Preface

When creating content illustrations, the most common loop is: open the image generation tool, write a prompt, generate, be dissatisfied, change a few words, and try again. The problem usually isn’t the tool, but the prompt itself—either it crams in elements that AI cannot render (text within images, mathematical symbols, hand details), or it only uses vague terms like “tech-style poster,” leaving the model to guess. The problem with image sets and videos is more hidden: individual images might look okay, but when connected, the character’s appearance, color palette, and composition all change.

The Skill introduced below targets this specific link: the user provides a topic, and it produces a prompt that can be directly pasted into image generation tools, while pre-constraining four things: “what AI can render,” “whether the image looks good,” “how to maintain consistency across multiple images,” and “how to provide platform-specific dimensions.”

What is this

Image Prompt Master (Coordinate @user_fa14b5bc/image-prompt-master) is a prompt generation Skill for AI image/video generation, published by community developer user_fa14b5bc on SkillHub. It is categorized under design-media, with the current version being 1.0.4 and the source marked as community.

It solves the problem of “writing prompts,” not “generating images”: it covers the usage differences of mainstream image/video generation tools like Doubao, Jimeng, Kling, Midjourney, Stable Diffusion, and Tongyi Wanxiang. It outputs a structured prompt that users can copy and use directly in their target tools.

Core Functions

Its approach is not about adding words, but adding constraints. According to the page description, the output is converged using three rulers:

  1. AI Capability Boundaries. Avoid high-risk elements such as excessive text within images, mathematical/rare symbols (÷ × ± √ ∑, etc.), hand deformities, Logos, and QR codes. In most models, these elements either render as garbled text or cause the entire image to fail; they must be excluded first.

  2. Balance between Detail and Consistency. For single images, details can be expanded to increase information density and texture; for image sets and videos, consistency anchors (character appearance, color palette, composition skeleton, style keywords) are locked, allowing only changes in action or shot content. This directly addresses the pain point of “every generation looks different.”

  3. Channel Specification Adaptation. Layout parameters are provided according to the deployment platform: WeChat Official Account horizontal version, Douyin/Xiaohongshu vertical version, and Bilibili horizontal version with reserved title space. The prompt includes the layout, saving the rework of cropping or incorrect whitespace after generation.

In addition, it adjusts the art style based on the industry, covering scenarios such as finance, HR, education, and government affairs.

The final output is fixed into four parts: Main Prompt, Negative Prompt, Layout Parameters, and Consistency Anchors. The negative prompt is used to explicitly exclude items, and consistency anchors are key for reuse in image sets and videos.

Installation and Activation

This Skill belongs to the universal SKILL.md format and can be placed directly into the Agent’s Skills directory for the host to load.

The unique identifier provided on the page is the coordinate:

@user_fa14b5bc/image-prompt-master

The remaining information is as follows, sourced from the SkillHub skill page:

Source:     community
Category:   design-media
Version:    1.0.4
Publisher:  user_fa14b5bc
Tags:       requires_api_key=false

It needs to be noted that: the skill page does not disclose specific installation commands, Skills directory paths, or configuration file fields, nor does it provide platform-specific instructions for Cursor, Codex CLI, or Claude Code. Therefore, no commands are given here to avoid writing unverified steps. requires_api_key=false indicates that the Skill itself does not require an additional API Key configuration; the key for actually calling the image generation model is still handled by the target tool.

Typical Usage

Below is its input/output format (input is the topic, output is a four-section structured prompt). The official page does not provide a fully reproducible example input/output, so only the interaction method is described here:

Input: Create a header image for a WeChat Official Account article about "Compound Interest"

Output:
1. Main Prompt (including image type, style, subject, lighting, composition, color description)
2. Negative Prompt (excluding text, symbols, deformed limbs, Logos, QR codes, etc.)
3. Layout Parameters (platform, ratio, whether to reserve title space)
4. Consistency Anchors (locked items like character/color palette/composition skeleton for reuse in sets)

After generation, simply paste the main prompt into the corresponding tool; when creating a series of illustrations, keep the 4th anchor item unchanged and only replace the action or scene description.

Applicable Scenarios and Notes

It is suitable for these needs: headers, covers, in-article illustrations, posters, infographics, storyboard scripts for WeChat Official Accounts, Douyin, Xiaohongshu, Video Accounts, and Bilibili content, as well as prompts for video generation. It is also suitable for scenarios where users explicitly complain about “imprecise prompt writing,” “poor generation consistency,” “no composition or aesthetics,” “too few elements/too empty,” or “messy colors.”

Points to note:

  1. It produces prompts, not images themselves. The final image quality still depends on the tool and model you use; the Prompt can only constrain, not guarantee.
  2. The constraints are a general template; the adaptation of industry art styles and platform layouts needs to be clearly stated in the input. If you only say “give me an image,” you are likely to get a generic style.
  3. Low-version image generation models vary greatly in their ability to handle hands, text, and symbols. It is recommended to keep the exclusion items in the negative prompt as needed, and do not delete them just because they worked well once.
  4. The page data shows a rating of 100000, 1242 downloads, and 0 installations. An installation count of 0 means there are no large-scale verified feedback samples in the community yet. It is recommended to try it on a small scale first for complex scenarios before deciding whether to use it in your official content stream.

Conclusion

The value of this Skill lies in front-loading the most common pitfalls in image generation prompts (unrenderable elements, inconsistency in image sets, platform layout errors) as constraints, producing direct-use results. If your daily routine involves batch creating illustrations for articles and videos, it is worth putting into your workflow for a trial run.

Official Address: https://api.skillhub.cn/user_fa14b5bc/image-prompt-master