Agent skill

Media Heavy Workflows

by swyxio in swyxio/skills

Design or revise a multi-candidate AI media-generation workspace with reference attachment, model/provider capability routing, generation history, or explicit draft-to-publish flows.

MITAuto-check passedMedia & Creative

Install Media Heavy Workflows

skills CLI
$ npx skills add swyxio/skills --skill media-heavy-workflows -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install swyxio/skills media-heavy-workflows --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/swyxio/skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/media-heavy-workflows .claude/skills/media-heavy-workflows && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
media-heavy-workflows
GitHub stars
176
Token cost
~545 tokens
SKILL.md length
219 words
Files
3 (incl. references)
Skills in repo
89
Repo updated
First seen
Licence
MIT

At a glance

Design or revise a multi-candidate AI media-generation workspace with reference attachment, model/provider capability routing, generation history, or explicit draft-to-publish flows.

  • Works in 7 steps: Inspect the existing media entrypoint,… → Distinguish saved references from… → When users compare multiple generated… → …
  • Those workflow concerns are central to the requested product
  • SKILL.md covers Behavioral core and Optional specialist guidance
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Media Heavy Workflows is an agent skill from swyxio/skills. Design or revise a multi-candidate AI media-generation workspace with reference attachment, model/provider capability routing, generation history, or explicit draft-to-publish flows. Use when those workflow concerns are central to the requested product. Do not use for individual canvas tools, ordinary image editing, one-off provider integrations, inference-runtime work, or simple image/video generation without a media workspace.

Its SKILL.md is about 550 tokens, which your agent loads only when the skill is triggered. The skill folder holds 4 other files, including reference files (for example `agents/openai.yaml` and `references/media-studio-lessons.md`).

It sits in Media & Creative, covering Image editing and AI video generation. The repository describes itself as: Agent skills for Claude Code and other AI agents. The licence is MIT.

When your agent uses it

  • Those workflow concerns are central to the requested product
  • Individual canvas tools
  • Ordinary image editing
  • One-off provider integrations

Example prompts

  • “/media-heavy-workflows”

Workflow steps

7 steps, taken from the first numbered list in SKILL.md.

  1. Inspect the existing media entrypoint, ownership, provider route, and final
  2. Distinguish saved references from references actually sent to a model. Honor
  3. When users compare multiple generated candidates, keep batches and selection
  4. Separate generation from publishing only when the product requests a draft
  5. Make external uploads and material cost visible. Keep provider credentials
  6. Show useful progress or failure state for slow operations. Preserve original
  7. Verify only the changed behavior and risks: capability/reference handling,

What it can do on your machine

Read from SKILL.md and the folder at commit 038ef34. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Media Heavy Workflows loads about 545 tokens when it runs, and up to ~2k if it reads all its reference files. Until then it costs about 114 tokens; SKILL.md has 219 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~114
When it runs · the whole SKILL.md, loaded when a task matches
~545
With references · SKILL.md plus every file in references/, read only if the agent opens them
~2k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from swyxio/skills at commit 038ef34, republished under its MIT licence (© swyxio). 219 words, ~545 tokens.

Download SKILL.mdSave it as .claude/skills/media-heavy-workflows/SKILL.md (or your agent's skills folder). This skill also uses 2 other files; get the full folder from GitHub.
name
media-heavy-workflows
description
Design or revise a multi-candidate AI media-generation workspace with reference attachment, model/provider capability routing, generation history, or explicit draft-to-publish flows. Use when those workflow concerns are central to the requested product. Do not use for individual canvas tools, ordinary image editing, one-off provider integrations, inference-runtime work, or simple image/video generation without a media workspace.

Media Heavy Workflows

Apply only the patterns required by the requested product; a media operation is not automatically a media studio.

Behavioral core

  1. Inspect the existing media entrypoint, ownership, provider route, and final insertion path. Preserve working behavior and the requested interaction.
  2. Distinguish saved references from references actually sent to a model. Honor the selected endpoint's supported tasks, input schema, and reference limits.
  3. When users compare multiple generated candidates, keep batches and selection with their owning artifact; snapshot the prompt, model, and references needed to explain each result.
  4. Separate generation from publishing only when the product requests a draft or review workflow. Direct image-edit actions may update their target immediately when undo and existing state semantics are preserved.
  5. Make external uploads and material cost visible. Keep provider credentials server-side, and require authorization before paid or irreversible actions.
  6. Show useful progress or failure state for slow operations. Preserve original dimensions and source ownership when the requested operation requires them.
  7. Verify only the changed behavior and risks: capability/reference handling, intended insertion or publish semantics, privacy, and secret protection.

Optional specialist guidance

Read references/media-studio-lessons.md only when the user actually requests cast boards, public/celebrity references, multi-provider studios, structured prompt authoring, specialized media-workspace layouts, or broader studio QA. Those patterns are recommendations, not prerequisites for unrelated work.

© swyxio, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 2 other files (references) in media-heavy-workflows of swyxio/skills.

  • SKILL.md
  • agents/openai.yaml
  • references/media-studio-lessons.md

Open the folder on GitHubat commit 038ef34

Compare with similar skills

Media Heavy Workflows next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Media Heavy Workflows compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Media Heavy Workflows this skillswyxio/skills176—~545Automated safety check: PassMIT
Agnes AI GenerationYacey/agnes-ai-generation-skill419—~1.7kAutomated safety check: PassMIT
Gc Still Image Motion DirectorLiamGvchi/gc-still-image-motion-director152—~1.4kAutomated safety check: PassMIT
Media Genclacky-ai/openclacky1.2k—~7.5kAutomated safety check: PassMIT
Mdbox Mediahi5jeff/deepclonewebsite94—~993Automated safety check: NotesCustom licence
Character Design with genmediafal-ai-community/skills251—~1.3kAutomated safety check: PassNone

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Questions about Media Heavy Workflows

What does Media Heavy Workflows do?

Design or revise a multi-candidate AI media-generation workspace with reference attachment, model/provider capability routing, generation history, or explicit draft-to-publish flows. Media Heavy Workflows is an agent skill from swyxio/skills. Design or revise a multi-candidate AI media-generation workspace with reference attachment, model/provider capability routing, generation history, or explicit draft-to-publish flows.

When should I use Media Heavy Workflows?

Media Heavy Workflows fits situations like: those workflow concerns are central to the requested product; individual canvas tools; ordinary image editing; one-off provider integrations.

How do I install Media Heavy Workflows in Claude Code?

Run `npx skills add swyxio/skills --skill media-heavy-workflows -a claude-code`. Or copy the skill folder (media-heavy-workflows in swyxio/skills) into .claude/skills/media-heavy-workflows in your project. Claude Code loads it when a task matches its description.

How do I install Media Heavy Workflows in Codex?

Run `npx skills add swyxio/skills --skill media-heavy-workflows -a codex`. Or copy the skill folder (media-heavy-workflows in swyxio/skills) into .agents/skills/media-heavy-workflows in your project. Codex loads it when a task matches its description.

Can I use Media Heavy Workflows in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add swyxio/skills --skill media-heavy-workflows -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/media-heavy-workflows, .gemini/skills/media-heavy-workflows, .github/skills/media-heavy-workflows and .opencode/skills/media-heavy-workflows in your project.

What does Media Heavy Workflows need to run?

SKILL.md names no scripts, command-line tools or credentials: Media Heavy Workflows is instructions for the agent only.

Does Media Heavy Workflows access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Media Heavy Workflows safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Media Heavy Workflows use?

Media Heavy Workflows is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Media Heavy Workflows use?

About 545 tokens (SKILL.md is roughly 2.2k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 1.4k tokens, read only when the agent opens those files.

What are the alternatives to Media Heavy Workflows?

Skills that share tags, products or a category with Media Heavy Workflows: Agnes AI Generation (Yacey/agnes-ai-generation-skill, 419 stars), Gc Still Image Motion Director (LiamGvchi/gc-still-image-motion-director, 152 stars), Media Gen (clacky-ai/openclacky, 1.2k stars) and Mdbox Media (hi5jeff/deepclonewebsite, 94 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Media Heavy Workflows?

swyxio (a GitHub user) maintains it in swyxio/skills, which has 176 GitHub stars. The repository holds 89 skills in this directory. The repository was last updated on October 5, 2026.

Source: swyxio/skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.