Ai Artist
CheckedGenerates unique images from text prompts in various artistic styles using advanced AI models.
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Showing Claude Code. One command installs this skill into any of the agents below.
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terminal$ npx skills add binhmuc/autobot-review --skill ai-artist -a claude-code Uses the open-source
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What we know about this skill
Publisher
binhmuc
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Install target
Live repository
Not pinned. Installing fetches whatever the repository holds at the time you run the command.
Automated safety checks
This skill passed all 6 checks. We read its files at one commit and looked for the things that make a skill dangerous to run — not for whether it works.
Declares what it does: passed
SKILL.md parses and declares a name and a description.
SKILL.md exists, its frontmatter parses, and it declares a name and a description.
No undeclared network calls: passed
Makes no network calls.
Every host the skill dials — from its scripts, its config endpoints or the commands it tells the agent to run — is either well-known package and API infrastructure or declared in its own frontmatter. Links in documentation are not counted.
No obfuscated payloads: passed
No encoded or obfuscated payloads.
No base64, hex or compressed blob is decoded and then executed, and no encoded shell commands.
No credential access: passed
Reads no keys, tokens, keychains or credential files.
Neither the code nor the SKILL.md instructions read SSH keys, cloud credentials, keychains, token stores, browser cookie databases or dotfiles that hold secrets.
No pipe-to-shell installers: passed
No pipe-to-shell or download-and-run installers.
No `curl … | sh` pattern, in the code or in the instructions, that runs code fetched at run time.
Pinned to a commit: passed
Scanned binhmuc/autobot-review at a2b4913a35.
The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.
- Commit
- a2b4913a35
- Scanned
- 11 files, 1,015 lines
About this skill
What it does
This skill, Ai Artist, helps you craft effective prompts for AI text and image generation models like Midjourney, DALL-E, Stable Diffusion, Flux, Imagen/Veo, and others. It focuses on prompt engineering principles to generate higher quality outputs by emphasizing clarity, context, structure, and iterative refinement. The skill provides structured patterns and reference materials to guide users in creating prompts for both Large Language Models (LLMs) and image generation models.
When to use it
- Generating images: You want to create unique images using AI tools but are struggling with the results.
- Improving LLM responses: You need help structuring your requests to LLMs for more targeted and useful outputs.
- Learning prompt engineering techniques: You're new to AI generation and want a guide to best practices.
- Optimizing existing prompts: You have some experience but want to refine your prompts for better results across different models.
Key capabilities
- Structured Prompt Patterns: Provides templates for both LLM and image generation prompts, including sections for Role, Context, Task, Format (for LLMs) and Subject, Style, Composition, Quality, Negative Prompts (for images).
- Model-Specific Syntax Guides: Includes key syntax information for models like Midjourney, DALL-E 3, Stable Diffusion, Flux, and Imagen/Veo.
- Reference Materials: Offers links to detailed guides on LLM prompting, image prompting, Gemini prompting, advanced techniques (meta-prompting, A/B testing), domain patterns, and more.
- Anti-Pattern Identification: Highlights common pitfalls in prompt engineering like vague instructions or conflicting constraints.
Example prompts
- "LLM Prompt: [Role] You are a marketing expert specializing in social media. [Context] We're launching a new line of organic dog treats. [Task] Write three catchy Instagram captions. [Format] List."
- "Image Generation (Midjourney): Portrait of a cyberpunk hacker, neon lighting, cinematic composition, detailed face, 8k, artstation quality --ar 16:9 --style raw"
- "Image Generation (DALL-E 3): A fluffy golden retriever puppy playing in a field of wildflowers."
Tips & gotchas
- Be specific: Avoid vague instructions like "make it better". Clarity is key.
- Consider model limitations: Each AI model has strengths and weaknesses; tailor your prompts accordingly (e.g., DALL-E 3 uses natural language with no parameters).
- Iterate and test: Experiment with different prompt variations to see what produces the best results.