design-linkedin-post

design-linkedin-post is a skill for Claude Code from slogsdon/skills-design. It costs 86 tokens per session (3,093 once invoked), scanned A, original, MIT.

A tool for creating a LinkedIn post image and accompanying text suggestion. LinkedIn is a professional social network, and the image uses its recommended share dimensions.

In plain words
What is it for?
It creates an image canvas for announcements, milestones, opinions, or project takeaways, with optional supporting text, a call to action, and attribution.
Why use it?
It gives a post both a visual asset and a structured draft instead of requiring separate design and copy work.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Needs its repository: it runs a file that does not travel with it, so clone the repository first. The line is test -f ./design/<brand-slug>/tokens.css.

Part of the skills-design plugin — 19 skills shipped together

Good fit It creates an image canvas for announcements, milestones, opinions, or project takeaways, with optional supporting text, a call to action, and attribution.

Compare 6 skills from other repositories ↓
Install

Getting it into your agent

It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.

Clone the repo
git clone --depth 1 https://github.com/slogsdon/skills-design
agentmods
npx agentmods add skills/slogsdon/skills-design/design-linkedin-post

Made for: Claude Code.

Or install skills-design, the plugin that ships this one along with the rest of its 19 skills.

Wrote 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.

agentmods badge for design-linkedin-post

README.md
[![agentmods](https://agentmods.dev/badge/skills/slogsdon/skills-design/design-linkedin-post/github.svg)](https://agentmods.dev/skills/slogsdon/skills-design/design-linkedin-post)
Your own site
<a href="https://agentmods.dev/skills/slogsdon/skills-design/design-linkedin-post"><img src="https://agentmods.dev/badge/skills/slogsdon/skills-design/design-linkedin-post/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.

agentmods 80×15 button for design-linkedin-post

Your own site · 80×15
<a href="https://agentmods.dev/skills/slogsdon/skills-design/design-linkedin-post"><img src="https://agentmods.dev/badge/skills/slogsdon/skills-design/design-linkedin-post.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 86 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,093 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00086 $0.03093
Opus 5 $0.00043 $0.01546
Sonnet 5 $0.00017 $0.00619
Haiku 4.5 $0.00009 $0.00309

Measured 10d ago against content hash f7f8e02ca5be, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

design-linkedin-post 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.

skills/design-linkedin-post/SKILL.md · 259 lines

How it starts

The opening of the file, as written. The whole thing — 259 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Skill: linkedin-post

Produces a pixel-exact 1200×627 HTML canvas suitable for screenshotting and uploading to LinkedIn as a post image, plus a markdown block with the recommended companion text. Reads from a brand's DESIGN.md system — never hardcodes brand values.

When to use

  • User wants a visual asset for a LinkedIn post (announcement, milestone, opinion piece, takeaway from a project)
  • A DESIGN.md exists for the brand. If it doesn't, stop and tell the user to run /design-plan/design-system first.

Inputs

  • Required: brand slug, post topic / headline (1 line)
  • Optional: key claim or supporting line, CTA text, attribution (author name + role), variation hints

Output

./design/<brand-slug>/artifacts/linkedin-YYYY-MM-DD-<topic-slug>.html

Steps

1. Verify brand exists

test -f ./design/<brand-slug>/tokens.css

If missing, stop and instruct the user to build the design system first.

2. Gather the brief

Ask in one message:

1. Headline — the single sentence on the image (max 8 words for legibility at feed scale)
2. Optional supporting line (max 14 words)
3. Optional CTA text (e.g. "Read more →") — leave blank to omit
4. Attribution — your name + role, or leave blank for a clean unsigned look
5. Companion text style: insight | story | announcement | question

3. Pick variation — ARCHITECTURE FIRST

Before anything else, pick ONE architecture archetype. This is the structural skeleton; everything else is decoration. The single biggest cause of AI-editorial output is reaching for chrome-led by default.

  • Architecture archetype (most-important choice — pick FIRST):
    • chrome-led — eyebrow + headline + signature-row footer. Treat as the LAST resort. This is the AI-editorial default; using it more than once per brand creates structural sameness.
    • type-only — nothing but the type. No eyebrow, no footer, no rules. The headline IS the artifact.
    • number-led — one oversized number/stat dominates ~60%+ of canvas; the rest is short caption. Everything bows to the figure.
    • object-of-content — the artifact IS the thing being communicated. Looks like a fragment of the product (a transcript, a printed page, a list of entries, a receipt). The "post" frame disappears.
    • pattern-led — typographic pattern or repetition fills the canvas; one element breaks the pattern as the punctum.
    • inverse-text — text becomes surface. Massive headline with body text wrapping the negative space; or a block of body type with the headline carved out as a void.

Read the full file on GitHub · 259 lines

Files

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.

Changes

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.

  1. 10d ago First seen · 259 lines · 86 tokens per session scan A f7f8e02ca5be

Subscribe to this mod's changes

design-linkedin-post is a skill published in the GitHub repository slogsdon/skills-design (3 stars, last pushed 27d ago), licensed MIT. It adds 86 tokens to every session and 3,093 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.

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