storyboard-prompting
Generate detailed image prompts for storyboard frames optimized for Midjourney, DALL-E, and Stable Diffusion
What this skill does
# Storyboard Prompting Skill ## Purpose Create detailed, production-ready image generation prompts for storyboard frames. These prompts should produce consistent, cinematic images that communicate composition, lighting, mood, and action for pre-visualization. ## Prompt Architecture ### Core Structure ``` [SUBJECT] + [COMPOSITION] + [LIGHTING] + [MOOD/ATMOSPHERE] + [STYLE] + [TECHNICAL] ``` ### Component Breakdown | Component | Description | Examples | |-----------|-------------|----------| | Subject | Who/what is in frame | "detective in trench coat" | | Composition | Framing and arrangement | "medium close-up, rule of thirds" | | Lighting | Light sources and quality | "rim lighting, high contrast" | | Mood | Emotional atmosphere | "tense, ominous" | | Style | Visual reference | "noir, cinematic" | | Technical | Camera/image specs | "35mm, shallow DOF" | ## Platform-Specific Optimization ### Midjourney ``` Midjourney v6 parameters: --ar [aspect ratio] (16:9, 2.39:1, 4:3) --s [stylize] (0-1000, default 100) --c [chaos] (0-100, for variation) --q [quality] (0.25, 0.5, 1, 2) --style raw (less Midjourney aesthetic) Structure: [Subject and action], [composition], [lighting], [mood], [style reference], cinematic still, film photography --ar 16:9 --s 150 ``` ### DALL-E ``` DALL-E 3 optimization: - Natural language descriptions work well - Be specific about what you want - Include negative instructions when needed - Reference artistic styles by description, not artist name Structure: A cinematic film still of [subject], [composition description]. The scene has [lighting description] creating a [mood] atmosphere. Shot on [camera/lens], [style description]. ``` ### Stable Diffusion ``` Positive prompt: (cinematic:1.3), (film still:1.2), [subject], [composition], [lighting], [mood], [style], detailed, high quality, 8k Negative prompt: cartoon, anime, illustration, drawing, painting, blurry, low quality, watermark, text, deformed, ugly, bad anatomy Settings: - CFG Scale: 7-12 - Steps: 30-50 - Sampler: DPM++ 2M Karras or Euler a ``` ## Shot Type Prompts ### Extreme Wide Shot (EWS) ``` vast landscape with tiny silhouetted figure, establishing shot, epic scale, environmental storytelling, cinematic composition, golden hour lighting, anamorphic lens flare --ar 2.39:1 ``` ### Wide Shot (WS) ``` full body shot of [character] standing in [environment], environmental context visible, subject in lower third, motivated practical lighting, cinematic atmosphere --ar 16:9 ``` ### Medium Shot (MS) ``` medium shot of [character] from waist up, [action/pose], [background environment], shallow depth of field, three-point lighting setup, film grain --ar 16:9 ``` ### Close-Up (CU) ``` close-up portrait of [character], [expression], face fills frame, soft key light, dramatic shadows, intimate composition, emotional intensity, 85mm lens --ar 16:9 ``` ### Extreme Close-Up (ECU) ``` extreme close-up of [detail/feature], macro detail, selective focus, dramatic lighting, texture emphasis, cinematic tension, tight framing --ar 16:9 ``` ## Lighting Prompts ### Natural Light ``` golden hour sunlight, warm tones, long shadows, natural window light, overcast diffusion, magic hour, practical sun ``` ### Studio/Artificial ``` three-point lighting, rim light, motivated light, practical lamps, neon glow, fluorescent overhead, spotlight, volumetric light ``` ### Mood Lighting ``` chiaroscuro, high contrast, low key, high key, silhouette, backlit, lens flare, god rays, atmospheric haze, dusty light beams ``` ## Composition Prompts ### Framing ``` rule of thirds, centered composition, symmetrical frame, off-center subject, negative space, frame within frame, leading lines, diagonal composition, Dutch angle ``` ### Depth ``` foreground elements, layered composition, deep focus, shallow depth of field, background blur bokeh, environmental depth, atmospheric perspective ``` ## Storyboard Frame Template ```markdown ## Frame [ID]: [Beat Description] ### Scene Context - **Scene:** [Number and title] - **Shot:** [Size and angle] - **Action:** [What's happening] ### Visual Specifications - **Composition:** [Framing details] - **Lighting:** [Light sources and mood] - **Characters:** [Who's in frame, expressions] - **Environment:** [Setting details] ### Image Prompts **Midjourney:** ``` [Full prompt with parameters] ``` **DALL-E:** ``` [Natural language prompt] ``` **Stable Diffusion:** ``` Positive: [prompt] Negative: [negative prompt] ``` ### Frame Notes - **Dialogue:** "[Any dialogue]" - **Duration:** [Estimated seconds] - **Movement:** [Camera or subject movement] ``` ## Style Reference Library ### Film Noir ``` high contrast black and white, dramatic shadows, venetian blind shadows, rain-slicked streets, cigarette smoke, fedoras, low-key lighting ``` ### Sci-Fi ``` neon lights, holographic displays, lens flares, futuristic architecture, chrome surfaces, volumetric lighting, blue and orange color grade ``` ### Horror ``` underexposed, deep shadows, obscured faces, practical effects, desaturated colors, fog, dutch angles, motivated darkness ``` ### Romance ``` soft focus, warm lighting, golden hour, lens flare, shallow depth of field, intimate framing, natural expressions ``` ## Quality Checklist - [ ] Shot size and angle specified - [ ] Lighting direction and quality described - [ ] Mood/atmosphere conveyed - [ ] Character positioning clear - [ ] Environment context included - [ ] Style reference appropriate - [ ] Technical specs match project - [ ] Aspect ratio specified - [ ] Platform optimized
Related in Image & Video
watch
IncludedWatch a video (URL or local path). Downloads with yt-dlp, extracts auto-scaled frames with ffmpeg, pulls the transcript from captions (or Whisper API fallback), and hands the result to Claude so it can answer questions about what's in the video.
physical-ai-defect-image-generation
IncludedUse when the user wants to orchestrate defect image generation, run associated setup, or handle outputs on OSMO. The Day 0 path handles cold-start with USD-to-ROI, image-edit augmentation, and AnomalyGen to create initial PCBA datasets. The Day 1 path performs inference and labeling on real images. This skill helps with first-time asset setup, creation of finetuning checkpoints, and configuring deployment. Trigger keywords: defect image generation, dig workflow, dig pipeline, defect image detection workflow, aoi pipeline, aoi anomalygen, usd2roi anomalygen, day 0 pcba, day 1 pcba, day 1 real-photo alignment, day 1 manual roi, metal surface anomaly, glass defect, anomalygen finetune, setup_pcb, setup_metal, setup_glass, setup_pretrained, dig setup, dig datasets, dig pretrained checkpoint, dig image-edit endpoint.
accelint-react-best-practices
IncludedReact performance optimization and best practices. ALWAYS use this skill when working with any React code - writing components, hooks, JSX; refactoring; optimizing re-renders, memoization, state management; reviewing for performance; fixing hydration mismatches; debugging infinite re-renders, stale closures, input focus loss, animations restarting; preventing remounting; implementing transitions, lazy initialization, effect dependencies. Even simple React tasks benefit from these patterns. Covers React 19+ (useEffectEvent, Activity, ref props). Triggers - useEffect, useState, useMemo, useCallback, memo, inline components, nested components, components inside components, re-render, performance, hydration, SSR, Next.js, useDeferredValue, combined hooks.
elevenlabs-agents
IncludedBuild conversational AI voice agents with ElevenLabs Platform using React, JavaScript, React Native, or Swift SDKs. Configure agents, tools (client/server/MCP), RAG knowledge bases, multi-voice, and Scribe real-time STT. Use when: building voice chat interfaces, implementing AI phone agents with Twilio, configuring agent workflows or tools, adding RAG knowledge bases, testing with CLI "agents as code", or troubleshooting deprecated @11labs packages, Android audio cutoff, CSP violations, dynamic variables, or WebRTC config. Keywords: ElevenLabs Agents, ElevenLabs voice agents, AI voice agents, conversational AI, @elevenlabs/react, @elevenlabs/client, @elevenlabs/react-native, @elevenlabs/elevenlabs-js, @elevenlabs/agents-cli, elevenlabs SDK, voice AI, TTS, text-to-speech, ASR, speech recognition, turn-taking model, WebRTC voice, WebSocket voice, ElevenLabs conversation, agent system prompt, agent tools, agent knowledge base, RAG voice agents, multi-voice agents, pronunciation dictionary, voice speed control, elevenlabs scribe, @11labs deprecated, Android audio cutoff, CSP violation elevenlabs, dynamic variables elevenlabs, case-sensitive tool names, webhook authentication
humanizer
IncludedHumanize AI-generated text by detecting and removing patterns typical of LLM output. Rewrites text to sound natural, specific, and human. Uses 28 pattern detectors, 560+ AI vocabulary terms across 3 tiers, and statistical analysis (burstiness, type-token ratio, readability) for comprehensive detection. Use when asked to humanize text, de-AI writing, make content sound more natural/human, review writing for AI patterns, score text for AI detection, or improve AI-generated drafts. Covers content, language, style, communication, and filler categories.
generating-mermaid-diagrams
IncludedSalesforce architecture diagrams using Mermaid with ASCII fallback. Use this skill when generating text-based diagrams for Salesforce architecture, OAuth flows, ERDs, integration sequences, or Agentforce structure. TRIGGER when: user says "diagram", "visualize", "ERD", or asks for sequence diagrams, flowcharts, class diagrams, or architecture visualizations in Mermaid. DO NOT TRIGGER when: user wants PNG/SVG image output (use generating-visual-diagrams), or asks about non-Salesforce systems.