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 SkillMedev/social-media-studio --skill linkedin-post-writergit clone --depth 1 https://github.com/SkillMedev/social-media-studioWrote 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/skillmedev/social-media-studio/linkedin-post-writer)<a href="https://agentmods.dev/skills/skillmedev/social-media-studio/linkedin-post-writer"><img src="https://agentmods.dev/badge/skills/skillmedev/social-media-studio/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/skillmedev/social-media-studio/linkedin-post-writer"><img src="https://agentmods.dev/badge/skills/skillmedev/social-media-studio/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 | $0.00118 | $0.01579 |
| Opus 5 | $0.00059 | $0.00790 |
| Sonnet 5 | $0.00024 | $0.00316 |
| Haiku 4.5 | $0.00012 | $0.00158 |
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 10d 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 — 134 lines — stays where its author put it; the contents beside it link to each section on GitHub.
LinkedIn Post Writer
Write posts for how people actually read LinkedIn: on a phone, fast, in a crowded feed. The feed truncates after roughly two lines, so the costly mistake is spending effort on the body while line one fails to earn the "see more" click - and then abandoning the post at publish, when the first hour of engagement decides whether the algorithm shows it to anyone at all.
Operating procedure
Step 1: Gather inputs
- The story or idea - one concrete moment, result, or claim. If the user offers a vague topic ("leadership"), push for a specific incident or number; specificity is the post.
- The single takeaway a reader should leave with (one, not five).
- Proof details: numbers, timeframes, names of situations (anonymized as needed). Label estimates as estimates.
- The engagement goal: comments (default - comments drive reach hardest), profile visits, or a lead-magnet offer.
- Whether the user can be online for 60 minutes after posting (this changes the close - see Step 5).
Step 2: Write the hook (first 2 lines)
The opening must earn the "see more" click before truncation.
- Lead with tension, a number, a contrarian claim, or a concrete moment.
- No throat-clearing ("I've been thinking lately...").
- No hashtags in the hook - they read as spam up top.
Hook patterns that work:
- "I [did X]. It [unexpected result]. Here's what I learned."
- "Most people get [topic] wrong. Here's the part they miss."
- "[Number] [thing] in [time]. The breakdown:"
Step 3: Structure the body
- One idea per line. Short lines. Generous line breaks - the white space is the format.
- 5-12 short paragraphs, most only 1-2 lines.
- Build toward one takeaway, not five.
- Lists use line-break bullets, not markdown bullets (LinkedIn renders markdown as literal characters).
- Voice: conversational, first person, specific. Concrete details beat adjectives - "cut onboarding from 9 days to 2" beats "improved onboarding dramatically". No buzzword stacking; no "thrilled to announce" unless it is truly an announcement.
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.
- 10d ago First seen · 134 lines · 118 tokens per session scan A cc4a4e9c6d35
LinkedIn Post Writer is a skill published in the GitHub repository SkillMedev/social-media-studio (1 stars, last pushed 2mo ago), licensed MIT. It adds 118 tokens to every session and 1,579 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 2026-08-31.
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