image-assistant

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🇺🇸

Original

English
🇨🇳

Translation

Chinese

配图助手

Image Assistant

触发方式

Trigger Methods

当用户说类似以下内容时触发:
  • “这段内容做个图 / 配几张图?”
  • “给我两张(或多张)出图提示词”
  • “字太多不好看,帮我更趣味、更好读”
  • “把这个流程封装成提示词模板/skills”
  • “/image “/配图” “/出图”

Trigger when the user says something like:
  • "Make a graphic for this content / create several supporting images?"
  • "Give me two (or multiple) image generation prompts"
  • "Too much text, make it more interesting and readable"
  • "Package this process into a prompt template/skills"
  • "/image " "/配图" "/出图"

流程概览

Process Overview

阶段名称目标详细文件
1需求澄清(Spec/DoD)先挖需求:内容/场景/受众/字多字少;尺寸与风格默认;产出一句话复述与需求小结
stages/01-brief.md
2配图规划(拆块→清单)拆内容→定图清单(几张/每张讲啥/用啥模板)
stages/02-plan.md
3文案定稿(Copy Spec)逐字定稿“图上写什么”(唯一真值)
stages/03-copy.md
4提示词封装(Prompt Pack)把 Copy Spec 封装成可复制提示词;生成批量请求包并在用户确认后批量出图
stages/04-prompts.md
5迭代润色根据反馈减字、换隐喻、提可读性
stages/05-iterate.md

StageNameGoalDetailed File
1Requirements Clarification (Spec/DoD)First explore requirements: content/scenario/audience/text density; default size and style; produce a one-sentence restatement and requirement summary
stages/01-brief.md
2Image Planning (Chunking → List)Chunk content → define image list (quantity / what each image covers / recommended template)
stages/02-plan.md
3Copy Finalization (Copy Spec)Finalize "what text to put on the image" word by word (single source of truth)
stages/03-copy.md
4Prompt Packaging (Prompt Pack)Package Copy Spec into copyable prompts; generate batch request packages and batch generate images after user confirmation
stages/04-prompts.md
5Iterative PolishingReduce text, replace metaphors, and improve readability based on feedback
stages/05-iterate.md

调度规则

Scheduling Rules

如何判断当前阶段:
  1. 还没把需求讲清楚(内容 + 场景 + 受众 + 字多/字少)→ 阶段1
  2. 文章很长、需要拆块,或需要确定“几张图/每张讲什么”→ 阶段2
  3. 已确认图清单,但还没确定“图上逐字写什么”→ 阶段3
  4. Copy Spec 已确认,要出可复制提示词;(可选)提示词确认后批量出图 → 阶段4
  5. 用户反馈“字多/不好看/不符合封面” → 阶段5(必要时回退到阶段1重锁需求与字多/字少)
每个阶段开始时:
  • 告诉用户当前阶段与本阶段输出物
  • 读取对应阶段文件并按步骤执行

How to determine the current stage:
  1. Requirements not clearly defined (content + scenario + audience + text density) → Stage 1
  2. Long article that needs chunking, or need to confirm "how many images / what each image covers" → Stage 2
  3. Image list confirmed, but "exact text for each image" not finalized → Stage 3
  4. Copy Spec confirmed, need to generate copyable prompts; (optional) batch generate images after prompt confirmation → Stage 4
  5. User feedbacks "too much text / not good-looking / doesn't fit the cover" → Stage 5 (roll back to Stage 1 to re-lock requirements and text density if necessary)
At the start of each stage:
  • Inform the user of the current stage and deliverables for this stage
  • Read the corresponding stage file and execute according to steps

输出规范(必须遵守)

Output Specifications (Must Follow)

  • 每张图一个“核心信息”,不把解释性段落塞进图里
  • 所有中文必须清晰可读:大字号、少字短句、避免密集小字
  • 每张提示词用一个独立代码块输出,便于复制
  • 默认输出 16:9 横版(除非用户明确要 3:4 漫画/竖版)
  • 默认风格:奶油纸底 + 彩铅水彩手绘 + 轻涂鸦,趣味但干净(可用
    templates/style-block.md
  • 阶段3产物(Copy Spec)一旦确认,阶段4不得擅自改文案,只做封装与参数/约束补全

  • Each image has one "core message", do not include explanatory paragraphs in the image
  • All Chinese text must be clearly readable: large font size, short sentences with minimal text, avoid dense small text
  • Each prompt is output in an independent code block for easy copying
  • Default output is 16:9 landscape (unless the user explicitly requests 3:4 comic/portrait)
  • Default style: cream paper background + colored pencil watercolor hand-drawn + light doodles, fun but clean (can use
    templates/style-block.md
    )
  • Once the Stage 3 deliverable (Copy Spec) is confirmed, the copy cannot be modified without permission in Stage 4; only packaging and parameter/constraint completion are allowed

快速使用(给用户的最小输入)

Quick Start (Minimum Input for Users)

用户只要给这四项,就能开始:
  1. 要配图的内容(可是一段、一个小节、或整篇文章)
  2. 用在哪里 + 观看距离(PPT投影远看 / 手机近看 / 海报)
  3. 谁来看(小白/从业者/老板/学生…)
  4. 偏好:更“少字清爽”还是更“信息密度”
可选补充(不写也没关系):
  • 你大概想要哪类图:封面/目录、单页概览、讲义解释、社媒海报(不确定我会根据场景与偏好推荐)
你要做的交付顺序:
  • 先输出:图清单(几张 + 每张一句话目的 + 模板建议)(阶段2)
  • 用户确认后:逐张输出 Copy Spec(逐字定稿)(阶段3)
  • Copy Spec 确认后:逐张输出可复制提示词/调用包(阶段4)
  • (可选)提示词确认后:批量调用 API 出图(阶段4内连续流程)
  • 用户说“字多/不好看”就进入迭代(阶段5)

Users only need to provide these four items to start:
  1. Content to be illustrated (can be a paragraph, a section, or an entire article)
  2. Usage scenario + viewing distance (PPT projection for long-distance viewing / mobile phone for close viewing / poster)
  3. Target audience (beginners/practitioners/managers/students...)
  4. Preference: "more minimal and clean" or "higher information density"
Optional supplements (not required):
  • What type of images you roughly want: cover/table of contents, single-page overview, lecture explanation, social media poster (I will recommend based on scenario and preference if unsure)
Your delivery order:
  • First output: Image list (quantity + one-sentence purpose for each + template recommendation) (Stage 2)
  • After user confirmation: Output Copy Spec for each image (finalize text word by word) (Stage 3)
  • After Copy Spec confirmation: Output copyable prompts/call packages for each image (Stage 4)
  • (Optional) After prompt confirmation: Batch call API to generate images (continuous process within Stage 4)
  • Enter iteration when the user says "too much text / not good-looking" (Stage 5)

文件结构

File Structure

stages/
├── 01-brief.md
├── 02-plan.md
├── 03-copy.md
├── 04-prompts.md
└── 05-iterate.md

templates/
├── style-block.md
├── 16x9-infographic.md
├── 16x9-contrast-2cards.md
├── 16x9-3cards-insights.md
├── 16x9-cover-roadmap.md
├── 16x9-5panel-comic.md
├── api-config.md
├── apimart-curl.md
├── apimart-requests-jsonl.md
└── checklist.md

examples/
└── ai-tools-selection.md

scripts/
├── apimart_batch_generate.py
├── apimart.env.example
└── README.md
stages/
├── 01-brief.md
├── 02-plan.md
├── 03-copy.md
├── 04-prompts.md
└── 05-iterate.md

templates/
├── style-block.md
├── 16x9-infographic.md
├── 16x9-contrast-2cards.md
├── 16x9-3cards-insights.md
├── 16x9-cover-roadmap.md
├── 16x9-5panel-comic.md
├── api-config.md
├── apimart-curl.md
├── apimart-requests-jsonl.md
└── checklist.md

examples/
└── ai-tools-selection.md

scripts/
├── apimart_batch_generate.py
├── apimart.env.example
└── README.md