{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"github-saturndec--waoowaoo","slug":"saturndec--waoowaoo","name":"waoowaoo","type":"agent","url":"https://www.waoowaoo.com/","page_url":"https://unfragile.ai/saturndec--waoowaoo","categories":["video-generation","deployment-infra"],"tags":["ai-agent","ai-agents","automation","film-production","generative-ai","short-drama","storyboard","video-generation"],"pricing":{"model":"open_source","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"github-saturndec--waoowaoo__cap_0","uri":"capability://automation.workflow.multi.stage.novel.to.video.production.pipeline.orchestration","name":"multi-stage novel-to-video production pipeline orchestration","description":"Orchestrates a sequential workflow that transforms novel text through six distinct stages: configuration, script generation, asset creation, storyboard composition, video synthesis, and voice-over production. Uses a graph runtime system with event-driven task submission to coordinate LLM calls, image generation, video synthesis, and voice synthesis across multiple AI providers, with React Query managing client-side state synchronization and background task polling.","intents":["I need to automate the entire process of turning a novel into a promotional video with consistent characters and locations","I want to manage a complex multi-step content generation workflow where each stage depends on previous outputs","I need to track progress and retry failed steps in a long-running video production pipeline"],"best_for":["content studios automating short-drama and novel adaptation production","teams managing batch video generation with Hollywood-standard workflows","developers building multi-stage AI agent systems with human-in-the-loop approval gates"],"limitations":["Pipeline is sequential — stages cannot run in parallel, adding latency for large projects","No built-in persistence for intermediate artifacts — requires external storage integration","Task retry logic is step-level only; no cross-stage rollback or transaction semantics","React Query polling adds ~2-5s latency for task status updates vs real-time WebSocket"],"requires":["TypeScript/Node.js 18+ runtime","API keys for at least one LLM provider (OpenAI, Anthropic, etc.)","API keys for image generation (Midjourney, DALL-E, Stable Diffusion)","API keys for video synthesis (Runway, Synthesia, or equivalent)","API keys for voice synthesis (ElevenLabs, Google Cloud TTS, or equivalent)","PostgreSQL or compatible database for project/task state"],"input_types":["plain text (novel/story content)","structured JSON (project configuration, character definitions)","image references (for style guidance and character appearance)"],"output_types":["video files (MP4, WebM with lip-sync)","audio files (WAV, MP3 voice-overs)","structured JSON (storyboard frames, character metadata)","image assets (character renders, location backgrounds)"],"categories":["automation-workflow","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-saturndec--waoowaoo__cap_1","uri":"capability://text.generation.language.llm.driven.screenplay.and.narrative.generation.with.provider.abstraction","name":"llm-driven screenplay and narrative generation with provider abstraction","description":"Accepts novel text and generates screenplays/scripts using configurable LLM providers (OpenAI, Anthropic, etc.) through an abstraction layer that handles model selection, prompt engineering, and output parsing. The system maintains provider configuration state and billing tracking per model, allowing users to switch between providers and models without code changes. Integrates with the task infrastructure to submit LLM tasks asynchronously and track completion via event system.","intents":["I want to generate a screenplay from a novel using my preferred LLM provider without vendor lock-in","I need to compare screenplay quality across different LLM models and switch providers based on cost/quality tradeoffs","I want to track LLM API costs per project and model to optimize spending"],"best_for":["content creators experimenting with different LLM providers for screenplay generation","studios managing multi-project budgets with per-model cost tracking","developers building LLM-agnostic content generation systems"],"limitations":["No streaming output — entire screenplay is generated and returned as single artifact","Prompt engineering is hardcoded per stage; no user-customizable system prompts","No built-in validation of screenplay structure — relies on LLM output quality","Provider failover is manual; no automatic fallback to secondary provider on timeout"],"requires":["API key for at least one LLM provider (OpenAI, Anthropic, Claude, etc.)","Configuration of model name and API endpoint in project settings","Billing account setup for selected provider"],"input_types":["plain text (novel content, up to context window limit)","structured JSON (project metadata, character list, tone/style preferences)"],"output_types":["structured JSON (screenplay with scene descriptions, dialogue, character actions)","plain text (formatted screenplay)"],"categories":["text-generation-language","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-saturndec--waoowaoo__cap_10","uri":"capability://data.processing.analysis.artifact.lifecycle.management.with.media.reference.tracking","name":"artifact lifecycle management with media reference tracking","description":"Manages the lifecycle of generated artifacts (images, videos, audio files) with versioning, reference tracking, and cleanup policies. The system tracks which artifacts are used in which stages (e.g., character image used in storyboard frame), prevents deletion of in-use artifacts, and maintains artifact metadata (generation parameters, provider, timestamp). Implements a media reference system that maps artifacts to their usage locations in the project.","intents":["I want to see which artifacts are used in which parts of my project before deleting them","I need to track the generation parameters and provider for each artifact for reproducibility","I want to clean up unused artifacts to save storage space"],"best_for":["teams managing large numbers of generated artifacts across projects","studios with storage constraints needing artifact cleanup","developers building artifact versioning systems"],"limitations":["Reference tracking is manual — no automatic detection of artifact usage","No artifact deduplication — identical artifacts are stored separately","Cleanup is manual — no automatic deletion of unused artifacts","No artifact compression — all artifacts stored at full resolution"],"requires":["Artifact storage (local filesystem or cloud storage)","Database for artifact metadata and reference tracking"],"input_types":["image files (PNG, JPG)","video files (MP4, WebM)","audio files (WAV, MP3)"],"output_types":["structured JSON (artifact metadata with reference tracking and usage statistics)"],"categories":["data-processing-analysis","memory-knowledge"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-saturndec--waoowaoo__cap_11","uri":"capability://safety.moderation.workspace.and.project.isolation.with.multi.tenant.support","name":"workspace and project isolation with multi-tenant support","description":"Implements workspace-level isolation that separates projects, assets, and credentials between different users or teams. The system enforces access control at the workspace level, with role-based permissions (admin, editor, viewer) for project access. Each workspace maintains its own Asset Hub, project list, and provider configurations, with no cross-workspace data sharing except through explicit export/import.","intents":["I want to create a workspace for my team with separate projects and shared assets","I need to control who can access which projects and assets in my workspace","I want to isolate my API credentials and billing per workspace"],"best_for":["teams managing multiple projects with different access levels","studios with separate departments needing isolated workspaces","enterprises requiring multi-tenant isolation"],"limitations":["No cross-workspace collaboration — assets cannot be shared between workspaces","Role-based access control is basic — only admin/editor/viewer roles","No audit logging — cannot track who accessed what and when","No workspace-level billing — costs are tracked per project, not per workspace"],"requires":["User authentication system","Database for workspace and project metadata","Access control enforcement in API layer"],"input_types":["structured JSON (workspace name, members, roles)"],"output_types":["structured JSON (workspace metadata with member list and permissions)"],"categories":["safety-moderation","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-saturndec--waoowaoo__cap_2","uri":"capability://image.visual.character.and.location.asset.generation.with.style.consistency.enforcement","name":"character and location asset generation with style consistency enforcement","description":"Generates character images and location backgrounds using image generation APIs (Midjourney, DALL-E, Stable Diffusion) with style reference forwarding to ensure visual consistency across all generated assets. The system maintains a character management subsystem that stores character descriptions, appearance references, and style parameters, then injects these into image generation prompts. Uses a candidate selector UI that presents multiple generation options for human approval before committing assets to the project.","intents":["I need to generate character images that look consistent across all scenes in the video","I want to generate location backgrounds that match the visual style of my characters","I need to iterate on character appearance by regenerating with different style references"],"best_for":["video production teams ensuring visual consistency across multi-scene projects","content creators who want AI-generated assets but need human approval before use","studios managing character libraries with style guidelines"],"limitations":["Style consistency is prompt-based, not enforced at model level — quality depends on image generator's prompt understanding","No built-in image editing or inpainting — must regenerate entire image to fix details","Candidate selection is manual; no automatic filtering or ranking of generated options","Character style references must be manually uploaded; no automatic style extraction from reference images"],"requires":["API key for image generation provider (Midjourney, DALL-E, Stable Diffusion, etc.)","Character metadata including name, description, appearance details","Optional: style reference images (JPG, PNG)"],"input_types":["structured JSON (character name, description, appearance, style parameters)","image files (style reference images, up to 5MB each)","plain text (location descriptions, visual style notes)"],"output_types":["image files (PNG, JPG character renders and location backgrounds)","structured JSON (asset metadata, generation parameters, approval status)"],"categories":["image-visual","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-saturndec--waoowaoo__cap_3","uri":"capability://planning.reasoning.storyboard.composition.with.frame.sequencing.and.visual.planning","name":"storyboard composition with frame sequencing and visual planning","description":"Composes storyboards by sequencing generated character and location assets into frames that correspond to screenplay scenes. The system maps screenplay scenes to storyboard frames, selects appropriate character and location assets for each frame, and presents a visual timeline for human review and editing. Uses a frame-level candidate selector that allows swapping assets, reordering scenes, or adjusting frame timing before committing to video synthesis.","intents":["I want to visually plan the video before synthesis by arranging characters and locations into a storyboard","I need to adjust which characters appear in which scenes and swap assets if a generation didn't work well","I want to preview the visual flow of the video and make edits before expensive video synthesis"],"best_for":["video directors who want to review visual composition before synthesis","content teams iterating on scene arrangement and asset selection","studios with approval workflows requiring visual storyboard sign-off"],"limitations":["Storyboard is static images only — no motion preview or timing visualization","Frame timing is estimated from screenplay; no manual frame duration adjustment","Asset swapping is limited to existing generated assets — cannot generate new assets from storyboard view","No collaboration features — single-user editing only"],"requires":["Completed screenplay with scene descriptions","Generated character and location assets from Assets stage","Character-to-scene mapping from screenplay"],"input_types":["structured JSON (screenplay scenes with character and location references)","image files (character and location assets from previous stage)"],"output_types":["structured JSON (storyboard frame sequence with asset references and timing)","image files (storyboard preview grid)"],"categories":["planning-reasoning","image-visual"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-saturndec--waoowaoo__cap_4","uri":"capability://image.visual.video.synthesis.with.lip.sync.and.character.animation","name":"video synthesis with lip-sync and character animation","description":"Synthesizes animated videos from storyboard frames and voice-over audio using video generation APIs (Runway, Synthesia, or equivalent) with integrated lip-sync to match character mouth movements to dialogue. The system submits video synthesis tasks asynchronously, tracks generation progress, and returns final video files with synchronized audio and animation. Handles frame-to-frame transitions and character positioning based on storyboard layout.","intents":["I want to generate a video with animated characters that speak the dialogue with synchronized lip movements","I need to produce multiple video variations with different character animations or transitions","I want to track video generation progress and retry failed synthesis tasks"],"best_for":["content studios producing short-form video content with character animation","creators needing lip-synced character videos without manual animation","teams generating multiple video variations for A/B testing"],"limitations":["Lip-sync quality depends on video generator's implementation — may not match all phonemes perfectly","No control over animation style or character movement — fixed by video generator","Video generation is slow (5-30 minutes per video) — not suitable for real-time preview","Output resolution and frame rate are limited by video generator capabilities"],"requires":["API key for video synthesis provider (Runway, Synthesia, etc.)","Storyboard with frame sequence and asset references","Voice-over audio file (WAV, MP3) with matching duration","Character and location images from Assets stage"],"input_types":["structured JSON (storyboard frame sequence with timing and asset references)","image files (character and location assets)","audio file (voice-over WAV or MP3)"],"output_types":["video file (MP4, WebM with H.264 or VP9 codec)","structured JSON (video metadata, generation parameters, status)"],"categories":["image-visual","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-saturndec--waoowaoo__cap_5","uri":"capability://text.generation.language.voice.over.synthesis.with.multi.provider.tts.and.character.voice.assignment","name":"voice-over synthesis with multi-provider tts and character voice assignment","description":"Synthesizes voice-over audio from screenplay dialogue using text-to-speech APIs (ElevenLabs, Google Cloud TTS, Azure Speech, etc.) with character-to-voice assignment and voice cloning support. The system maintains a voice management subsystem that stores voice profiles (provider, model, language, tone), maps characters to voices, and generates audio for each dialogue line. Supports voice cloning from reference audio samples to create custom character voices.","intents":["I want to generate voice-overs for all dialogue with different voices for different characters","I need to use a specific voice provider and customize voice tone, accent, or speed per character","I want to clone a voice from a reference audio sample to create a custom character voice"],"best_for":["video producers creating multi-character dialogue with consistent voice assignments","studios managing voice libraries with character-to-voice mappings","creators using voice cloning to match specific character personas"],"limitations":["Voice cloning quality depends on reference audio quality — requires 30+ seconds of clean audio","No real-time voice preview — must generate full audio to hear result","Voice consistency across multiple dialogue lines depends on TTS provider stability","No support for emotional tone variation within dialogue — tone is fixed per character"],"requires":["API key for TTS provider (ElevenLabs, Google Cloud TTS, Azure Speech, etc.)","Screenplay with dialogue and character assignments","Optional: reference audio samples for voice cloning (WAV, MP3, 30+ seconds)"],"input_types":["structured JSON (screenplay dialogue with character names and line numbers)","structured JSON (character-to-voice mappings with voice parameters)","audio files (reference samples for voice cloning, WAV or MP3)"],"output_types":["audio file (WAV or MP3 voice-over with all dialogue lines)","structured JSON (voice metadata, character-to-voice mappings, generation parameters)"],"categories":["text-generation-language","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-saturndec--waoowaoo__cap_6","uri":"capability://memory.knowledge.global.asset.hub.with.reusable.character.and.location.libraries","name":"global asset hub with reusable character and location libraries","description":"Maintains a global asset library (Asset Hub) that stores reusable character definitions, location backgrounds, and voice profiles across all projects. The system allows users to create global assets once and reference them in multiple projects, with project-level asset overrides for customization. Uses a hierarchical asset management system that separates global assets (shared across workspace) from project assets (specific to one project), with asset versioning and usage tracking.","intents":["I want to create a character once and reuse it across multiple video projects","I need to maintain a library of location backgrounds and voice profiles for my studio","I want to override a global asset for a specific project without affecting other projects"],"best_for":["studios producing multiple projects with shared character universes","content teams managing reusable asset libraries across projects","creators building character franchises with consistent appearances"],"limitations":["Asset versioning is manual — no automatic version tracking or rollback","No asset usage analytics — cannot see which projects use which assets","Asset sharing is workspace-level only — no cross-workspace asset sharing","No asset deprecation workflow — old assets remain in library indefinitely"],"requires":["Workspace with multiple projects","Character or location asset definitions (JSON metadata + images)"],"input_types":["structured JSON (character definitions, location descriptions, voice profiles)","image files (character renders, location backgrounds)"],"output_types":["structured JSON (asset metadata with global/project scope indicators)","asset references (pointers to global assets for use in projects)"],"categories":["memory-knowledge","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-saturndec--waoowaoo__cap_7","uri":"capability://automation.workflow.task.queue.and.background.job.processing.with.provider.specific.handlers","name":"task queue and background job processing with provider-specific handlers","description":"Implements an asynchronous task queue system that submits image generation, video synthesis, LLM, and voice synthesis tasks to background workers with provider-specific handlers. The system maintains task state (pending, running, completed, failed), tracks task progress, and provides retry logic with exponential backoff. Uses event-driven architecture where task completion triggers downstream stage transitions and artifact management updates.","intents":["I want to submit long-running tasks (video synthesis, image generation) without blocking the UI","I need to track task progress and retry failed tasks without manual intervention","I want to handle different task types (image, video, LLM, voice) with provider-specific logic"],"best_for":["teams running long-running content generation pipelines","systems requiring reliable task execution with retry logic","developers building multi-provider AI orchestration systems"],"limitations":["Task queue is in-process only — no distributed queue support (no Redis, RabbitMQ)","Retry logic is exponential backoff only — no circuit breaker or adaptive retry","No task prioritization — all tasks processed in FIFO order","Task state is not persisted across server restarts — in-flight tasks are lost"],"requires":["Background task worker process (Node.js)","API keys for all enabled providers (image, video, LLM, voice)","Database for task state persistence"],"input_types":["structured JSON (task definition with type, provider, parameters, input references)"],"output_types":["structured JSON (task status, progress, result artifacts, error messages)"],"categories":["automation-workflow","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-saturndec--waoowaoo__cap_8","uri":"capability://data.processing.analysis.react.query.based.client.side.state.management.with.real.time.task.polling","name":"react query-based client-side state management with real-time task polling","description":"Uses React Query to manage client-side state for projects, assets, tasks, and workflow progress with automatic background polling for task status updates. The system maintains query caches for project data, asset lists, and task status, with mutations for creating/updating projects and submitting tasks. Implements polling intervals that adapt based on task state (faster polling for in-progress tasks, slower for completed tasks) to balance responsiveness and server load.","intents":["I want the UI to automatically update when background tasks complete without manual refresh","I need to manage complex project state with multiple assets and tasks without prop drilling","I want to handle optimistic updates and rollback when mutations fail"],"best_for":["React-based web applications with long-running background tasks","teams building real-time collaborative editing interfaces","developers managing complex client-side state with server synchronization"],"limitations":["Polling adds 2-5s latency vs real-time WebSocket updates","Query cache invalidation is manual — no automatic cache busting on server changes","Optimistic updates can diverge from server state if mutations fail silently","No offline support — all queries require active server connection"],"requires":["React 16.8+ with hooks support","React Query 3.0+","Backend API with REST endpoints for queries and mutations"],"input_types":["REST API responses (JSON)"],"output_types":["React hooks (useQuery, useMutation, useInfiniteQuery)"],"categories":["data-processing-analysis","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-saturndec--waoowaoo__cap_9","uri":"capability://tool.use.integration.project.configuration.and.multi.provider.api.credential.management","name":"project configuration and multi-provider api credential management","description":"Provides a configuration system that allows users to select and configure multiple AI providers (LLM, image generation, video synthesis, TTS) at the project level, with secure credential storage and per-provider model selection. The system validates API credentials on configuration and tracks provider usage and costs per project. Supports switching providers mid-project without losing project state, with automatic provider failover if configured.","intents":["I want to configure which AI providers to use for my project (OpenAI vs Anthropic for LLM, etc.)","I need to manage API credentials securely without exposing them in the UI","I want to track costs per provider and compare pricing across providers"],"best_for":["teams evaluating multiple AI providers and comparing costs","studios managing projects with different provider requirements","developers building provider-agnostic AI systems"],"limitations":["Credentials are stored in database — requires encryption at rest","No built-in provider failover — manual switching only","Cost tracking is approximate — based on API usage estimates, not actual billing","No provider health monitoring — cannot detect provider outages automatically"],"requires":["API keys for selected providers","Project-level configuration UI","Encrypted credential storage in database"],"input_types":["structured JSON (provider name, API key, model name, configuration parameters)"],"output_types":["structured JSON (provider configuration with masked credentials, usage statistics)"],"categories":["tool-use-integration","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":53,"verified":false,"data_access_risk":"high","permissions":["TypeScript/Node.js 18+ runtime","API keys for at least one LLM provider (OpenAI, Anthropic, etc.)","API keys for image generation (Midjourney, DALL-E, Stable Diffusion)","API keys for video synthesis (Runway, Synthesia, or equivalent)","API keys for voice synthesis (ElevenLabs, Google Cloud TTS, or equivalent)","PostgreSQL or compatible database for project/task state","API key for at least one LLM provider (OpenAI, Anthropic, Claude, etc.)","Configuration of model name and API endpoint in project settings","Billing account setup for selected provider","Artifact storage (local filesystem or cloud storage)"],"failure_modes":["Pipeline is sequential — stages cannot run in parallel, adding latency for large projects","No built-in persistence for intermediate artifacts — requires external storage integration","Task retry logic is step-level only; no cross-stage rollback or transaction semantics","React Query polling adds ~2-5s latency for task status updates vs real-time WebSocket","No streaming output — entire screenplay is generated and returned as single artifact","Prompt engineering is hardcoded per stage; no user-customizable system prompts","No built-in validation of screenplay structure — relies on LLM output quality","Provider failover is manual; no automatic fallback to secondary provider on timeout","Reference tracking is manual — no automatic detection of artifact usage","No artifact deduplication — identical artifacts are stored separately","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.7060390722057408,"quality":0.49,"ecosystem":0.7000000000000001,"match_graph":0.25,"freshness":0.75,"weights":{"adoption":0.25,"quality":0.25,"ecosystem":0.1,"match_graph":0.28,"freshness":0.12}},"observed_outcomes":{"matches":0,"success_rate":0,"avg_confidence":0,"top_intents":[],"last_matched_at":null},"maintenance":{"status":"active","updated_at":"2026-05-24T12:16:22.063Z","last_scraped_at":"2026-05-03T13:57:04.027Z","last_commit":"2026-05-01T16:13:11Z"},"community":{"stars":11970,"forks":2712,"weekly_downloads":null,"model_downloads":null,"model_likes":null}},"distribution":{"claim_url":"https://unfragile.ai/submit?claim=saturndec--waoowaoo","compare_url":"https://unfragile.ai/compare?artifact=saturndec--waoowaoo"}},"signature":"ByyO2Wzz/TWV+1gUJoJbICL9Koj4T3E2RfefHqAsmp5Y7d2SLzXOijONHdik29ysMEla5OH0XNPN5yzCBQ3uDg==","signedAt":"2026-06-22T12:45:04.503Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/saturndec--waoowaoo","artifact":"https://unfragile.ai/saturndec--waoowaoo","verify":"https://unfragile.ai/api/v1/verify?slug=saturndec--waoowaoo","publicKey":"https://unfragile.ai/api/v1/trust-passport-public-key","spec":"https://unfragile.ai/trust","schema":"https://unfragile.ai/schema.json","docs":"https://unfragile.ai/docs"}}