consistent visual series builder
A production control system for generating visually consistent multi-image series without style or identity drift.
$5
Works with the AI Agents you already use
Claude Code
Cursor
Codex CLI
Muse
Dots+21 moreClaude CodeCursorCodex CLIMuseDots
Manus
Grok
Grok Bot+18 agentsconsistent visual series builder
Example session with this skill installed
I need 3 images for a cyber-noir campaign. The hero is a female detective in a matte black trench coat with neon cyan trim. Scenes:
- Standing in rain, 2. In a dark office, 3. Chasing a suspect.
- Read your context and instructions
- Compiled the consistent visual series
I have normalized your brief and established the visual canon for the 'Neon Noir Detective' series.
Visual Production System
1. Canon Card: V1.0 - Neon Noir Detective
| Attribute | Specification |
|---|---|
| Subject Identity | Female detective, athletic build, matte black high-collar trench coat, neon cyan electroluminescent trim on cuffs/collar. |
| Medium/Style | Cinematic photorealism, high contrast, 35mm lens impression, fine film grain. |
| Palette | Dominant: Charcoal (#121212), Deep Shadow (#050505). Accent: Neon Cyan (#00FFFF). |
| Lighting | Low-key, high-contrast rim lighting, cool cyan highlights vs. warm ambient street spill. |
2. Scene Matrix
| ID | Scene Delta | Invariants | Risk |
|---|---|---|---|
| S1 | Exterior, heavy rain, street level | Coat trim, lighting temp | Rain-blurring facial detail |
| S2 | Interior, office, cigarette smoke | Coat material, cyan trim | Muted colors in shadows |
| S3 | Action, running, motion blur | Silhouette, trim color | Geometry distortion |
3. Coordinated Prompts
Master Prompt (Lock):
Cinematic photorealism, 35mm lens, female detective, matte black trench coat with neon cyan glowing trim, high contrast low-key lighting, cyan rim light, film grain, deep shadows, 8k resolution.
Prompt S1 (Rainy Street):
[Master Prompt Lock], standing on a rain-slicked city street at night, heavy rain droplets, reflections of neon cyan on wet asphalt, wide shot, moody atmosphere, --ar 16:9
Prompt S2 (Office):
[Master Prompt Lock], sitting in a dark noir office, swirling cigarette smoke caught in a single desk lamp beam, neon cyan trim glowing in the dark, medium close-up, --ar 16:9
Prompt S3 (Chase):
[Master Prompt Lock], running through a narrow alleyway, motion blur, detective reaching for a holster, neon cyan trim creating a light trail, dynamic action pose, --ar 16:9
Next steps
- Run the Master Prompt first to verify the coat's glow intensity.
- If S3 shows identity drift, increase the weight of the 'matte black trench coat' token.
- Compare the cyan hex values across all three outputs to ensure color profile matching.
Connects securely to your tools. The creator never sees your data.
About this skill
The problem
Generating a series of images often leads to style drift, where character identity, lighting, and textures shift inconsistently between frames. Managing these variables manually across multiple prompts is error-prone and leads to unusable assets.
What it does
- Extracts a visual canon from briefs or reference images to lock core identity and style markers.
- Categorizes every visual attribute into invariants, bounded variables, or intentional scene deltas.
- Generates a coordinated prompt system that restates critical locks to ensure cross-series coherence.
- Audits existing outputs using a weighted rubric to identify specific drift in lighting, palette, or geometry.
- Prescribes targeted prompt repairs to fix localized failures without breaking global consistency.
Why this beats prompting it yourself
Manual prompting lacks a formal control system for invariants, leading to "random" variations that ruin professional campaigns. This skill replaces guesswork with a structured scene matrix and audit protocol, ensuring every asset follows the same visual logic even as scenes change.
Use cases
- Maintaining a consistent character across a storyboard or graphic novel sequence.
- Generating a cohesive set of product lifestyle shots with identical lighting and materials.
- Creating social media ad variants that preserve brand palette and composition rules.
- Standardizing a multi-asset editorial illustration series for a single article.
Known limitations
Requires an initial approved direction or clear brief to establish the canon. It does not perform actual image generation; it provides the logic, prompts, and audits for external AI tools.
Requires an initial approved direction or clear brief to establish the canon. It does not perform actual image generation.
How to use
- 1
Connect your agent to the Agensi MCP
Copy the prompt and paste it into Claude, ChatGPT, Cursor or any agent that supports MCP. It sets up the connection for you. Manual setup
- 2
Sign in to Agensi
Your agent shows a sign-in link. Sign in and click Allow.
- 3
Ask for what you need
Your agent loads this skill and uses it on your task. It always asks before any payment.
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