AI Draw 绘画提示词自动化工作台 · 用户指南AI Draw Prompt Automation Workbench · User Guide

把 ai-draw-cue-word-project v2.8 的提示词工程资产（角色锚点 · 五大家族语法 · 负面词库 · 渲染前检查 · 视频生成 · 3D 生成 · LoRA 管理 · 多角色空间 · 对话编辑链 · 分镜骨架 · 漫剧模式）变成可交互工具：填一次角色设定，按模型家族自动拼装提示词，渲染前逐项过关。Turn the ai-draw-cue-word-project v2.8 prompt engineering assets (character anchors · five syntax families · negative word bank · pre-render checklist · video generation · 3D generation · LoRA management · multi-character spatial relations · conversational edit chain · storyboard skeleton · comic mode) into interactive tools: fill in a character once, auto-assemble prompts per model family, and pass every check before rendering.

1. 产品简介1. Overview

工作台是一套提示词工程方法论的可交互实现，核心目标是解决跨模型角色一致性问题。以「角色锚点」作为跨模型一致性的根，按「角色锚点层 → 生成引擎层 → 质量保障层 → 输出适配层」四层架构组织。The workbench is an interactive implementation of a prompt-engineering methodology built to solve cross-model character consistency. Character anchors are the root of consistency, organized into four layers: anchor → generation engine → quality assurance → output adaptation.

2. 快速上手2. Quick Start

3. 核心机制3. Core Mechanics

3.1 角色锚点系统3.1 Character Anchor System

锚点是跨模型保持角色一致的根。权重规范：核心身份锚点 ≥1.6（最不可变，每场强制保留，禁止替换）；核心气质标签 ≥1.3；自然语言主描述权重 0–2。Anchors are the root of cross-model consistency. Weight rules: core identity ≥1.6 (most immutable, kept every scene, never replaced); temperament tag ≥1.3; natural-language main description 0–2.

配套能力：企业 IP 锚点库（保存、复用企业 IP 角色锚点，JSON 导入/导出，团队共享预设）与 生成审计日志（自动记录所有提示词生成行为，记录不可手动删除，完整追溯链永久保留，满足企业溯源合规要求）。Companion features: the Enterprise IP Preset Library (save, reuse and share team presets via JSON import/export) and the Generation Audit Log (auto-logs every prompt generation; logs cannot be manually deleted, retaining a permanent traceability chain for compliance).

3.2 提示词生成器 · 五大家族语法3.2 Prompt Generator · Five Syntax Families

同一份角色设定 + 构图选择 → 按所选模型家族语法自动拼装；语法差异由引擎处理。Same character setup + composition choices → auto-assembled per family syntax; differences handled by the engine.

构图参数面板覆盖：画幅比例（1:1 / 3:4 / 4:3 / 16:9 / 9:16）、镜头焦段（35 / 50 / 85mm）、景别（特写 / 近景 / 中景 / 全景 / 远景）、机位角度（仰拍 / 平视 / 俯拍…）、光线方向（顺光 / 侧光 / 逆光 / 轮廓光 / 三点布光…）、光线类型与氛围、灯光强度、色温（2700K 暖黄 ~ 8000K 冷蓝）、构图类型（三分法 / 黄金螺旋 / 对称…）、景深、前景层（权重 0.5–0.8）与背景。The composition panel covers: aspect ratio (1:1 / 3:4 / 4:3 / 16:9 / 9:16), focal length (35/50/85mm), shot scale (close-up / medium / full / wide), camera angle (low / eye / high), light direction (front / side / rim / three-point), light type & mood, intensity, color temperature (2700K warm to 8000K cold), composition (rule of thirds / golden spiral / symmetry), depth of field, foreground layer (weight 0.5–0.8) and background.

「自动权重拆分」会根据角色层级自动分配前景 / 主体 / 背景权重；「提示词历史版本」支持选两条记录对比、一键导出。Auto Weight Split assigns foreground/subject/background weights by character hierarchy; Prompt History lets you compare two records and export.

3.3 负面词助手3.3 Negative-Word Bank Assistant

9 大失败类别逐项勾选 → 自动汇总负面词清单。每类自带推荐权重与「失败 → 修复」指引。Check any of the 9 failure categories and the assistant compiles a negative prompt list. Each category carries a recommended weight and a fail→fix guide.

模型适配要点：SD 用长负面词框；MJ 用 --no 且限 4–6 个短词。Model adaptation: SD uses long negative prompts; MJ uses --no with 4–6 short words.

3.4 渲染前检查清单3.4 Pre-Render Checklist

13 项 P0–P2 验证：P0 必须全过，P1 建议全过，P2 尽力满足。全部打勾后再点生成。13 P0–P2 checks: P0 must all pass, P1 should all pass, P2 best effort. Tick everything before generating.

3.5 模型能力矩阵3.5 Model Capability Matrix

同一功能在四大模型家族的实现差异——选模型前先看这里，避免用错语法。How the same capability differs across the four model families — check here before choosing a model.

3.6 视频生成提示词3.6 Video Generation Prompts

6 大视频模型语法对照 + 通用红线。交互式生成器：选模型 → 填主体 / 动作 / 场景 / 镜头 → 自动拼装。Six video-model syntax comparisons plus universal red lines. Interactive generator: pick model → fill subject / action / scene / camera → auto-assemble.

3.7 3D 生成矩阵3.7 3D Generation Matrix

6 款 3D 模型输入输出与角色一致性对照。多视角参考锁定 360 度身份，单视角仅锁正面。Six 3D models; input-output and character-consistency comparison. Multi-view references lock 360° identity; single view locks the front only.

3.8 LoRA 管理矩阵3.8 LoRA Management Matrix

5 种 LoRA 类型 + 堆叠规则 + 与权重系统交互。单 LoRA >1.0 致伪影，总权重 >2.0 致模型失稳。Five LoRA types plus stacking rules and weight-system interaction. Single LoRA >1.0 causes artifacts; total weight >2.0 destabilizes the model.

3.9 多角色空间关系3.9 Multi-Character Spatial Relations

3+ 角色场景的空间排布、深度分层、视线链、遮挡规则、比例透视。三角排布最稳；禁面部遮挡。Spatial layout, depth layering, gaze chains, occlusion rules, and proportion perspective for scenes with 3+ characters. Triangular layout is most stable; never occlude faces.

• 排布Layout：三角 / 弧形 / 自由排布Triangular, arc, free-form
• 深度分层权重Depth weights：前景 1.2–1.4 / 中景 1.0–1.2 / 背景 0.7–0.9Front 1.2–1.4 / mid 1.0–1.2 / back 0.7–0.9
• 视线链Gaze chains：单向，指向明确Unidirectional, clear target
• 比例透视Proportion：近大远小容差 ≤10%Perspective tolerance ≤10%
• 光照Lighting：优先单光源Prefer a single light source

3.10 对话式编辑链（仅 GPT-4o / Gemini）3.10 Conversational Edit Chain (GPT-4o / Gemini only)

逐轮单点修正：每轮只改一个元素，锚点句全程冻结。3 轮连续修正失败 → 退出对话，从 Round 1 重新生成。Per-round single-point fix: change one element per round, anchor sentence frozen throughout. 3 consecutive failures → exit and regenerate from Round 1.

3.11 分镜骨架模板3.11 Storyboard Skeleton Template

10 种面板角色 + 3 条镜头连续性规则 + 4 种页面排版。每行含提示词拼装规则、连续性检查项、常见失败。用户只填故事和对话，工具出结构、出提示词、出布局。Ten panel roles + three camera-continuity rules + four page layouts. Each row provides prompt assembly rules, continuity checks and common failures. You fill story and dialogue; the tool outputs structure, prompts and layout.

• 10 种面板角色：定场、对话过肩、动作特写、情绪大特、高潮跨页、登场、反打、反应、转场、收束。Ten panel roles: establishing, over-shoulder dialogue, action close-up, emotional close-up, climactic spread, entrance, reverse shot, reaction, transition, coda.
• 3 条镜头连续性：180° 轴线规则、30° 机位夹角、视线链一致。Three continuity rules: 180° axis, 30° camera angle, consistent gaze chains.
• 4 种页面排版：网格、跨页、条带、条漫式。Four page layouts: grid, spread, strip, webtoon.

3.12 漫剧模式（v2.8）3.12 Comic Mode (v2.8)

漫剧工作流闭环：面板排布规则 · 对话气泡定位 · 逐帧时序一致性验收。填故事 → 出布局 → 出气泡 → 出验收清单。The closed-loop comic workflow: panel layout rules · dialogue bubble positioning · per-frame temporal consistency validation. Fill story → layout → bubbles → validation checklist.

• 故事导入：拖拽 Word / TXT（.docx · .txt）自动解析故事内容。Story import: drag in Word / TXT (.docx · .txt) for auto-parsing.
• 排版类型：4 格 / 6 格 / 电影条带 / 跨页 / 条漫。Layouts: 4-panel, 6-panel, cinematic strip, spread, webtoon.
• 画幅：Portrait A4 / B5 / 16:9 / 1080px 竖版。Aspect: Portrait A4 / B5 / 16:9 / 1080px vertical.
• 输出：面板排布 + 气泡定位 + 时序验收清单，全部可复制。Output: panel layout + bubble positions + temporal validation checklist; all copyable.

3.13 SPL 合规认证3.13 SPL Compliance Certification

面向集成商与提示词工具厂商——证明你的产品遵循 SPL Prompt Specification 标准，可在产品上展示认证徽章。For integrators and prompt-tool vendors: prove your product follows the SPL Prompt Specification and display the certification badge.

3.14 数据安全3.14 Data Security

4. 批量工具4. Batch Tools

面向下游管线的生产级工具：Production-grade tools for downstream pipelines:

5. 常见问题5. FAQ

Q1：为什么锚点句必须全程冻结？Q1: Why must anchor sentences stay frozen?

锚点是跨模型一致性的根；同义改写会改变权重分布与语义锚定，导致不同模型渲染出不一致的角色。逐字复用才能保证可复现。Anchors are the root of cross-model consistency; paraphrasing shifts weight distribution and semantic anchoring, producing inconsistent characters. Verbatim reuse keeps outcomes reproducible.

Q2：负面词和检查清单怎么配合？Q2: How do negatives and the checklist work together?

负面词预防「已知失败模式」，检查清单验证「渲染前条件」。顺序：先按 9 类勾选负面词，再逐项过 13 项 P0–P2，全部通过后再渲染。Negatives prevent known failure modes; the checklist validates pre-render conditions. Order: compile negatives from the 9 categories, then walk the 13 P0–P2 checks, then render.

Q3：Midjourney 的负面词为什么只能 4–6 个？Q3: Why only 4–6 negative words in Midjourney?

MJ 的 --no 参数短词效果最佳；过长会降低正向提示词的权重响应。SD 等模型则适合长负面词框。MJ’s --no works best with short words; longer lists dilute positive-weight response. SD-style models prefer long negative prompts.

Q4：LoRA 权重有上限吗？Q4: Is there a LoRA weight cap?

有。单 LoRA >1.0 会致伪影；多 LoRA 总权重 >2.0 会致模型失稳。推荐区间见 3.8 节矩阵。Yes. Single LoRA >1.0 causes artifacts; combined weight >2.0 destabilizes the model. See the §3.8 ranges.

Q5：这个帮助文档为什么是站内 HTML？Q5: Why is this guide now an in-site HTML page?

原帮助文档托管在腾讯文档（海外访问受限）。本页为自包含单文件，覆盖 v2.8 全部主题，全球任何地区均可直接访问，无需登录。The previous guide lived on Tencent Docs, which is restricted overseas. This self-contained single-file page covers all v2.8 topics and is directly accessible from any region without login.

6. 术语表6. Glossary