agentmods.dev

media-processing

media-processing is a skill for Claude Code, Codex from siviter-xyz/dot-agent. It costs 35 tokens per session (985 once invoked), scanned A, original, MIT.

A collection of command-line workflows for processing images, audio, and video. It uses tools such as FFmpeg and ImageMagick to convert, resize, optimise, and batch-process media files.

In plain words
What is it for?
Making thumbnails, resizing image batches, converting video to audio or images, reducing video size, and preparing media for websites, apps, or archives.
Why use it?
It removes repetitive manual work when preparing media in different formats or sizes. Its repeatable scripts can also avoid overwriting the original files.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

not rated 22repo 7mo ago A scan 35 tokens original MIT

Good fit Making thumbnails, resizing image batches, converting video to audio or images, reducing video size, and preparing media for websites, apps, or archives.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/siviter-xyz/dot-agent/media-processing
View source ↗ siviter-xyz/dot-agent
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 siviter-xyz/dot-agent --skill media-processing
Clone the repo
git clone --depth 1 https://github.com/siviter-xyz/dot-agent

Made for: Claude Code, Codex.

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 media-processing

README.md
[![agentmods](https://agentmods.dev/badge/skills/siviter-xyz/dot-agent/media-processing/github.svg)](https://agentmods.dev/skills/siviter-xyz/dot-agent/media-processing)
Your own site
<a href="https://agentmods.dev/skills/siviter-xyz/dot-agent/media-processing"><img src="https://agentmods.dev/badge/skills/siviter-xyz/dot-agent/media-processing/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 media-processing

Your own site · 80×15
<a href="https://agentmods.dev/skills/siviter-xyz/dot-agent/media-processing"><img src="https://agentmods.dev/badge/skills/siviter-xyz/dot-agent/media-processing.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 35 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 985 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 $0.00035 $0.00985
Opus 5.5 $0.00014 $0.00394
Sonnet 5.5 $0.00007 $0.00197
Haiku 4.5 $0.00003 $0.00098

Measured 1mo ago against content hash c26da9f7e3ae, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

media-processing 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 1mo ago.

The scan reads SKILL.md. This mod also ships 3 executable files (scripts/batch_resize.py, scripts/media_convert.py, scripts/video_optimize.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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/media-processing/SKILL.md · 93 lines

How it starts

The opening of the file, as written. The whole thing — 93 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Media Processing

Tools and workflows for working with images, audio, and video in a repeatable, scriptable way using standard CLI tools (FFmpeg, ImageMagick) and Python helpers.

When to Use

  • Working with image batches (thumbnails, resizing, format conversion)
  • Converting media between formats (video ↔ audio ↔ image)
  • Optimizing video size while maintaining acceptable quality
  • Preparing assets for web, mobile, or archival use
  • Designing or refining CLI workflows around FFmpeg/ImageMagick

Key Principles

  • CLI-first workflows: Prefer command-line tools (FFmpeg, ImageMagick) and scripts that can be automated in CI or local tooling.
  • Deterministic scripts: Scripts should be safe to run repeatedly with predictable output paths and options.
  • Non-destructive defaults: Default to writing outputs to new files/directories rather than overwriting originals.
  • Cross-platform friendly: Keep examples and scripts usable on Linux, macOS, and Windows where possible.
  • Agent-agnostic: Guidance should work with any coding agent (Cursor, Claude, Copilot, etc.), not one specific environment.

Capabilities

  • Image workflows

    • Batch resize and thumbnail generation
    • Aspect-ratio–aware resizing (fit, fill, cover, exact)
    • Optional watermarking
    • Format conversion (e.g., PNG → WebP, JPEG)

  • Media conversion

    • Detects media type (video, audio, image) from extension
    • Uses FFmpeg for video/audio, ImageMagick for images
    • Quality presets for web, archive, and mobile use cases
    • Batch conversion with dry-run and verbose modes

  • Video optimization

    • Resolution and frame-rate adjustments
    • Single-pass (CRF) or two-pass encoding
    • Audio bitrate tuning
    • Basic before/after comparison (size, bitrate, resolution, FPS)

Scripts

Scripts live in scripts/ and are intended to be run directly from a shell:

  • batch_resize.py
    • Batch image resizing with multiple strategies (fit, fill, cover, exact, thumbnail)
    • Optional watermark overlay
    • Supports parallel processing and dry-run mode

Read the full file on GitHub · 93 lines

Files

What ships with it

10 files 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. 1mo ago First seen · 93 lines · 35 tokens per session scan A c26da9f7e3ae

Subscribe to this mod's changes

media-processing is a skill published in the GitHub repository siviter-xyz/dot-agent (22 stars, last pushed 7mo ago), licensed MIT. It adds 35 tokens to every session and 985 once invoked, about $0.0001 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.

Creative and media
Related

Other skills, from other repositories

local-ai-agents

Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…

microsoft/ai-agents-for-beginners · 200 tokens

systematic-debugging

Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.

obra/superpowers · 21 tokens

next-cache-components-adoption

Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…

vercel/next.js · 95 tokens

chat-pet-sprite-creation

Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.

microsoft/vscode · 53 tokens

cpu-profile-analysis

Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…

microsoft/vscode · 71 tokens

insight-error-page

Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…

vercel/next.js · 83 tokens