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-post-writergit 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-post-writer)<a href="https://agentmods.dev/skills/sergebulaev/linkedin-skills/linkedin-post-writer"><img src="https://agentmods.dev/badge/skills/sergebulaev/linkedin-skills/linkedin-post-writer/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-post-writer"><img src="https://agentmods.dev/badge/skills/sergebulaev/linkedin-skills/linkedin-post-writer.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 | $0.00120 | $0.03363 |
| Opus 5 | $0.00060 | $0.01682 |
| Sonnet 5 | $0.00024 | $0.00673 |
| Haiku 4.5 | $0.00012 | $0.00336 |
Grade A, and why
linkedin-post-writer 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 today.
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 — 128 lines — stays where its author put it; the contents beside it link to each section on GitHub.
LinkedIn Post Writer
Ship long-form LinkedIn posts using hook formulas that actually performed in 2025-2026 (verified engagement multipliers).
When to use
- User says "write me a LinkedIn post about X"
- User has a topic + a rough angle and needs a hook + structure
- User wants to pick from known-winning formats and fill in their voice
- User wants to audit + schedule in one flow
Formulas this skill can use
| Code | Formula | Reference eng | Best for |
|---|---|---|---|
| F1 | Platform Risk Anaphora | 4,240 | Category/platform posts, product-as-fix |
| F2 | R.I.P. Obituary | 3,822 | Era-ending claims, industry pivots |
| F3 | Year-over-Year Pivot | 494, 3.74x | Identity shifts, founder reflection |
| F4 | Time-Anchor Confession | 1,519+ | Vulnerability, voice reset, ICP re-targeting (2026: use with care, see caveats) |
| F5 | Self-Proving Meta | 1,082 / 435 comments | Commitment-based posts, tests in public |
| F6 | Comment-Gate Lead Magnet | 717-3,008 | List building (2026: use with care, real deliverable only, see caveats) |
| F7 | Odd-Precision Money Ledger | 1,755, 9.4x | Founder build-log, cost breakdowns (2026: strongest opener, number-first) |
| F8 | Paid-vs-Free Reversal | 550, 19.64x | Free framework give-away |
| F9 | Curiosity-Gap Teaser | 306, 4.25x | Emergent behavior, behind-the-scenes (2026: use with care, pay off in 2 lines) |
| F10 | Contrarian + Historical Receipts | 3,083 | Sacred-cow takes, AI/tech cycles |
| F11 | Emotional Cold-Open | high-reach* | Real story with emotional stakes (likes) |
| F12 | Permission Slip | comment-heavy* | Encouragement, reassurance (comments; 2026: use with care, needs a dated fact) |
| F13 | Bait-and-Switch Reversal | high-reach* | Policy/process change that's an upgrade (likes) |
| F14 | Named Gratitude / Tribute | repost-heavy* | Thanking mentors / team / departing colleague (reposts) |
| F15 | Explain-to-Kids | save-heavy* | Demystifying jargon (saves) |
| F16 | Status-Strip Humility | like-heavy* | Senior voice wanting warmth not distance (likes) |
| F17 | Controlled A/B Anecdote | structural† | One-variable comparison, delegation/AI takes (comments) |
| F18 | False-Binary Dissolve | structural† | "Both obvious answers fail" governance/strategy (comments/reposts; 2026: it is the post's one contrast) |
| F19 | Anecdote-Meets-Evidence Bridge | structural† | Personal noticing + a data stack (comments/saves) |
| F20 | Diverging-Curves Close | structural† | Two trajectories that diverge, quotable maxim (reposts) |
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.
- today Changed f928c631c75a
- 3d ago Changed · +19 lines 14b5298191a9
- 10d ago First seen · 109 lines · 120 tokens per session scan A d421c55b3bda
linkedin-post-writer is a skill published in the GitHub repository sergebulaev/linkedin-skills (1,489 stars, last pushed today), licensed MIT. It adds 120 tokens to every session and 3,363 once invoked, about $0.0006 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.
Other skills, from other repositories
linkedin-content-calendar-planner
Generate a 4-week LinkedIn content calendar tuned to the user's pillars, posting cadence, and audience. Returns a day-by-day plan with topic, format, hook angle, and CTA per post. Use when the user wants a system for the next month instead of inventing content every morning. Once the plan is confirmed it writes a…
linkedin-niche-definer
Help the user define (or sharpen) their LinkedIn niche : audience, problem they solve, unique angle, and one-line positioning. The skill walks the user through a 7-question diagnostic, then synthesizes a positioning statement they can use across headline, About, and posts. Use when the user says "I do not know what to…
linkedin-swipe-file-builder
Help the user assemble a personal swipe file of high-performing LinkedIn posts, organized by hook pattern, format, and angle. The skill defines the structure, asks for inputs, turns saved posts into a usable reference library, then drafts the user's own post for every reference in the file (reusing structure, not…
linkedin-analytics-interpreter
Translate raw LinkedIn analytics (impressions, engagement rate, profile visits, follower growth, top posts) into a clear diagnosis : what is working, what is not, and 3 specific actions to take next month. Use when the user has numbers but does not know what they mean or what to do about them. Requires the Taplio MCP…
linkedin-audience-persona-builder
Build a sharp, post-ready persona of the user's target LinkedIn audience : role, pains, jobs to be done, vocabulary, aspirations, what content they consume, what objections they raise. Use when the user is starting on LinkedIn or when their content does not resonate (low comments, no DMs, traffic without conversion).…
linkedin-content-pillars-builder
Define 3 to 5 LinkedIn content pillars consistent with the user's positioning, plus 5 to 10 post topics for each pillar. Pillars are the recurring themes that make a creator recognizable. Use after the user has defined their niche, or when their content feels random and they want a system. Requires the Taplio MCP…