Generate new images or edit existing ones using OpenAI's GPT Image 1.5 model.
Works with
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versiongpt-image-1-5Execute the skills CLI command in your project's root directory to begin installation:
Fetches gpt-image-1-5 from intellectronica/agent-skills and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate gpt-image-1-5. Access via /gpt-image-1-5 in your agent's command palette.
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
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Automate repetitive workflows and reduce manual effort
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Generate reports, summarize documents, draft communications
Save 3-5 hours per week on routine tasks
Learn new skills, understand complex topics, get expert guidance
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Explain concepts, provide examples, suggest learning resources
Accelerate learning and skill development by 2x
Enhance output quality through reviews, suggestions, and refinements
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Review drafts, suggest improvements, catch errors
Improve work quality by 30-40% with less effort
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Generate new images or edit existing ones using OpenAI's GPT Image 1.5 model.
Run the script using absolute path (do NOT cd to skill directory first):
Generate new image:
uv run ~/.claude/skills/gpt-image-1-5/scripts/generate_image.py --prompt "your image description" --filename "output-name.png" [--quality low|medium|high] [--size 1024x1024|1024x1536|1536x1024|auto] [--background transparent|opaque|auto] [--api-key KEY]
Edit existing image (without mask - full image edit):
uv run ~/.claude/skills/gpt-image-1-5/scripts/generate_image.py --prompt "editing instructions" --filename "output-name.png" --input-image "path/to/input.png" [--size 1024x1024|1024x1536|1536x1024|auto] [--api-key KEY]
Edit existing image (with mask - precise inpainting):
uv run ~/.claude/skills/gpt-image-1-5/scripts/generate_image.py --prompt "what to put in masked area" --filename "output-name.png" --input-image "path/to/input.png" --mask "path/to/mask.png" [--size 1024x1024|1024x1536|1536x1024|auto] [--api-key KEY]
Important: Always run from the user's current working directory so images are saved where the user is working, not in the skill directory.
Map user requests:
mediumlowhighMap user requests:
1024x10241024x10241024x15361536x1024The script checks for API key in this order:
--api-key argument (use if user provided key in chat)OPENAI_API_KEY environment variableIf neither is available, the script exits with an error message.
Generate filenames with the pattern: yyyy-mm-dd-hh-mm-ss-name.png
Format: {timestamp}-{descriptive-name}.png
yyyy-mm-dd-hh-mm-ss (24-hour format)x9k2, a7b3)Examples:
2025-12-17-14-23-05-japanese-garden.png2025-12-17-15-30-12-sunset-mountains.png2025-12-17-16-45-33-robot.png2025-12-17-17-12-48-x9k2.pngBoth editing modes use the Image API (images.edit endpoint) with gpt-image-1.5 for reliable results.
When the user wants to modify an existing image without specifying exact regions:
--input-image parameter with the path to the imageWhen the user wants to edit specific regions:
--input-image parameter with the path to the image--mask parameter with a PNG mask fileCommon editing tasks: add/remove elements, change style, adjust colors, replace backgrounds, etc.
For generation: Pass user's image description as-is to --prompt. Only rework if clearly insufficient.
For editing: Pass editing instructions in --prompt (e.g., "add a rainbow in the sky", "make it look like a watercolor painting")
Preserve user's creative intent in both cases.
Generate new image:
uv run ~/.claude/skills/gpt-image-1-5/scripts/generate_image.py --prompt "A serene Japanese garden with cherry blossoms" --filename "2025-12-17-14-23-05-japanese-garden.png" --quality high --size 1536x1024
Generate with transparent background:
uv run ~/.claude/skills/gpt-image-1-5/scripts/generate_image.py --prompt "A cute cartoon cat mascot" --filename "2025-12-17-14-25-30-cat-mascot.png" --background transparent --quality high
Edit existing image (full image):
uv run ~/.claude/skills/gpt-image-1-5/scripts/generate_image.py --prompt "make the sky more dramatic with storm clouds" --filename "2025-12-17-14-27-00-dramatic-sky.png" --input-image "original-photo.jpg"
Edit with mask (inpainting):
uv run ~/.claude/skills/gpt-image-1-5/scripts/generate_image.py --prompt "a flamingo swimming" --filename "2025-12-17-14-30-00-lounge-flamingo.png" --input-image "lounge.png" --mask "mask.png"
Prerequisites
Time Estimate
15-45 minutes depending on use case complexity
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.
✗ Avoid when
Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.
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gpt-image-1-5 is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
I recommend gpt-image-1-5 for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
gpt-image-1-5 fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
Keeps context tight: gpt-image-1-5 is the kind of skill you can hand to a new teammate without a long onboarding doc.
We added gpt-image-1-5 from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
Solid pick for teams standardizing on skills: gpt-image-1-5 is focused, and the summary matches what you get after install.
Registry listing for gpt-image-1-5 matched our evaluation — installs cleanly and behaves as described in the markdown.
gpt-image-1-5 has been reliable in day-to-day use. Documentation quality is above average for community skills.
Solid pick for teams standardizing on skills: gpt-image-1-5 is focused, and the summary matches what you get after install.
I recommend gpt-image-1-5 for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
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