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luminary19luminary19/atelier/skills/codex-imagegen/SKILL.md

codex-imagegen

Skill2 starsChanged 5 months agoNo licenceView on GitHub

Generate and edit raster images by driving the locally-installed OpenAI Codex CLI headlessly and invoking its FIRST-PARTY built-in `image_gen` tool (gpt-image) — using the ChatGPT Plus/Pro login Codex is already authenticated with, NO OpenAI API key, no reverse-engineered routes. Use when asked to "generate an image", "make a logo/icon/ texture/mockup", "edit this PNG", "use codex to create an image", or "/codex-imagegen". Wraps `codex exec` and parses output via a PowerShell helper so files are reliably found.

  • Reads credentials
  • Installs packages

15 other projects use a version of this.

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Projects with it also use orchestrate and implement.

Other files people use alongside this one.

Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
  • varun29ankuSSkill

    orchestrate

    This skill should be used when the user asks to 'orchestrate a task', 'break down work into parallel agents', 'coordinate subtasks', 'run agents in parallel', or mentions 'multi-agent'. Decomposes complex tasks into tracked subtasks, dispatches parallel subagents, and coordinates until completion.

    Also in 3 projects that use this

  • Hugging FaceSkill

    implement

    Make tests pass. Invoke after /write-tests produces failing tests.

    Also in 3 projects that use this

The file

We split this skill into the rules it gives an agent

3 rules. 0 are common, 0 are distinctive, and 3 are very specific to this project.

  • 0

    Common

    Most of the 14 edited versions we read keep these.

  • 0

    Distinctive

    This author's own choices. Worth a look.

  • 3

    Very specific

    Tied to their project's names, files or tools. Probably skip.

No licence file, so all rights are reserved — read it at the source. We count its rules but don't quote them. Read them on GitHub.

“Common” is measured: kept by at least 6 in 10 of the 14 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

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Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

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