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 TaplioOfficial/taplio-linkedin-claude-skills --skill linkedin-carousel-buildergit clone --depth 1 https://github.com/TaplioOfficial/taplio-linkedin-claude-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/taplioofficial/taplio-linkedin-claude-skills/linkedin-carousel-builder)<a href="https://agentmods.dev/skills/taplioofficial/taplio-linkedin-claude-skills/linkedin-carousel-builder"><img src="https://agentmods.dev/badge/skills/taplioofficial/taplio-linkedin-claude-skills/linkedin-carousel-builder/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/taplioofficial/taplio-linkedin-claude-skills/linkedin-carousel-builder"><img src="https://agentmods.dev/badge/skills/taplioofficial/taplio-linkedin-claude-skills/linkedin-carousel-builder.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 | $0.00089 | $0.01361 |
| Opus 5 | $0.00044 | $0.00681 |
| Sonnet 5 | $0.00018 | $0.00272 |
| Haiku 4.5 | $0.00009 | $0.00136 |
Grade A, and why
linkedin-carousel-builder 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 12d 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-carousel-builder — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 94 lines — stays where its author put it; the contents beside it link to each section on GitHub.
LinkedIn Carousel Builder
Carousels reach far because they keep people swiping. This skill writes the script.
When to trigger
The user says "make a carousel about X", "turn this into slides", "I have a framework, build a carousel", "this would work better as slides".
Inputs to ask for
- The topic or framework.
- The number of slides (default to 8 to 10, the sweet spot).
- The audience.
- The CTA goal (DM, profile visit, link click, comment).
Carousel structure
Always 3 zones :
- Cover slide (slide 1) : the hook. One promise, one bold visual idea, no fluff.
- Value slides (slides 2 to N-1) : one idea per slide. Title + 1 to 3 short lines + optional micro-example.
- Closing slide (last slide) : the CTA. Tell the reader exactly what to do.
Process
- Distill the topic into a promise that fits on a cover slide ("7 mistakes that kill your reach", "How I write a LinkedIn post in 12 minutes").
- Break the promise into N-2 atomic ideas.
- Order the slides so each one earns the swipe : start with the most counter-intuitive, end with the most actionable.
- Write a closing slide with one clear CTA ("Save this", "Comment X", "DM me Y", "Follow for more on Z").
Output format
SLIDE 1 - COVER
Title : [the promise]
Subtitle : [optional, one line]
Visual idea : [what to draw / show]
SLIDE 2 - [idea name]
Title : [short, punchy]
Body :
- [line 1]
- [line 2]
- [line 3]
Visual idea : [optional]
... (repeat for each slide)
SLIDE N - CTA
Title : [CTA headline]
Body : [why they should act]
Visual idea : [arrow, button, profile photo, etc.]
CAPTION (the LinkedIn post body that goes with the carousel) :
[2 to 4 short lines that hook, set context, and tell people to swipe]
Rules
- One idea per slide. If a slide has 2 ideas, split it.
- Cover slide title : max 7 words, ideally a number + payoff.
- Closing slide CTA : one action, not three.
- Caption : do not repeat the slides, tease them.
- Slides 2-3 carry the heaviest swipe-through drop. Put your strongest content there.
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.
- 12d ago First seen · 94 lines · 89 tokens per session scan A 2e89514b2d6e
linkedin-carousel-builder is a skill published in the GitHub repository TaplioOfficial/taplio-linkedin-claude-skills (5 stars, last pushed 1mo ago), licensed MIT. It adds 89 tokens to every session and 1,361 once invoked, about $0.0004 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.
Other skills, from other repositories
linkedin-humanizer
Remove the AI tells human readers and LinkedIn's AI-slop filter react to in a post or comment: 2026 vocabulary by paragraph density, reveal bridges, staccato fragments, stacked triads, performed sincerity. Tiered rewriter (forensic / strict / aesthetic / all) plus --mode audit pass-fail review and --mode profile voice…
linkedin-marketing
Plan, draft, audit, and publish LinkedIn posts and comments. Use when the user wants to write a viral LinkedIn post, draft a comment or reply on any LinkedIn post URL, audit a draft against 2026 algorithm heuristics, remove AI tells, extract hook formulas from viral posts, or plan a week of content. Powered by the…
linkedin-reply-handler
Draft a reply to a specific existing LinkedIn comment from its URL. Use when the user wants to reply to a comment on any post, or follow up after an author replied to them. Parses the commentUrn, resolves the correct parentComment target (LinkedIn flattens threads to 2 levels), and posts via Publora on approval. Not…
linkedin-post-writer
Draft a new LinkedIn post from scratch using one of 20 2026 hook formulas (anaphora, R.I.P., time-anchor, curiosity-gap, contrarian, controlled A/B, false-binary, and more) plus a founders-edition angle library, picked by engagement goal (comments, reposts, likes, saves). Runs the humanizer pass and schedules via…
linkedin-comment-drafter
Draft a LinkedIn comment on someone else's post from its URL, or reshare (repost) it to your feed with optional commentary. Use when the user pastes a post URL and asks to comment, engage, be first commenter, or repost with their thoughts. Produces 1-3 variants in the user's voice, picks a reaction, and publishes via…
linkedin-content-planner
Generate a 7-day LinkedIn content plan from a theme, audience, and pillars. Produces per-day post pillar, format, hook type, CTA, posting time, daily comment targets, and a weekly inbound-readiness check. Use when the user wants to plan a week or month of content, not draft a single post.