Story to Prompts

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name: story-to-prompts description: "Convert story synopses or single-scene descriptions into high-quality text-to-image prompts. Two modes: (1) multi-scene - a story outline is split into multiple coherent scenes, each with its own prompt; (2) single-scene - a single scene description gets a prompt directly. Outputs scored prompts with bilingual versions. Use when users say story to images, generate prompts for this scene, story split, storyboard prompts, text-to-image prompt, 文生图, 分镜, 故事拆分."

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Story to Prompts

One-shot conversion from story/scene to text-to-image prompts. No interactive confirmation — output the final result directly.

Output Language

Detect language from user input:

Chinese input → primary prompt in Chinese, secondary in English

English input → primary prompt in English, secondary in Chinese

Explicit language override (e.g. "output in English", "用中文输出") → follow user instruction

All structural text (titles, character sheets, scene descriptions) matches the primary language

Entry Point

Determine mode based on user input:

Multi-scene mode: Input contains multiple events/plot points, or user explicitly requests N images

Single-scene mode: Input describes only one scene/画面, or user asks for a prompt for "one scene"

Split Strategy (Multi-scene Mode)

Priority for determining image count and split:

1. User specifies count (e.g. "4 images", "拆成6张") → use directly 2. User does not specify → split by spatiotemporal boundaries: - Identify distinct time-space units (location change, time jump) - Each independent time-space = one image - Within the same time-space, if multiple key actions exist, split into 2-3 images with different shot types 3. Default range: 3-6 images unless the story is extremely simple or very long

Workflow (Multi-scene Mode)

Complete all steps in one pass. Output final result only.

Step 1: Extract Story Baseline

Determine internally (do not output separately):

Story core (one sentence)

Character fixed features (age, hair, clothing, signature accessories)

Unified visual style

Color palette

Lighting style

Step 2: Structure Split

Determine N images, assign for each:

Shot type (refer to references/shot-types.md narrative rhythm template, adjacent images must differ)

Camera angle

Narrative function (establishing / progression / climax / resolution)

Step 3: Generate Prompt per Image

Requirements for each prompt:

Repeat character fixed features in every prompt (consistency)

Vary viewpoint, composition, posture across images (diversity)

Only include characters/objects mentioned in the current scene (appearance rule)

Include negative prompt (anti-failure)

Follow the writing spec below

Step 4: Score and Optimize

Self-evaluate each prompt on 10 dimensions and optimize:

Structure Completeness (40 pts) 1. Core intent clarity (10): Is the goal unambiguous? 2. Subject and hierarchy (10): Is the main subject clear with size ratio? 3. Composition and ratio constraints (10): Aspect ratio, viewpoint, composition technique? 4. Style anchor clarity (10): Specific style/medium specified?

Generation Quality Control (40 pts) 5. Motif unity (10): Do visual details serve a unified theme? 6. Material and lighting description (10): Specific material and light logic? 7. Constraints and negative prompts (10): Anti-failure constraints present? 8. Text-image integration (10): Text layout handled or explicitly absent?

Productization and Reusability (20 pts) 9. Parameterization (10): Easy to adjust and reuse? 10. Failure anticipation (10): Common AI errors preemptively blocked?

Logic check per prompt: character consistency, scene continuity, physics plausibility, style coherence. Fix contradictions if found.

Target: each prompt ≥ 80 points (High Quality). If below, self-optimize and output the improved version.

Workflow (Single-scene Mode)

Simpler, one pass:

1. Extract character features and visual style from the scene 2. Determine optimal shot type and composition 3. Generate prompt (same requirements as Step 3-4 above) 4. Output

Output Format

Primary language marked ★, secondary marked ☆:

### Image N | [Shot Type] | [Narrative Function]
Scene Description: [Detailed description in primary language]
Text-to-Image Prompt ★ ([Primary Language]):
[Complete detailed prompt, ready to copy-paste]
Text-to-Image Prompt ☆ ([Secondary Language]):
[Complete prompt adapted to target language conventions]
Negative Prompt: [negative keywords]
Score: [X]/100 | Level: [Product-grade / High Quality / Usable]
Strengths: [One sentence]
Improvements: [If applicable, one sentence]

Prompt Writing Spec

Structure (by priority):

[Style] + [Shot type + Composition + Camera angle] + [Subject + fixed features] + [Action/Expression] + [Environment/Background] + [Lighting/Atmosphere] + [Material/Texture] + [Quality tags] + [Negative prompt]

Bilingual output rules:

Primary language prompt: complete and detailed, ready to copy-paste

Secondary language prompt: equally complete, adapted to target language prompt conventions (not a literal translation)

Consistency rules:

Character fixed features (age, hair, clothing) must be explicitly repeated in every prompt

Style, color palette, lighting baseline must carry through all images

Key props appearance must remain consistent

Diversity rules:

Adjacent images use different shot types

Encourage different composition techniques

Character posture, expression, position may vary

Lighting intensity may be adjusted, style remains constant

Reference Files

Read on demand:

references/shot-types.md — Shot types, camera angles, narrative rhythm templates

references/composition-patterns.md — 12 composition patterns with prompt fragments

references/style-params.md — 30+ style parameters (keywords, quality tags, avoid list, lighting)