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 agentmods add skills/styfinity/linkedin-engine/linkedin-post-writernpx skills add styfinity/linkedin-engine --skill linkedin-post-writergit clone --depth 1 https://github.com/styfinity/linkedin-engineWhat 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 | $0.00057 | $0.00609 |
| Opus 5 | $0.00028 | $0.00304 |
| Sonnet 5 | $0.00011 | $0.00122 |
| Haiku 4.5 | $0.00006 | $0.00061 |
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 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 — 37 lines — stays where its author put it; the contents beside it link to each section on GitHub.
LinkedIn Post Writer
The hero skill. Turns a topic and a shred of proof into a post that earns attention and proves the competence the buyer is buying. Drafts only, never posts.
Inputs
- The topic or angle, plus any proof you have (a number, a before/after, a build): $ARGUMENTS
- The brief (persona, voice profile, offer, pains) loads automatically.
Do this
- Pick the best-fit hook formula from THE TEN, given the topic and proof: Pattern-Break, Counter-Intuitive Insight, Experience-Led Observation, Direct Consequence, Confession+Result, Numbered Promise, Enemy-Hero-Gasoline-Teaser, BREAKING/News framing, Stat-Anchored (X% vs Y%), Mechanism-Reveal.
- Write the hook so the first 210 to 235 characters (everything visible before "see more") carry all four value levers at once: dream outcome up, perceived likelihood up, time-delay down, effort down.
- Body gives a SYSTEM, not tips: name the parts and show the arrows between them. Include one copy-paste-able artefact line (a prompt, a check, a template line). Quantify one before/after in money and hours. Land one contrarian quotable line.
- Close with a comment-keyword CTA plus a connect line (e.g. "comment WORD and I'll send it").
- Total length 900 to 1,300 characters. Count it.
Output
- The post, ready to read top to bottom.
- The hook formula used (one of THE TEN).
- The visible-before-cut preview (first 210 to 235 chars, exactly what shows before "see more").
- The character count.
- A suggested comment keyword.
- A note: run /linkedin-humanizer next before posting.
Rules
- Sell the operator, not the artefact: the topic must PROVE the competence the buyer is buying, even when it is not literally the product.
- Outcome + mechanism: name the outcome and reveal the mechanism. AI does the volume, operator judgment picks the targets. Position the operator as a Revenue Partner who uses AI to do the heavy lifting.
- Proof attributes to "a post", "a client", or "an operator", never to a named person or company.
- No em-dashes. No banned hype words.
- Draft only. Pass the draft through /linkedin-humanizer before posting. Nothing auto-posts; the operator approves and publishes.
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 First seen · 37 lines · 57 tokens per session scan A 6843ddc1f7ea
linkedin-post-writer is a skill published in the GitHub repository styfinity/linkedin-engine (7 stars, last pushed 2mo ago), licensed MIT. It adds 57 tokens to every session and 609 once invoked, about $0.0003 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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