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Agent skill

Gpt Image 2 Prompting

by nodetool-ai in nodetool-ai/nodetool

Prompt OpenAI's GPT Image 2 — the five-slot Scene/Subject/Details/Use case/Constraints template it responds to, the change-versus-preserve shape for edits, labelled multi-image compositing, and how…

AGPL-3.0Auto-check passedMedia & Creative

Install Gpt Image 2 Prompting

skills CLI
$ npx skills add nodetool-ai/nodetool --skill gpt-image-2-prompting -a claude-code

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

GitHub CLI
$ gh skill install nodetool-ai/nodetool gpt-image-2-prompting --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/nodetool-ai/nodetool.git skills-src && mkdir -p .claude/skills && cp -r skills-src/packages/system-skills/gpt-image-2-prompting .claude/skills/gpt-image-2-prompting && 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
gpt-image-2-prompting
GitHub stars
560
Token cost
~1.6k tokens
SKILL.md length
637 words
Files
1
Skills in repo
127
Repo updated
First seen
Licence
AGPL-3.0

At a glance

Prompt OpenAI's GPT Image 2 — the five-slot Scene/Subject/Details/Use case/Constraints template it responds to, the change-versus-preserve shape for edits, labelled multi-image compositing, and how…

  • Works in 6 steps: Visual facts over vague praise. Drop… → Style tags need visual targets.… → Say the real thing. Transit kiosk.… → …
  • The model id contains gpt-image-2 (openai/gpt-image-2
  • SKILL.md covers The template, Rules, Three modes and What it is good at
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Gpt Image 2 Prompting is an agent skill from nodetool-ai/nodetool. Prompt OpenAI's GPT Image 2 — the five-slot Scene/Subject/Details/Use case/Constraints template it responds to, the change-versus-preserve shape for edits, labelled multi-image compositing, and how to get text on an image to render verbatim. Use whenever the model id contains gpt-image-2 (openai/gpt-image-2, openai/gpt-image-2/edit, openai/gpt-image-2/text-to-image, kie's gpt-image-2-text-to-image and gpt-image-2-image-to-image) on generateimage, editimage or a TextToImage node. Not for GPT Image 1, 1-mini or 1.5.

Its SKILL.md is about 1.6k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Media & Creative, covering Image generation. It works with OpenAI. The repository describes itself as: Agent-first Creative Workspace. The licence is AGPL-3.0.

When your agent uses it

  • The model id contains gpt-image-2 (openai/gpt-image-2
  • Openai/gpt-image-2/edit
  • Openai/gpt-image-2/text-to-image
  • Kies gpt-image-2-text-to-image and gpt-image-2-image-to-image) on generateimage

Example prompts

  • “/gpt-image-2-prompting”

Workflow steps

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

  1. Visual facts over vague praise. Drop stunning, incredible, epic,
  2. Style tags need visual targets. "Minimalist brutalist editorial luxury
  3. Say the real thing. Transit kiosk. Boarding pass. Preserve the face.
  4. Separate change from preserve in edits. "Change only X", "keep
  5. Treat text as typography. Wrap literal copy in quotes or ALL CAPS, mark
  6. One revision per turn. Small iterative edits beat one giant rewrite.

What it can do on your machine

Read from SKILL.md and the folder at commit fefb6d1. 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

    Links to these hosts (documentation or services it may open):

    • fal.ai

    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

Gpt Image 2 Prompting loads about 1.6k tokens when it runs. Until then it costs about 136 tokens; SKILL.md has 637 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~136
When it runs · the whole SKILL.md, loaded when a task matches
~1.6k

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 nodetool-ai/nodetool at commit fefb6d1, republished under its AGPL-3.0 licence (© nodetool-ai). 637 words, ~1,628 tokens.

Download SKILL.mdSave it as .claude/skills/gpt-image-2-prompting/SKILL.md (or your agent's skills folder).
name
gpt-image-2-prompting
description
Prompt OpenAI's GPT Image 2 — the five-slot Scene/Subject/Details/Use case/Constraints template it responds to, the change-versus-preserve shape for edits, labelled multi-image compositing, and how to get text on an image to render verbatim. Use whenever the model id contains gpt-image-2 (openai/gpt-image-2, openai/gpt-image-2/edit, openai/gpt-image-2/text-to-image, kie's gpt-image-2-text-to-image and gpt-image-2-image-to-image) on generate_image, edit_image or a TextToImage node. Not for GPT Image 1, 1-mini or 1.5.

GPT Image 2 → five slots, in order

The model responds to structure: scene, subject, specific details, intended artifact, constraints, in that order, with line breaks between sections once the prompt runs past a short paragraph. Everything else sits on top of that spine.

Reach it with find_model for text_to_image or image_to_image, then generate_image / edit_image.

The template

Scene:
[where this happens, time of day, background, environment]

Subject:
[who or what is the main focus]

Important details:
[materials, clothing, texture, lighting, camera angle, lens feel, composition, mood]

Use case:
[editorial photo / product mockup / poster / UI screen / infographic / concept frame]

Constraints:
[no watermark / no logos / no extra text / preserve face / preserve layout]

Five slots, five problems people usually blur together: where the image exists, what it is about, what must be visible, what kind of finished artifact you want, and what must not drift. The fifth is where mediocre prompts fail silently — describe the idea without bounding it and the model gets inventive in directions you will regret.

Filled in:

Scene:
A quiet classical museum gallery in soft afternoon light.

Subject:
A woman in her 30s standing casually in front of a large oil painting.

Important details:
Natural smile, realistic skin texture, beige knit sweater, dark jeans, white
sneakers, eye-level full-body framing, marble floor reflections, warm neutral
colour balance, shallow depth of field, believable indoor ambient light.

Use case:
Editorial lifestyle photograph.

Constraints:
No watermark, no logos, no extra people in the foreground, no heavy retouching.

Rules

  1. Visual facts over vague praise. Drop stunning, incredible, epic, masterpiece, insane detail. Use overcast daylight, brushed aluminium, chipped paint, clean kerning, 50mm feel, soft bounce light, worn canvas.
  2. Style tags need visual targets. "Minimalist brutalist editorial luxury premium" is noise. "Cream background, heavy black condensed sans serif, asymmetrical type block, one hero object, generous negative space, studio tabletop lighting" is a layout.
  3. Say the real thing. Transit kiosk. Boarding pass. Preserve the face. Mood language buries the brief.
  4. Separate change from preserve in edits. "Change only X", "keep everything else the same", and repeat the preserve list on every pass.
  5. Treat text as typography. Wrap literal copy in quotes or ALL CAPS, mark it EXACT TEXT, and specify font class, size, colour and placement. Add "no extra words" and "no duplicate text".
  6. One revision per turn. Small iterative edits beat one giant rewrite.

Three modes

Generate from scratch — the five-slot template above. One clean pass lands believable mundane realism once the prompt locks the lighting, the camera behaviour and the environment details.

Edit one image — two columns, plus a physical-realism line:

Change:
Replace the parked car with a vintage bicycle.

Preserve:
The house, fence, driveway concrete, landscaping, lighting direction, and time
of day, exactly.

Constraints:
Match the bicycle's scale and shadow pattern to the existing scene. No extra
objects, no redesign, no watermark.

The preserve list carries the edit. Inventory what must stay — awning, brick facade, mullions, reflections, sidewalk, every person on it — and the edit stays in scope.

Combine multiple images — label every input by role and reference the labels in the instruction. The family takes up to 16 reference images.

Image 1: base scene to preserve.
Image 2: jacket reference.
Image 3: boots reference.

Dress the person from Image 1 using the jacket from Image 2 and the boots from
Image 3. Preserve the face, body shape, pose, background, lighting, and framing
from Image 1. Fit the garments naturally with realistic folds, drape, occlusion
and contact shadows. No extra accessories.

Unlabelled inputs make the model guess which image is content and which is reference, and it guesses wrong.

Show full SKILL.md (268 more words)Show less

What it is good at

  • Photoreal editorial. Describe the photograph, not the fantasy: lens, framing, time of day, light source, surface wear, an ordinary background detail, one believable imperfection.
  • Product. Material accuracy, lighting consistency, label fidelity. A flat inventory of physical objects plus one piece of print that must stay legible is the entire recipe.
  • UI and screenshots. Name the screen type, the hierarchy, the exact copy, the state, and the layout logic. "Clean survival HUD along the bottom, believable UI spacing" does the layout work; remove those clauses and the HUD collapses into noise.
  • Text in image. Give the copy verbatim, then typography, then layout, then "render the text verbatim / no extra words / no duplicate text". For a still that will sit on a timeline or seed a video clip, leave the copy off and add it as a text clip afterwards (caption-titles) so it stays editable.
  • Style transfer. "Same style" is not enough. Name the parts: chunky pixel forms, limited arcade palette, bright glow accents, clean silhouette edges.
  • Drawing to photo. Say whether the drawing is a suggestion or a contract: "preserve the exact layout, horizon line, proportions, river path, mountain placement, tree placement, and overall perspective".
  • Character consistency. First prompt establishes the anchor. Second prompt repeats the anchor details verbatim and adds "do not redesign the character".

Transparency works on PNG and WebP output when the background is set transparent; JPEG silently falls back to opaque.

Check the render rather than assuming it: critique_image, or score_image_adherence when the prompt has copy or a layout to hold.

Adapted from fal's GPT Image 2 prompting guide: https://fal.ai/learn/tools/prompting-gpt-image-2

© nodetool-ai, AGPL-3.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in packages/system-skills/gpt-image-2-prompting of nodetool-ai/nodetool.

Open the folder on GitHubat commit fefb6d1

Compare with similar skills

Gpt Image 2 Prompting 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.

Gpt Image 2 Prompting compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Gpt Image 2 Prompting this skillnodetool-ai/nodetool560—~1.6kAutomated safety check: PassAGPL-3.0
AI Image Generation and Editingzhayujie/CowAgent47k—~1.3kAutomated safety check: PassMIT
GPT Image Generation CLIwuyoscar/GPT-Image2-Skill5.7k—~2.5kAutomated safety check: NotesMIT
Imagegentheowenyoung/home1154 repos~4.8kAutomated safety check: PassApache-2.0
Openai Image Gentrpc-group/trpc-agent-go1.9k12 repos~843Automated safety check: PassApache-2.0
Image Generationonyx-dot-app/onyx32k1 repos~1.7kAutomated safety check: PassCustom licence

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Works with

Categories

Questions about Gpt Image 2 Prompting

What does Gpt Image 2 Prompting do?

Prompt OpenAI's GPT Image 2 — the five-slot Scene/Subject/Details/Use case/Constraints template it responds to, the change-versus-preserve shape for edits, labelled multi-image compositing, and how…. Gpt Image 2 Prompting is an agent skill from nodetool-ai/nodetool. Prompt OpenAI's GPT Image 2 — the five-slot Scene/Subject/Details/Use case/Constraints template it responds to, the change-versus-preserve shape for edits, labelled multi-image compositing, and how to get text on an image to render verbatim.

When should I use Gpt Image 2 Prompting?

Gpt Image 2 Prompting fits situations like: the model id contains gpt-image-2 (openai/gpt-image-2; openai/gpt-image-2/edit; openai/gpt-image-2/text-to-image; kies gpt-image-2-text-to-image and gpt-image-2-image-to-image) on generateimage.

How do I install Gpt Image 2 Prompting in Claude Code?

Run `npx skills add nodetool-ai/nodetool --skill gpt-image-2-prompting -a claude-code`. Or copy the skill folder (packages/system-skills/gpt-image-2-prompting in nodetool-ai/nodetool) into .claude/skills/gpt-image-2-prompting in your project. Claude Code loads it when a task matches its description.

How do I install Gpt Image 2 Prompting in Codex?

Run `npx skills add nodetool-ai/nodetool --skill gpt-image-2-prompting -a codex`. Or copy the skill folder (packages/system-skills/gpt-image-2-prompting in nodetool-ai/nodetool) into .agents/skills/gpt-image-2-prompting in your project. Codex loads it when a task matches its description.

Can I use Gpt Image 2 Prompting 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 nodetool-ai/nodetool --skill gpt-image-2-prompting -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/gpt-image-2-prompting, .gemini/skills/gpt-image-2-prompting, .github/skills/gpt-image-2-prompting and .opencode/skills/gpt-image-2-prompting in your project.

What does Gpt Image 2 Prompting need to run?

SKILL.md names no scripts, command-line tools or credentials: Gpt Image 2 Prompting is instructions for the agent only.

Does Gpt Image 2 Prompting access the network?

SKILL.md names 1 domain. As links in the text: fal.ai. This is read from the text; nothing was executed.

Is Gpt Image 2 Prompting 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 Gpt Image 2 Prompting use?

Gpt Image 2 Prompting is published under the AGPL-3.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Gpt Image 2 Prompting use?

About 1.6k tokens (SKILL.md is roughly 6.5k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Gpt Image 2 Prompting?

Skills that share tags, products or a category with Gpt Image 2 Prompting: AI Image Generation and Editing (zhayujie/CowAgent, 47k stars), GPT Image Generation CLI (wuyoscar/GPT-Image2-Skill, 5.7k stars), Imagegen (theowenyoung/home, 115 stars) and Openai Image Gen (trpc-group/trpc-agent-go, 1.9k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Gpt Image 2 Prompting?

nodetool-ai (a GitHub organization) maintains it in nodetool-ai/nodetool, which has 560 GitHub stars. The repository holds 127 skills in this directory. The repository was last updated on October 11, 2026.

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