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/rockyco/claude-linkedin-plugin/linkedin-apinpx skills add rockyco/claude-linkedin-plugin --skill linkedin-apigit clone --depth 1 https://github.com/rockyco/claude-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/rockyco/claude-linkedin-plugin/linkedin-api)<a href="https://agentmods.dev/skills/rockyco/claude-linkedin-plugin/linkedin-api"><img src="https://agentmods.dev/badge/skills/rockyco/claude-linkedin-plugin/linkedin-api.svg" alt="Measured on agentmods" 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 | $0.00049 | $0.08438 |
| Opus 5 | $0.00024 | $0.04219 |
| Sonnet 5 | $0.00010 | $0.01688 |
| Haiku 4.5 | $0.00005 | $0.00844 |
Grade A, and why
linkedin-api 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 5d 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 — 475 lines — stays where its author put it; the contents beside it link to each section on GitHub.
LinkedIn Post Authoring (Save-Local Workflow)
This skill does not publish to LinkedIn. It produces a self-contained bundle (post text + images / carousel pages) in a local linkedin/ directory. The user uploads and publishes manually at https://www.linkedin.com/feed/?shareActive=true.
Why save-only in 2026: LinkedIn's March 2026 Authenticity Update demotes automation-pattern content. The REST API also silently truncates text past ~3000 chars and adds round trips that risk shadow-truncated posts. Manual upload gives full control over preview, media order, and timing.
Local Output Convention
Every post is a folder bundle:
<project>/linkedin/
post.txt # first-3-line hook + body + hashtags, final copy-paste-ready
01-cover.png # assets in upload order (1-9 images or 5-10 PDF pages)
02-*.png
...
carousel.pdf # optional, for Document-post upload (best-performing format)
publishing-checklist.md # optional short checklist for the user
Default target directory: <project-root>/docs/linkedin/ or <project-root>/linkedin/. Ask the user if the path is ambiguous.
Algorithm Mechanics (2026)
LinkedIn's 2026 algorithm ranks by dwell time above everything else - the actual seconds a reader spends on the post. Likes barely register. Comments are weighted ~15x a like. Every authoring choice should maximize read-time and comment substance.
Dwell-time tiers
| Read duration | Engagement rate | Distribution |
|---|---|---|
| 0-3 s | 1.2% | Limited |
| 11-30 s | 6.1% | Extended |
| 31-60 s | 10.2% | Maximum |
| 61+ s | 15.6% | Exceptional (~2.5x wider reach) |
Golden Hour
The first 60-90 minutes after posting determine distribution tier. Only ~5% of posts that underperform in hour one ever recover. Tactics:
- Post during working-hour windows: Tue-Thu 8-10 AM local (primary), 12-2 PM (secondary)
- Reply to every comment within the first hour - each reply compounds dwell measurement
- Seed with 2-3 trusted colleagues who leave substantive (5+ word) comments
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.
- 5d ago First seen · 475 lines · 49 tokens per session scan A cfa415da3dab
linkedin-api is a skill published in the GitHub repository rockyco/claude-linkedin-plugin (2 stars, last pushed 1mo ago), licensed MIT. It adds 49 tokens to every session and 8,438 once invoked, about $0.0002 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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