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 TaplioOfficial/taplio-linkedin-claude-skills --skill linkedin-post-writergit clone --depth 1 https://github.com/TaplioOfficial/taplio-linkedin-claude-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/taplioofficial/taplio-linkedin-claude-skills/linkedin-post-writer)<a href="https://agentmods.dev/skills/taplioofficial/taplio-linkedin-claude-skills/linkedin-post-writer"><img src="https://agentmods.dev/badge/skills/taplioofficial/taplio-linkedin-claude-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/taplioofficial/taplio-linkedin-claude-skills/linkedin-post-writer"><img src="https://agentmods.dev/badge/skills/taplioofficial/taplio-linkedin-claude-skills/linkedin-post-writer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00092 | $0.01549 |
| Opus 5 | $0.00046 | $0.00775 |
| Sonnet 5 | $0.00018 | $0.00310 |
| Haiku 4.5 | $0.00009 | $0.00155 |
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 12d 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- linkedin-post-writer — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 96 lines — stays where its author put it; the contents beside it link to each section on GitHub.
LinkedIn Post Writer
Turn a raw idea into a LinkedIn post that earns the scroll-stop and the comment.
When to trigger
The user gives you a topic, an idea, an experience, an opinion, a product update, a learning, or a story and wants it turned into a LinkedIn post. They might say "write me a post about X", "help me post this", "I want to share that I did Y", "turn this into a LinkedIn post".
Inputs to ask for (only if missing)
- The raw idea, story, or topic.
- The target audience (founders, marketers, devs, sales, etc.). If missing, infer from context or ask.
- The desired format. Default to "let me pick the best one for you" and propose:
- Story : a personal anecdote with a turning point.
- Opinion : a strong stance + reasoning.
- Listicle : a numbered list of tips, mistakes, or lessons.
- Contrarian : a take that challenges conventional wisdom.
- Experience recap : "I tried X for Y days, here is what I learned".
- The CTA goal (comments, profile visits, DMs, link clicks). Default to "comments" since it boosts reach the most.
Process
- Choose the format that fits the raw input.
- Write the hook (first 2 lines, the only thing visible before "see more"). It must create curiosity, contradict an assumption, or promise a payoff.
- Write the body with short lines (max 8 words per line on average), white space, and one idea per line. No corporate filler.
- Write a CTA that fits the goal (a question for comments, a tag for shares, a link for clicks).
- Generate 3 variants of the post so the user can pick the strongest hook.
- Once the user picks a variant, render it directly in an editable block so they can tweak it in place (see "Editable block" below). Do this automatically, before saving it as a draft.
Output format
VARIANT 1 - [format name]
[hook line 1]
[hook line 2]
[body, 80 to 200 words, short lines]
[CTA]
---
VARIANT 2 - ...
VARIANT 3 - ...
After the variants, add a one-line recommendation: "I would ship Variant X because [reason]".
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.
- 12d ago First seen · 96 lines · 92 tokens per session scan A 14492ff88350
linkedin-post-writer is a skill published in the GitHub repository TaplioOfficial/taplio-linkedin-claude-skills (5 stars, last pushed yesterday), licensed MIT. It adds 92 tokens to every session and 1,549 once invoked, about $0.0005 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 2026-08-31.
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Generate a 7-day LinkedIn content plan from a theme, audience, and pillars. Produces per-day post pillar, format, hook type, CTA, posting time, daily comment targets, and a weekly inbound-readiness check. Use when the user wants to plan a week or month of content, not draft a single post.