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-plugin --skill linkedin-hook-generatorgit clone --depth 1 https://github.com/TaplioOfficial/taplio-linkedin-pluginWrote 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-plugin/linkedin-hook-generator)<a href="https://agentmods.dev/skills/taplioofficial/taplio-linkedin-plugin/linkedin-hook-generator"><img src="https://agentmods.dev/badge/skills/taplioofficial/taplio-linkedin-plugin/linkedin-hook-generator/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-plugin/linkedin-hook-generator"><img src="https://agentmods.dev/badge/skills/taplioofficial/taplio-linkedin-plugin/linkedin-hook-generator.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 | $0.00100 | $0.01193 |
| Opus 5 | $0.00050 | $0.00596 |
| Sonnet 5 | $0.00020 | $0.00239 |
| Haiku 4.5 | $0.00010 | $0.00119 |
Grade A, and why
linkedin-hook-generator 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 9d 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.
This is a copy
100% identical to linkedin-hook-generator — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 84 lines — stays where its author put it; the contents beside it link to each section on GitHub.
LinkedIn Hook Generator
The first 2 lines decide whether the post gets read. This skill produces 10 of them.
When to trigger
The user says "give me hooks for X", "the opening of this post is weak", "I need a better first line", "rewrite the hook", "A/B test the opening".
Inputs to ask for
- The topic or angle of the post.
- The post body (if they have one). If not, work from the topic alone.
- The audience. Default to "professional LinkedIn audience".
The 7 hook patterns to rotate through
- Curiosity gap : "I just spent $X to learn one thing about Y."
- Contrarian : "Stop doing X. Here is why."
- Number tension : "9 out of 10 founders make this mistake."
- Personal stake : "I almost lost my company last month."
- Question : "Why do most LinkedIn posts get zero comments ?"
- Before / after : "2 years ago I had 200 followers. Today I have 50K. Here is what changed."
- Callout : "If you are a [persona] doing [action], read this."
Process
- Generate at least 1 hook per pattern (so 7 minimum).
- Add 3 more in the patterns that fit the topic best.
- For each hook, write 2 lines max (line 1 + line 2 if needed).
- Rank them from strongest to weakest based on : specificity, emotional pull, novelty, and how well they pair with the body.
Output format
TOP PICK
1. [hook line 1]
[hook line 2]
Pattern : [pattern name] | Why : [one-liner]
ALSO STRONG
2. ...
3. ...
OPTIONS
4. ...
...
10. ...
Rules
- Be specific. "I made $87,400 last quarter" beats "I made some money".
- Lead with the noun, not the verb when possible.
- Avoid words that scream AI : "delve", "leverage", "unlock", "in today's fast-paced world".
- Never put the keyword in line 1 if it sounds promotional.
- A hook that needs context to make sense is a bad hook.
Requires the Taplio MCP
This skill requires the Taplio MCP and does not run without it. Before doing anything else, call get_me. If the call succeeds, continue. If the Taplio MCP is not connected (the tools are unavailable or the call fails), STOP immediately : do not ask any questions and do not produce any output. Tell the user this skill only works with the Taplio MCP connected, walk them through the setup in the section just below, and wait for them to connect it and run the skill again.
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.
- 9d ago First seen · 84 lines · 100 tokens per session scan A 239cd5407121
linkedin-hook-generator is a skill published in the GitHub repository TaplioOfficial/taplio-linkedin-plugin (2 stars, last pushed 2mo ago), licensed MIT. It adds 100 tokens to every session and 1,193 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to linkedin-hook-generator, differing in 0 lines, and is treated as a copy.
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