post time budget: 5 minutes. Anything more and the program dies in week 3.
- Prove ROI. Track team reach, engagement, pipeline impact. Without attribution, the program gets cut at the first budget review.
Benchmarks
- Launch target: team posting within 14 days
- Active team size benchmark: 8-11 members
- Output benchmark: 70+ posts/week (at 8 members) or 3-5 posts/member/week
- Per-post time budget: 5 minutes
- Team touchpoint math: 11 people × 3 posts/week × 300 min impressions = 40,000 monthly touchpoints baseline
- Employee vs. brand page: 8x more engagement, 6-8x more reach on personal posts
What ships with it
3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2d ago Changed dca21067c266
- 13d ago First seen · 129 lines · 82 tokens per session scan A 061a9b369d85
linkedin-employee-advocacy is a skill published in the GitHub repository sergebulaev/linkedin-skills (1,826 stars, last pushed 3d ago), licensed MIT. It adds 82 tokens to every session and 1,372 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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