| What you want GPT Image 2.5 to do | Constraints to make explicit | Observed failure — and what it does not prove | How to accept the result | How to interpret it |
|---|---|---|---|---|
| Edit a subject while keeping the surrounding image | Name the intended change and the faces, objects, framing and other details that must remain. | An omitted object disappeared during a portrait edit even though the faces survived. This does not prove that listing it would guarantee preservation. | Check the requested edit and every protected element against the input. | A preserved face is only part of the check. If something was omitted, add that requirement; if it was already specified, record an unmet constraint. |
| Create a poster after clarifying its content | Distinguish questions used to prepare the brief from words intended to appear in the image. | Clarifying questions and answer lines appeared on the poster itself. No verified wording fix is established for that failure. | Read all visible text and confirm that it belongs in the finished design. | Correct spelling cannot rescue the wrong content. Separating preparation from visible copy is a suggested test, not a demonstrated cure. |
| Generate a simple scene without changing its premise | State the setting, required objects and visual treatment that define the scene. | A simple park-and-kiosk request repeatedly became a restaurant scene with lamps, wine and rain. The record does not establish that the original instruction lacked detail. | Compare the setting and objects with the brief before judging polish. | If the requirement was already explicit, the result failed it. Do not automatically diagnose a short prompt as the cause. |
| Remove repetitive texture while retaining natural detail | Identify the unwanted repeating pattern and the detail that should survive cleanup. | Direct cleanup instructions worked intermittently. Similar texture defects also appeared in fresh images. | Compare the affected surfaces and the details that should remain. | An intermittent repair is not a reliable recipe. More prompting or a new conversation is not an established cure. |
| Make an image larger | State the required output dimensions and distinguish enlargement from sharpening. | A request for a larger image produced sharper detail while the dimensions stayed unchanged. | Inspect the returned file’s dimensions. | Visual sharpness does not establish enlargement. More descriptive wording cannot substitute for checking the file. |
| Process an existing image without generating another | State that the operation is image processing and that a new generation is not requested. | A processing follow-up triggered another generation, prompting “DO NOT CREATE AN IMAGE”. The instruction is not evidence of a successful repair. | Confirm which operation occurred and inspect its output. | If another generation occurs, the task remains unmet; a more attractive image does not change that result. |
| Rebuild a damaged image through line art | Define what must survive the rebuild, especially whether a specific person’s identity matters. | A line-art intermediate was used to rebuild a photorealistic image where preserving a particular identity was unnecessary. | Check the rebuilt image against the actual preservation requirement. | There is no basis here for recommending this route when exact personal identity must survive. |
How to use this GPT Image 2.5 prompt table
The constraints and acceptance checks are editorial recommendations inferred from the recorded failures. They are not newly tested prompts. Where the original wording or a successful correction is unknown, the table says so rather than inventing a cause.
Decide what to rewrite
- Locate the failed requirement. Was the wrong object changed, the wrong text drawn, the setting replaced, the texture damaged or the requested operation left unfinished? Name the failure before adding instructions.
- Check whether the requirement was actually stated. If it was omitted, add that specific constraint and test again. If it was already explicit, classify the result as “requirement stated, not met.” Do not relabel it as missing detail merely because the image failed.
- Choose the right acceptance check. Content and preservation require comparison with the brief or input. Enlargement requires file dimensions. A processing request requires confirmation that processing, rather than another generation, occurred.
- Approve, revise or stop. Approve only when the requested change and preservation requirements pass. Revise a missing or ambiguous instruction when you can identify one. If the requirement is already clear and another attempt only trades defects, stop treating prompt expansion as a proven solution.
When the wording is not enough to decide
A requirement can be absent, ambiguous or explicit but unmet. Those are different situations. The available records do not justify turning every unwanted change into evidence that the prompt was too short.
Preparation instructions can also become image content. If questions appear on a poster, checking the spelling answers the wrong question. First establish whether those words should have appeared at all.
Some tasks cannot be accepted from appearance alone. A sharper preview does not prove larger dimensions, and a newly generated image does not prove that a processing request was completed.
Reconstruction has its own boundary. A line-art rebuild that is acceptable without a specific identity requirement does not establish a safe route for an identity-sensitive portrait.
Claims the evidence does not support
There is no established universal phrase that prevents all collateral edits, no dependable prompt-only cure for repetitive texture, and no basis for saying that a longer prompt always fixes a failed brief. An explicit instruction records what was requested; the output still determines whether it happened.
This page therefore gives no ideal prompt length, guaranteed retry count or success percentage. The records do not supply a controlled comparison that could justify those numbers. The useful stopping point is concrete: identify the unmet requirement, test a specific correction when one is supported, and leave unresolved failures marked unresolved.