fast-resize

fast-resize is a skill for Claude Code from danielrosehill/Claude-Image-Production-Plugin. It costs 74 tokens per session (991 once invoked), scanned A, original, MIT.

A fast batch image-resizing tool based on libvips, with an ImageMagick fallback. It is intended for large folders, especially jobs with more than 500 images.

In plain words
What is it for?
Use it to resize directories by width, height, or bounding box, optionally processing subfolders and saving resized copies separately.
Why use it?
It addresses the slow processing and high memory use that can occur when resizing large image libraries with ImageMagick.

Skill for Claude Code

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

Part of the image-production plugin — 29 skills, 19 commands shipped together

Good fit Use it to resize directories by width, height, or bounding box, optionally processing subfolders and saving resized copies separately.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/danielrosehill/claude-image-production-plugin/fast-resize
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 danielrosehill/Claude-Image-Production-Plugin --skill fast-resize
Clone the repo
git clone --depth 1 https://github.com/danielrosehill/Claude-Image-Production-Plugin

Made for: Claude Code.

Or install image-production, the plugin that ships this one along with the rest of its 29 skills, 19 commands.

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 fast-resize

README.md
[![agentmods](https://agentmods.dev/badge/skills/danielrosehill/claude-image-production-plugin/fast-resize/github.svg)](https://agentmods.dev/skills/danielrosehill/claude-image-production-plugin/fast-resize)
Your own site
<a href="https://agentmods.dev/skills/danielrosehill/claude-image-production-plugin/fast-resize"><img src="https://agentmods.dev/badge/skills/danielrosehill/claude-image-production-plugin/fast-resize/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 fast-resize

Your own site · 80×15
<a href="https://agentmods.dev/skills/danielrosehill/claude-image-production-plugin/fast-resize"><img src="https://agentmods.dev/badge/skills/danielrosehill/claude-image-production-plugin/fast-resize.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 74 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 991 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 $0.00074 $0.00991
Opus 5.5 $0.00030 $0.00396
Sonnet 5.5 $0.00015 $0.00198
Haiku 4.5 $0.00007 $0.00099

Measured 2mo ago against content hash dbc79d2618c1, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

fast-resize 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.

skills/fast-resize/SKILL.md · 72 lines

How it starts

The opening of the file, as written. The whole thing — 72 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Fast Resize (libvips)

Batch image resize using libvips. Material throughput improvement over ImageMagick on large libraries — typical 5–10× speed-up and lower peak memory.

When to use

  • Batch is >500 images.
  • The user is feeling ImageMagick's slowness (or is about to).
  • The job is "resize this directory" — pure resize without compositing or filters.

Do not use this skill for:

  • Small batches (<100 images) — batch-resize is fine, no point swapping engines.
  • Resize-with-filter / resize-with-text / multi-op pipelines — ImageMagick is the better tool for compound work.

Inputs

  1. Input directory — required.
  2. Target size — one of:
    • --width N — resize so width = N, height auto.
    • --height N — resize so height = N, width auto.
    • --max NxM — fit within NxM box (preserves aspect).
    • --exact NxM — force exact dimensions (may distort or crop).
  3. Output mode — in-place (overwrite) or --output-dir <path> (default: <input>/resized/).
  4. Filter — interpolation kernel: lanczos3 (default — best quality), cubic, linear, nearest.
  5. Recursive — --recursive to descend into subdirectories. Default: top-level only.
  6. Format preserve — by default keeps source format. --to <ext> to change format on the way out.

Procedure

  1. Verify vips is on PATH. If missing, fall back to ImageMagick convert with the same parameters and warn that this will be slower (point at install-deps).

  2. Enumerate input files (filter to image extensions: jpg, jpeg, png, webp, tiff, gif, heic, avif, jxl).

  3. For each file, build the vips command. Two main forms:

    Fit within box (preserves aspect):

    vipsthumbnail "<input>" --size "<W>x<H>" --output "<output>[Q=85]"
    

    vipsthumbnail is the right tool for "resize down" — it's optimised for thumbnail-style ops and handles JPEG shrink-on-load (free 8× speedup for 1/8-size targets).

    Exact resize via vips:

    vips resize "<input>" "<output>" <scale-factor> --kernel <kernel>
    

Read the full file on GitHub · 72 lines

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. 2mo ago First seen · 72 lines · 74 tokens per session scan A dbc79d2618c1

Subscribe to this mod's changes

fast-resize is a skill published in the GitHub repository danielrosehill/Claude-Image-Production-Plugin (21 stars, last pushed yesterday), licensed MIT. It adds 74 tokens to every session and 991 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.

Related

fast-resize compared with skills from other repositories

fast-resize next to 6 skills from other repositories
ModTypeStarsLast pushLicenceScanTokensWorks with
fast-resizedanielrosehill/Claude-Image-Production-PluginSkill21yesterdayMITA74Claude Code
imagegenopenai/codexSkill133kyesterdayApache-2.0A113Codex
playwright-climicrosoft/playwrightSkill99kyesterdayApache-2.0A19Claude Code
local-ai-agentsmicrosoft/ai-agents-for-beginnersSkill79k4d agoMITA200Claude Code, Codex
systematic-debuggingobra/superpowersSkill313k3d agoMITA21Claude Code
next-cache-components-adoptionvercel/next.jsSkill143kyesterdayMITA95Claude Code
next-partial-prefetching-adoptionvercel/next.jsSkill143kyesterdayMITA103Claude Code