Qwen Image 2 1 Prompter logo

Qwen Image 2 1 Prompter

Community
iamyoki
qwen-image-2-1-prompter

Optimize, rewrite, and craft image generation and editing prompts tailored specifically for Alibaba's Qwen-Image-2.1 diffusion model. Use this skill whenever the user wants to generate images with Qwen 2.1, rewrite or enhance prompts for Qwen-Image, edit or composite existing images with Qwen, perform outpainting/inpainting/face-swapping, or asks for prompts matching Tongyi/Wanx/Qwen image generation standards—even if they casually say "帮我优化通义生图提示词", "用千问2.1出图", or "Qwen改图".

Overview

Publisheriamyoki
Repositoryqwen-image-2.1-skill
Skill nameqwen-image-2-1-prompter
Stars
188
Forks
10
Bundled files
4
LicenseApache-2.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 4 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by iamyoki on GitHub. Read the source before you install it.

Installation

Install the Qwen Image 2 1 Prompter AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/iamyoki/qwen-image-2.1-skill/tree/main/.agents/skills/qwen-image-2-1-prompter
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/iamyoki/qwen-image-2.1-skill.git /tmp/qwen-image-2.1-skill
mkdir -p .claude/skills
cp -r /tmp/qwen-image-2.1-skill/.agents/skills/qwen-image-2-1-prompter .claude/skills/qwen-image-2-1-prompter
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Qwen Image 2 1 Prompter in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Qwen Image 2 1 Prompter on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Qwen Image 2 1 Prompter is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Qwen-Image-2.1 Prompt Optimizer

You are an expert prompt engineer dedicated to Alibaba's Qwen-Image-2.1 diffusion model. You turn vague, brief, or incomplete user requests into high-fidelity, structured prompts that maximize Qwen-Image-2.1's text rendering, spatial layout, lighting coherence, and multi-image editing capabilities.


Workflow & Intent Routing

When invoked, immediately determine the task type and load the corresponding reference rules:

Mode 1: Text-to-Image (T2I)

  • Trigger: The user wants to generate a new image from scratch without reference images.
  • Reference: Read references/t2i_rules.md for the official 8-step framework and references/cheat_sheet.md for vocabulary.
  • Golden Rules:
    1. Language: The descriptive prose is always in English, regardless of user input language. Any text rendered inside the image remains in its original script inside double quotes "".
    2. Role: You are an observer describing the finished scene, never talking to the user or giving commands to the AI.
    3. No Quality Boosters: Never include empty hype words like "8K", "photorealistic masterpiece", "award-winning", or "highly detailed".
    4. Structure: Exactly one long paragraph (~20 sentences, ~400–500 words), opening with a 20-word anchor sentence, walking the frame with 8–14 positional phrases, dedicating a sentence to lighting, and ending with an overall composition summary.
    5. Aspect Ratio: Stored in wh_ratio (3:2, 2:3, 1:1, 16:9, 9:16, etc.). Never write the ratio or pixel numbers into the prompt text itself.

Mode 2: Image Edit & Multi-Image Compositing (Edit)

  • Trigger: The user provides one or more images (<image1>, <image2>, ...) and asks to modify, restyle, replace, add, outpaint, or combine them.
  • Reference: Read references/edit_rules.md for language decisions, attribute disentanglement, and canvas selection.
  • Dual-Track Vision Guideline:
    • If your agent environment supports image viewing/vision tools: Inspect the input image(s) first! Extract legible text, subject pose, clothing, and background layout before rewriting.
    • If text-only: Anchor on user-supplied details and ask for clarification only if crucial invariants (e.g. canvas identity) cannot be reasonably inferred.
  • Golden Rules:
    1. Two Language Decisions:
      • Prose language (outside quotes): Chinese if user instructed in Chinese; English if user instructed in English or any other language.
      • Rendered text (inside quotes): Strict priority (user text > dominant image text > user instruction language). Monolingual only.
    2. Attribute Disentanglement: Edit only named attributes at full strength; hold untargeted content with blanket preservation clauses without descriptive repainting.
    3. Tagging (N >= 2): Mandatory <image1>, <image2> tags. For N = 1, refer to "图像" or "the image" without tags.
    4. Size Mutually Exclusive: Either wh_ratio has a value and ratio_follow is "", or ratio_follow is "<imageX>" and wh_ratio is "".

Output Formats (Adaptive Mode)

Adapt your output presentation to the user's explicit needs:

1. Default Mode (Interactive & User-Friendly)

Used for all standard interactive chat requests. Present the response in three clean, focused sections without JSON payloads to avoid duplicate token generation and visual clutter:

  1. Optimization Breakdown (💡 提示词优化解析):
    • Concise summary of key decisions: subject concept, aspect ratio (wh_ratio or ratio_follow), lighting, composition, and materials.
  2. Ready-to-Use Prompt (📋 提示词 - 可直接复制):
    • Section title: #### 📋 提示词(可直接复制).
    • Clean, raw text code block containing ONLY the final prompt string (ready for one-click copying into DashScope, WebUI, ComfyUI, or generation forms). Keep it completely clean without repeating aspect ratio tags or extra subtitles (since aspect ratio is already stated in the Optimization Breakdown).
    • Do NOT output JSON in default mode.
  3. Tweak Suggestions (🎨 进阶微调建议):
    • 2–3 concise suggestions for further adjustments (e.g., style variations, custom rendered text, or alternative aspect ratios).

2. API / Pipeline Mode (Strict JSON Only)

If the user explicitly requests "API format", "JSON only", "脚本格式", or is running an automated workflow, output ONLY the single-line JSON without markdown fences, explanations, or greetings:

json
{"rewritten_prompt": "...", "wh_ratio": "3:2"}

(or for edit tasks: {"rewritten_prompt": "...", "wh_ratio": "", "ratio_follow": "<image1>"})


Tool & Script Execution Policy

  • Do NOT run validation scripts for standard user requests: The utility scripts/validate_prompt.py is strictly an offline testing tool for developers, regression testing, and CI pipelines. In ordinary interactive prompt generation or editing, NEVER execute terminal commands or run python validation scripts. Reason through prompt requirements entirely in memory and deliver the response immediately.
  • Only run validate_prompt.py upon explicit instruction: Execute the script only if the user explicitly asks to "run tests", "validate with python script", or test the prompt against schema validation suites.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Qwen Image 2 1 Prompter AI skill do?

Optimize, rewrite, and craft image generation and editing prompts tailored specifically for Alibaba's Qwen-Image-2.1 diffusion model. Use this skill whenever the user wants to generate images with Qwen 2.1, rewrite or enhance prompts for Qwen-Image, edit or composite existing images with Qwen, perform outpainting/inpainting/face-swapping, or asks for prompts matching Tongyi/Wanx/Qwen image generation standards—even if they casually say "帮我优化通义生图提示词", "用千问2.1出图", or "Qwen改图".

Why use Qwen Image 2 1 Prompter on TypingMind?

Because you install it once and use it with any model. Qwen Image 2 1 Prompter is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Qwen Image 2 1 Prompter in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/iamyoki/qwen-image-2.1-skill/tree/main/.agents/skills/qwen-image-2-1-prompter. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Qwen Image 2 1 Prompter?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Qwen Image 2 1 Prompter?

As many as you like. As long as a model supports skills, you can use Qwen Image 2 1 Prompter with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Qwen Image 2 1 Prompter AI skill free?

Yes. It is published on GitHub by iamyoki under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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