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 reymerekar7/rm-skills --skill linkedin-asset-analyzergit clone --depth 1 https://github.com/reymerekar7/rm-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/reymerekar7/rm-skills/linkedin-asset-analyzer)<a href="https://agentmods.dev/skills/reymerekar7/rm-skills/linkedin-asset-analyzer"><img src="https://agentmods.dev/badge/skills/reymerekar7/rm-skills/linkedin-asset-analyzer/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/reymerekar7/rm-skills/linkedin-asset-analyzer"><img src="https://agentmods.dev/badge/skills/reymerekar7/rm-skills/linkedin-asset-analyzer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00069 | $0.00751 |
| Opus 5.5 | $0.00028 | $0.00300 |
| Sonnet 5.5 | $0.00014 | $0.00150 |
| Haiku 4.5 | $0.00007 | $0.00075 |
Grade A, and why
linkedin-asset-analyzer 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 2mo 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 — 109 lines — stays where its author put it; the contents beside it link to each section on GitHub.
LinkedIn Asset Analyzer
Overview
One job: look at a LinkedIn carousel or infographic and explain why it performed. Visual and structural analysis only — not copy critique.
When to Use
Trigger on:
- "analyze this carousel / infographic"
- "why did this perform"
- "break down this image"
- User drops an image or PDF of a LinkedIn asset without explanation
Input Formats
Images (PNG, JPG, screenshots): Use the Read tool directly on the file path. If multiple slides are separate images, read all in parallel.
PDFs: Use the pdf skill to extract slides, then analyze.
Analysis Framework
Run every asset through these 4 lenses.
1. FORMAT & LAYOUT
- Asset type: Single infographic / Multi-slide carousel / Table / Grid
- Slide count (carousel): Cover + body + CTA breakdown
- Layout pattern: Single column / Two-column / Grid / Timeline / Comparison table
- Information density: Dense / Balanced / Airy — how much per slide/section?
- Scannability: Can someone get the value in 5 seconds without reading every word?
2. VISUAL DESIGN
- Cover strength: What makes the cover slide stop-scroll? Bold text, color contrast, visual element, novelty?
- Color palette: Background + accent + highlight. Consistent? High contrast?
- Typography hierarchy: Is it immediately clear what to read first, second, third?
- Icons / imagery: None / Emoji / Custom icons / Illustrations. Do they add meaning or just decoration?
- Whitespace: Does the layout breathe or feel cluttered?
- Brand consistency: Does it look like a system or a one-off?
3. ENGAGEMENT MECHANICS
- Save trigger: Is there something worth bookmarking? Checklist / Cheat sheet / Reference table / Prompt list
- Share trigger: Would someone tag a colleague or repost this to their feed?
- Comment trigger: Does it invite a reaction, opinion, or follow-up question?
- CTA placement: Where is the follow/repost ask? Does it feel earned or bolted on?
- Algorithm fit: Carousel > infographic > single image. Does the format match the intent?
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 2mo ago First seen · 109 lines · 69 tokens per session scan A 583d1b7d47b7
linkedin-asset-analyzer is a skill published in the GitHub repository reymerekar7/rm-skills (39 stars, last pushed 3mo ago), licensed MIT. It adds 69 tokens to every session and 751 once invoked, about $0.0003 per session on Opus 5.5. 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 2026-08-30.
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