Story to Prompts

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 multi...

Security Scan

The skill is an instruction-only prompt-generation tool whose requirements and instructions are coherent with its stated purpose and request no unusual privileges or credentials.

Purpose & Capability

Name/description (story -> text-to-image prompts) matches the instructions and included reference files. No unrelated binaries, env vars, or credentials are requested.

Instruction Scope

SKILL.md confines runtime behavior to parsing user text, splitting scenes, and producing bilingual prompts scored/optimized per its spec. It does not instruct reading system files, environment variables, or contacting external endpoints. The references are local files bundled with the skill.

Install Mechanism

No install spec and no code files beyond markdown references — nothing is written to disk or downloaded during install. Lowest-risk install footprint.

Credentials

The skill requests no environment variables, credentials, or config paths. All declared requirements are minimal and proportionate to converting story text into prompts.

Persistence & Privilege

always is false and disable-model-invocation is default (agent may invoke autonomously, which is normal). The skill does not request permanent system presence or to modify other skills.

Assessment

This skill is instruction-only and internally consistent with its purpose: it generates multi- or single-scene text-to-image prompts and includes local reference files. It asks for no credentials or installs. Things to consider before installing: (1) the skill will output final prompts directly without asking follow-up questions — if you need clarification first, ask the skill to pause or provide explicit instructions in your prompt; (2) do not paste secrets or private data into text you plan to convert into prompts (those words will appear verbatim in outputs); (3) generated prompts may include style keywords that implicitly reference artists or copyrighted aesthetics — check licensing/usage policies of downstream image-generation services you plan to use.

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)