cover-image-pipeline

cover-image-pipeline is a skill for Claude Code from ur-grue/autopunk-media-skills. It costs 54 tokens per session (2,424 once invoked), scanned A, original, MIT.

A coordinated set of image prompts for one cover concept in several formats and crop shapes. It accounts for each layout instead of simply resizing one image.

In plain words
What is it for?
Use it to plan cover artwork, episode releases, publication issues, and multi-platform campaigns.
Why use it?
A square podcast image, a wide YouTube thumbnail, and a vertical social post need different compositions. This helps keep the same idea and visual identity across them.

Skill for Claude Code

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

Part of the autopunk-media-skills plugin — 187 skills shipped together

Good fit Use it to plan cover artwork, episode releases, publication issues, and multi-platform campaigns.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/ur-grue/autopunk-media-skills/cover-image-pipeline
Install

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.

Any agent
npx skills add ur-grue/autopunk-media-skills --skill cover-image-pipeline
Clone the repo
git clone --depth 1 https://github.com/ur-grue/autopunk-media-skills

Made for: Claude Code.

Or install autopunk-media-skills, the plugin that ships this one along with the rest of its 187 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 cover-image-pipeline

README.md
[![agentmods](https://agentmods.dev/badge/skills/ur-grue/autopunk-media-skills/cover-image-pipeline/github.svg)](https://agentmods.dev/skills/ur-grue/autopunk-media-skills/cover-image-pipeline)
Your own site
<a href="https://agentmods.dev/skills/ur-grue/autopunk-media-skills/cover-image-pipeline"><img src="https://agentmods.dev/badge/skills/ur-grue/autopunk-media-skills/cover-image-pipeline/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 cover-image-pipeline

Your own site · 80×15
<a href="https://agentmods.dev/skills/ur-grue/autopunk-media-skills/cover-image-pipeline"><img src="https://agentmods.dev/badge/skills/ur-grue/autopunk-media-skills/cover-image-pipeline.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 54 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,424 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. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
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 $0.00054 $0.02424
Opus 5 $0.00027 $0.01212
Sonnet 5 $0.00011 $0.00485
Haiku 4.5 $0.00005 $0.00242

Measured 8d ago against content hash 10eeb94541f7, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

cover-image-pipeline 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 8d 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/image-prompting/workflows/cover-image-pipeline/SKILL.md · 161 lines

How it starts

The opening of the file, as written. The whole thing — 161 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Cover Image Pipeline

What This Skill Does

Generates a complete, coordinated set of image prompts for a cover image concept across multiple formats and crop ratios — so a single visual idea produces consistent, properly composed assets for podcast artwork, YouTube thumbnails, newsletter headers, and social media simultaneously.

When To Use This Skill

  • You have a cover image concept and need to generate it in multiple formats (square for podcast, 16:9 for YouTube, vertical for Instagram) without it looking like a crop of the same image
  • You are launching a new episode, series, or publication issue and need a full suite of coordinated visual assets from one image session
  • You want to ensure that text placement areas, focal points, and compositional choices are optimized for each platform rather than just resized
  • You need consistent visual identity across a release campaign that touches multiple platforms simultaneously

What You Need To Provide

Required:

  • The core image concept (what the image should show — subject, scene, mood)
  • The visual style (or reference to your project's visual identity brief)
  • Which formats you need: select from podcast square (1:1), YouTube thumbnail (16:9), Instagram portrait (4:5), Instagram/Facebook landscape (1.91:1), newsletter header (3:1 approximately), or specify custom ratios

Optional:

  • Whether the image needs to accommodate text overlay (title, episode number) and where
  • The image generation tool being used (Midjourney, Flux, DALL-E) — each has different prompt grammar
  • Any existing assets to maintain consistency with (describe or reference your style brief)
  • The project's color palette if defined
  • Priority format (the one that must be strongest if trade-offs are needed)

How the Assistant Approaches This

  1. Analyzes the core image concept and identifies which visual element is the focal point — this determines how each format is composed, not just cropped
  2. Designs each format as an intentional composition, not a crop: the 16:9 version may use the wide aspect to show context the square version cannot; the square version may push the focal point to center in a way that would be static in landscape
  3. Writes a coordinated prompt set where all versions share a consistent subject, style, and palette anchor, but each prompt is written to optimize for its specific ratio and use context
  4. Notes text-safe zones for each format — where title text can be placed without covering the focal point
  5. Identifies the generation sequence: which format to generate first (usually the most compositionally complex), and how to use that result's style/seed to anchor the others
  6. Closes with a "Next Step" note: confirm the first format generation before moving on to the others, note the seed number after the first successful result, and review the full set at actual display sizes before finalizing

Read the full file on GitHub · 161 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. 8d ago First seen · 161 lines · 54 tokens per session scan A 10eeb94541f7

Subscribe to this mod's changes

cover-image-pipeline is a skill published in the GitHub repository ur-grue/autopunk-media-skills (32 stars, last pushed 12d ago), licensed MIT. It adds 54 tokens to every session and 2,424 once invoked, about $0.0003 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 2026-09-04.

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