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 tang-vu/social-posting-skills --skill post-linkedingit clone --depth 1 https://github.com/tang-vu/social-posting-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/tang-vu/social-posting-skills/post-linkedin)<a href="https://agentmods.dev/skills/tang-vu/social-posting-skills/post-linkedin"><img src="https://agentmods.dev/badge/skills/tang-vu/social-posting-skills/post-linkedin/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/tang-vu/social-posting-skills/post-linkedin"><img src="https://agentmods.dev/badge/skills/tang-vu/social-posting-skills/post-linkedin.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 | $0.00015 | $0.01959 |
| Opus 5 | $0.00008 | $0.00979 |
| Sonnet 5 | $0.00003 | $0.00392 |
| Haiku 4.5 | $0.00002 | $0.00196 |
Grade A, and why
post-linkedin 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 11d 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 — 232 lines — stays where its author put it; the contents beside it link to each section on GitHub.
LinkedIn Posting Skill
Platform Overview
LinkedIn is the professional networking platform with 1B+ members. It's the best platform for B2B thought leadership, career content, and professional brand building. LinkedIn organic reach is still excellent compared to other platforms.
Platform Constraints
- Character Limit: 3,000 characters per post
- Media: Images, videos, documents (carousel PDFs), polls
- Hashtags: 3-5 per post (at the bottom)
- Links: Put in comments — links in body reduce reach by 25-35%
- Linkless posts: Get 6x more reach and 18x more comments than posts with links
- Videos: Native video gets 5x more reach than YouTube links
- Carousels: Document posts get 2-3x reach
- 80/20 Rule: 80% native content, 20% with links (in comments)
AI Content Warning (2025)
LinkedIn's algorithm now scrutinizes AI-generated content. Overly generic or automated posts get reduced reach. Authentic, human-driven content is strongly prioritized.
- Posts analyzed for AI-generated material
- Generic, template-like content is penalized
- Add personal stories, specific details, and genuine voice to stand out
- Human oversight is essential even when using AI to draft
Link Placement Strategy
MANDATORY: Put links in the FIRST COMMENT, NEVER in the post body.
- Links in the body reduce reach by 25-35% (confirmed by LinkedIn's own algorithm)
- Linkless posts get 6x more reach and 18x more comments
- The ONLY correct strategy: Write a text-only post, publish it, then immediately add a comment with the link
- Even "link in bio" is better than link in body
- This is the single most important rule for LinkedIn reach
Posting Method: MANUAL PASTE
LinkedIn blocks browser automation via system policy. The agent generates content and saves it to
posts/drafts/linkedin_post.md. You paste it manually.
Manual Paste Steps
- Agent generates LinkedIn-optimized content
- Content saved to
posts/drafts/linkedin_post.md - User opens linkedin.com in their browser
- User pastes the content into the post composer
- User adds any images or documents manually
- User clicks "Post"
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.
- 11d ago First seen · 232 lines · 15 tokens per session scan A f877328096bb
post-linkedin is a skill published in the GitHub repository tang-vu/social-posting-skills (9 stars, last pushed 6mo ago), licensed MIT. It adds 15 tokens to every session and 1,959 once invoked, about $0.0001 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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