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Grok+17 agentsImage Prompt Consistency Guard
Audits AI image prompt sets for drift in style, identity, lighting, and composition.
Free
Image Prompt Consistency Guard
Example session with this skill installed
Audit these two prompts for a high-end watch brand. Model: Midjourney.
- Close up of a silver watch on a marble table, soft morning light.
- Man wearing a gold watch in a dark office, moody lighting.
- Read your context and instructions
- Compiled the image prompt consistency
- Generated the image
I have audited the prompt set for the high-end watch series. The set requires restructuring due to a fundamental mismatch in product material (silver vs. gold) and environmental lighting, which will break visual continuity.
Consistency Audit & Corrected Prompts
Consistency Verdict
The set needs restructuring. The primary issue is the change in the product's base material and the total lack of shared lighting logic. Without alignment, these will appear to be from two different brands or collections rather than a unified campaign.
Scorecard
| Metric | Score | Evidence-based Reasoning |
|---|---|---|
| Identity/Geometry | 40 | Material switches from silver to gold; product consistency is lost. |
| Style & Medium | 80 | Both imply a high-end photography medium. |
| Composition | 60 | One is a product close-up, the other is a lifestyle shot; acceptable but needs alignment. |
| Lighting | 30 | "Soft morning light" vs "moody office" creates an irreconcilable contrast. |
| Palette | 40 | Marble/Silver vs Dark/Gold creates two different color stories. |
| Prompt Clarity | 70 | Instructions are simple but lack specific technical camera or material descriptors. |
Drift Table
| Prompt | Issue | Severity | Why it Matters | Repair |
|---|---|---|---|---|
| 1 | Ambiguous material | Critical | "Silver" vs "Gold" in P2 breaks the product line. | Standardize to Polished Silver. |
| 2 | Lighting conflict | Major | Moody office light clashes with morning marble setup. | Shift to "low-key morning light" for continuity. |
| 2 | Subject drift | Critical | Gold material contradicts the primary product SKU. | Update to Polished Silver. |
Locked Visual DNA
[Subject: Polished Silver Luxury Watch, sapphire crystal, brushed steel lugs]
[Medium: Commercial product photography, 85mm lens, f/4.0]
[Lighting: Soft directional light, high micro-contrast, clean shadows]
[Palette: Cool neutrals, silver, slate, white marble accents]
Corrected Prompt Set
Prompt 1: Close up of a polished silver luxury watch on a white marble table, soft directional morning light, 85mm lens, f/4.0, high micro-contrast --ar 4:5
2.
Prompt 2: Medium shot of a man in a charcoal suit wearing a polished silver luxury watch, standing in a dim office with soft directional morning light hitting the wrist, 85mm lens, f/4.0, high micro-contrast --ar 4:5
Next steps
- Run both prompts using the same
--seedvalue to verify the silver material rendering. - Check if the "morning light" in the office setting requires more specific window-light keywords.
- Confirm if the watch face design needs a specific "complication" description to maintain geometry.
image-prompt-consistency-guard.png
PNG · 1536×1024
Example file from a real run - the skill writes it into your workspace.
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About this skill
The problem
Generating a series of AI images often results in visual drift where subjects, lighting, and product geometry change unexpectedly between prompts. Manually aligning these variables across a large set is error-prone and leads to inconsistent brand assets or storyboards.
What it does
- Identifies intended constants and variables across a set of image prompts.
- Extracts a visual DNA covering subject identity, lighting, palette, and medium.
- Audits prompts for critical mismatches in product geometry and rendering style.
- Repairs prompt syntax to maintain consistency while preserving intentional scene variations.
- Generates a verification plan to isolate variables during test generations.
Why this beats prompting it yourself
Instead of guessing why image three looks different than image one, this skill systematically decomposes the visual attributes. It treats your prompt set as a coherent system, ensuring that shared elements like material treatment and camera family remain locked across the entire series.
Use cases
- Maintaining product geometry across a series of e-commerce lifestyle shots.
- Ensuring character identity remains stable across storyboard frames.
- Aligning lighting and palette for a multi-channel social media ad campaign.
- Developing consistent prompt packs for stock photography or design systems.
Known limitations
Cannot guarantee identical outputs due to the probabilistic nature of image models. Requires at least two related prompts to perform a meaningful consistency audit.
How to install
Works the same in every agent - Claude, Cursor, Codex, Copilot and 20+ more.
- 1
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- 2
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- 3
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