{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"github-calesthio--openmontage","slug":"calesthio--openmontage","name":"OpenMontage","type":"repo","url":"https://github.com/calesthio/OpenMontage","page_url":"https://unfragile.ai/calesthio--openmontage","categories":["app-builders","deployment-infra"],"tags":["agent","agentic-ai","ai","claude","copilot","cursor","elevenlabs","ffmpeg","flux","image-generation","open-source","openai","python","remotion","stable-diffusion","text-to-speech","text-to-video","video-generation","video-production"],"pricing":{"model":"open_source","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"github-calesthio--openmontage__cap_0","uri":"capability://planning.reasoning.agent.first.orchestration.via.ide.coding.assistants","name":"agent-first orchestration via ide coding assistants","description":"Delegates video production orchestration to the LLM running in the user's IDE (Claude Code, Cursor, Windsurf) rather than making runtime API calls for control logic. The agent reads YAML pipeline manifests, interprets specialized skill instructions, executes Python tools sequentially, and persists state via checkpoint files. This eliminates latency and cost of cloud orchestration while keeping the user's coding assistant as the control plane.","intents":["Use my IDE's AI assistant as the orchestrator for multi-step video production without external API calls","Have the agent understand pipeline stages and make decisions based on local context","Maintain full transparency and human control over production decisions"],"best_for":["Developers using Claude Code, Cursor, or Windsurf as their primary IDE","Teams wanting to avoid cloud orchestration costs and latency","Builders who want the LLM to act as the intelligent controller"],"limitations":["Requires IDE with integrated AI assistant support — not compatible with standalone CLI or API-only workflows","Agent decision quality depends on LLM capability and context window size","No built-in fallback if IDE connection drops mid-pipeline"],"requires":["Claude Code, Cursor, or Windsurf IDE with AI assistant enabled","Python 3.9+","YAML pipeline manifests in pipeline_defs/ directory"],"input_types":["natural language requests","YAML pipeline manifests","checkpoint JSON state files"],"output_types":["executed Python tool calls","checkpoint state updates","human-readable agent decisions"],"categories":["planning-reasoning","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-calesthio--openmontage__cap_1","uri":"capability://automation.workflow.pipeline.manifest.driven.production.workflows","name":"pipeline manifest-driven production workflows","description":"Structures all video production work into YAML-defined pipeline stages with explicit inputs, outputs, and tool sequences. Each pipeline manifest declares a series of named stages (e.g., 'script', 'asset_generation', 'composition') with tool dependencies and human approval gates. The agent reads these manifests to understand the production flow and enforces 'Rule Zero' — all production requests must flow through a registered pipeline, preventing ad-hoc execution.","intents":["Define repeatable video production workflows as code (YAML manifests)","Ensure every production follows the same structured stages and quality gates","Checkpoint progress between stages so work can resume if interrupted"],"best_for":["Teams producing videos at scale with consistent workflows","Builders wanting to enforce production governance and approval gates","Organizations needing audit trails of production decisions"],"limitations":["Requires upfront YAML manifest design — not suitable for highly ad-hoc, one-off productions","Pipeline changes require manifest updates; no runtime pipeline modification","Checkpoint system adds ~50-100ms per stage transition for state serialization"],"requires":["YAML pipeline manifest files in pipeline_defs/ directory","Checkpoint directory with write permissions","Python 3.9+ with PyYAML support"],"input_types":["YAML pipeline manifests","stage input parameters","checkpoint JSON files"],"output_types":["stage execution logs","checkpoint state snapshots","pipeline completion reports"],"categories":["automation-workflow","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-calesthio--openmontage__cap_10","uri":"capability://image.visual.talking.head.video.generation.with.avatar.support","name":"talking head video generation with avatar support","description":"Provides a pipeline for generating talking head videos where a digital avatar or real person speaks a script. The system supports multiple avatar providers (D-ID, Synthesia, Runway), voice cloning for consistent narration, and lip-sync synchronization. The agent can generate talking head videos from text scripts without requiring video recording or manual editing.","intents":["Generate talking head videos with digital avatars or real people without recording","Create branded video content with consistent narrator voices","Produce personalized video messages at scale"],"best_for":["Companies creating branded video content with consistent presenters","Teams generating personalized video messages (sales, support, education)","Builders automating video production without hiring actors or videographers"],"limitations":["Avatar quality varies by provider; some look uncanny or robotic","Lip-sync quality depends on provider; some providers have noticeable sync issues","Talking head videos are limited to head-and-shoulders framing; no full-body movement","Premium avatar providers (Synthesia, D-ID) cost $0.10-1.00 per minute of video"],"requires":["API key for avatar provider (D-ID, Synthesia, Runway) OR local avatar model","API key for TTS provider (ElevenLabs, OpenAI)","Python 3.9+","4GB+ RAM"],"input_types":["text script","avatar selection","voice profile"],"output_types":["MP4 video file","avatar metadata","lip-sync timing data"],"categories":["image-visual","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-calesthio--openmontage__cap_11","uri":"capability://image.visual.cinematic.video.generation.with.shot.planning","name":"cinematic video generation with shot planning","description":"Provides a pipeline for generating cinematic videos with planned shot sequences, camera movements, and visual effects. The system includes a shot prompt builder that generates detailed cinematography prompts based on shot type (wide, close-up, tracking, etc.), lighting (golden hour, dramatic, soft), and composition principles. The agent orchestrates image generation, video composition, and effects to create cinematic sequences.","intents":["Generate cinematic video sequences with professional shot planning","Create product videos, trailers, or cinematic content with consistent visual language","Apply cinematography principles to automated video generation"],"best_for":["Production companies creating cinematic content","Brands producing high-quality product videos","Filmmakers exploring AI-assisted cinematography"],"limitations":["Cinematic quality depends on image generation and composition; may not match professional cinematography","Shot planning is automated but may not match human-designed storyboards","Camera movements are limited to Remotion's animation capabilities; no true 3D camera tracking","Generating cinematic sequences (5-10 minutes) costs $100-500 and takes 30-60 minutes"],"requires":["API keys for image generation (Flux, DALL-E) and video generation (Runway, Synthesia)","Node.js 18+ for Remotion rendering","Python 3.9+","16GB+ RAM for complex compositions"],"input_types":["cinematic brief (mood, style, subject)","shot list or storyboard","music/audio track"],"output_types":["MP4 video file","shot breakdown","cinematography analysis"],"categories":["image-visual","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-calesthio--openmontage__cap_12","uri":"capability://image.visual.podcast.repurposing.into.short.form.video.clips","name":"podcast repurposing into short-form video clips","description":"Provides a pipeline for converting long-form podcast audio into short-form video clips (TikTok, YouTube Shorts, Instagram Reels). The system extracts key moments from podcast transcripts, generates visual assets (images, animations, text overlays), and creates short videos with captions and background visuals. The agent can repurpose a 1-hour podcast into 10-20 short clips automatically.","intents":["Convert podcast episodes into short-form video content for social media","Maximize content reach by repurposing long-form audio into multiple short clips","Automate video creation from existing podcast content"],"best_for":["Podcast creators wanting to expand reach to social media platforms","Content marketing teams repurposing existing audio content","Creators wanting to maximize content ROI through repurposing"],"limitations":["Clip extraction is automated but may miss important context or select awkward moments","Visual assets are generated automatically; may not match podcast content perfectly","Captions require accurate transcription; errors in transcription propagate to video","Typical podcast (1 hour) generates 10-20 clips costing $30-100 in API calls"],"requires":["Podcast audio file or transcript","API keys for image generation and TTS","Python 3.9+","Transcription service (Whisper, Rev, or manual transcript)"],"input_types":["podcast audio file","podcast transcript","clip duration preferences"],"output_types":["MP4 video files (one per clip)","clip metadata (timestamp, transcript excerpt)","social media captions"],"categories":["image-visual","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-calesthio--openmontage__cap_13","uri":"capability://text.generation.language.multi.language.localization.with.automatic.translation.and.voice.cloning","name":"multi-language localization with automatic translation and voice cloning","description":"Provides an end-to-end localization pipeline that translates video scripts to multiple languages, generates localized narration with native-speaker voices, and re-composes videos with localized text overlays. The system maintains visual consistency across language versions while adapting text and narration. A single source video can be automatically localized to 20+ languages without re-recording or re-shooting.","intents":["Localize videos to multiple languages without re-recording or re-shooting","Generate native-speaker narration for each language automatically","Maintain visual consistency across language versions"],"best_for":["Global companies producing videos for international audiences","Educational content creators localizing courses to multiple languages","SaaS companies supporting multiple language markets"],"limitations":["Translation quality depends on translation service; may require human review for accuracy","TTS voice quality varies by language; some languages have limited voice options","Text overlays may need manual adjustment for languages with different text lengths (e.g., German vs. Chinese)","Localizing to 20 languages costs $200-500 in API calls and takes 1-2 hours"],"requires":["API keys for translation service (Google Translate, DeepL) and TTS (ElevenLabs, Google Cloud)","Python 3.9+","Source video in one language"],"input_types":["source video","source script","target language list"],"output_types":["localized MP4 videos (one per language)","translated scripts","localization metadata"],"categories":["text-generation-language","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-calesthio--openmontage__cap_14","uri":"capability://tool.use.integration.tool.registry.and.auto.discovery.with.basetool.contract","name":"tool registry and auto-discovery with basetool contract","description":"Implements a tool registry system where all video production tools (image generation, TTS, video composition, etc.) inherit from a BaseTool contract that defines a standard interface (execute, validate_inputs, estimate_cost). The registry auto-discovers tools at runtime and exposes them to the agent through a standardized API. This allows new tools to be added without modifying the core system.","intents":["Add new video production tools without modifying core system code","Ensure all tools follow consistent interface and error handling","Enable the agent to discover and use tools dynamically"],"best_for":["Developers extending OpenMontage with custom tools","Teams building tool ecosystems on top of OpenMontage","Organizations wanting to standardize tool interfaces"],"limitations":["All tools must inherit from BaseTool; incompatible tools require wrappers","Tool discovery is filesystem-based; requires tools to be in specific directories","No built-in tool versioning; multiple versions of same tool may cause conflicts"],"requires":["Python 3.9+","Tools in tools/ directory","Inheritance from BaseTool class"],"input_types":["tool class definitions","tool metadata"],"output_types":["tool registry","tool API documentation"],"categories":["tool-use-integration","code-generation-editing"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-calesthio--openmontage__cap_15","uri":"capability://safety.moderation.quality.governance.and.production.guardrails","name":"quality governance and production guardrails","description":"Implements Meta Skills that enforce quality standards and production governance throughout the pipeline. This includes human approval gates at critical stages (after scripting, before expensive asset generation), quality checks (image coherence, audio sync, video duration), and rollback mechanisms if quality thresholds are not met. The system can halt production if quality metrics fall below acceptable levels.","intents":["Enforce quality standards across all video productions","Require human approval before expensive operations","Automatically detect and flag quality issues before final output"],"best_for":["Organizations producing videos for external audiences (marketing, education)","Teams with strict quality requirements","Builders wanting to prevent low-quality outputs from being published"],"limitations":["Quality checks are heuristic-based; may have false positives/negatives","Human approval gates add latency to production (requires human response time)","Rollback mechanisms may discard expensive assets; requires careful threshold tuning","Quality metrics are subjective; different stakeholders may have different standards"],"requires":["Quality threshold definitions in pipeline manifests","Human approval process (email, Slack, web UI)","Python 3.9+"],"input_types":["production artifacts (scripts, images, videos)","quality metrics","approval decisions"],"output_types":["quality reports","approval logs","rollback instructions"],"categories":["safety-moderation","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-calesthio--openmontage__cap_16","uri":"capability://image.visual.screen.recording.and.demo.video.generation","name":"screen recording and demo video generation","description":"Provides a pipeline for generating screen recording videos and software demo videos. The system can capture screen recordings, add narration and captions, highlight UI elements, and create polished demo videos. The agent can generate demo videos from descriptions of software features without requiring manual screen recording or editing.","intents":["Generate software demo videos from feature descriptions","Create screen recording tutorials without manual recording","Produce polished demo videos with narration and captions"],"best_for":["SaaS companies creating product demo videos","Software teams generating tutorial videos","Creators producing software review or how-to videos"],"limitations":["Screen recording requires actual software interaction; cannot be fully automated for complex workflows","UI element highlighting is manual or requires custom detection logic","Demo videos are limited to screen content; no camera or video overlays","Requires software to be installed and accessible for recording"],"requires":["Screen recording tool (FFmpeg, OBS, or browser automation)","API keys for TTS and image generation","Python 3.9+","Software to be recorded must be installed"],"input_types":["feature description","software interaction steps","narration script"],"output_types":["MP4 video file","screen recording with captions","UI element annotations"],"categories":["image-visual","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-calesthio--openmontage__cap_2","uri":"capability://tool.use.integration.dual.provider.capability.selection.with.scoring","name":"dual-provider capability selection with scoring","description":"Implements a provider selector pattern where every video generation, image generation, and audio capability supports both high-end cloud APIs (OpenAI, Anthropic, ElevenLabs, Runway) and local/open-source alternatives (Stable Diffusion, Ollama, FFmpeg). The system scores available providers based on cost, latency, quality, and GPU availability, then selects the best match for the current task. This allows users to start with free local models and upgrade to premium APIs without code changes.","intents":["Use free, local models for development and testing, then switch to premium APIs for production","Automatically select the best provider based on cost, speed, and quality constraints","Avoid vendor lock-in by supporting multiple providers for the same capability"],"best_for":["Developers prototyping with limited budgets who want to upgrade to premium APIs later","Teams with GPU infrastructure wanting to use local models for cost savings","Organizations avoiding vendor lock-in through multi-provider support"],"limitations":["Quality and speed vary significantly between providers — local models may produce lower-quality outputs","Requires provider-specific API keys or local GPU setup for each provider","Provider scoring logic is heuristic-based; optimal selection may require manual tuning per use case","Local models require 8GB+ VRAM; cloud APIs have rate limits"],"requires":["API keys for cloud providers (OpenAI, Anthropic, ElevenLabs, Runway) OR local GPU with 8GB+ VRAM","Provider configuration in .env file","Python 3.9+ with provider-specific SDKs installed"],"input_types":["task parameters (quality target, latency budget, cost limit)","provider availability status","GPU resource metrics"],"output_types":["selected provider name","provider-specific API calls","cost and latency estimates"],"categories":["tool-use-integration","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-calesthio--openmontage__cap_3","uri":"capability://planning.reasoning.skill.based.agent.instruction.system","name":"skill-based agent instruction system","description":"Provides specialized instruction sets ('skills') that teach the agent how to execute specific production tasks (e.g., 'Cinematic Rendering', 'Talking Head Generation', 'Podcast Repurposing'). Skills are organized into Core Skills (foundational operations), Creative Skills (style and composition), and Meta Skills (governance and quality). Each skill contains detailed prompts, examples, and decision trees that guide the agent through complex multi-step processes without requiring the agent to invent the approach.","intents":["Give the agent detailed instructions for complex production tasks without hardcoding logic","Ensure consistent quality and approach across different production types","Enable non-technical users to leverage the agent's capabilities through skill-based guidance"],"best_for":["Teams wanting to standardize production approaches across multiple agents","Builders creating custom production workflows without modifying core code","Organizations training agents on domain-specific video production knowledge"],"limitations":["Skills are text-based instructions; quality depends on LLM's ability to follow complex prompts","No automatic skill selection — agent must choose the right skill for the task","Skills require manual updates when production requirements change"],"requires":["Skill definition files in skills/ directory","LLM with sufficient context window to load skill instructions (4K+ tokens)","Python 3.9+"],"input_types":["skill instruction files (markdown/text)","task parameters","production context"],"output_types":["agent-executed tool calls","skill-guided decisions","production artifacts"],"categories":["planning-reasoning","text-generation-language"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-calesthio--openmontage__cap_4","uri":"capability://image.visual.multi.format.video.composition.with.remotion","name":"multi-format video composition with remotion","description":"Provides a Remotion-based composition engine that generates videos from declarative JSON scene definitions. The system includes pre-built Remotion components for explainers, cinematic renders, talking heads, and animated sequences. The agent can generate or modify Remotion composition JSON, which is then rendered via the Remotion CLI to produce final video output. This enables programmatic video generation without manual editing.","intents":["Generate videos from JSON scene definitions without manual video editing","Create explainer videos, cinematic sequences, and talking head videos programmatically","Render videos in multiple formats and resolutions from a single composition definition"],"best_for":["Developers building automated video generation pipelines","Teams producing explainer videos, product demos, and cinematic content at scale","Builders wanting programmatic control over video composition and timing"],"limitations":["Remotion rendering is CPU-intensive; 1080p 30fps videos take 5-30 minutes depending on complexity","Requires Node.js 18+ and Remotion CLI; adds ~500MB dependency footprint","Complex animations require understanding Remotion's React-based composition model","Limited to Remotion's built-in components; custom effects require JavaScript/React knowledge"],"requires":["Node.js 18+","Remotion CLI installed globally or in project","FFmpeg for video encoding","8GB+ RAM for rendering"],"input_types":["JSON scene definitions","Remotion component props","media assets (images, audio, video clips)"],"output_types":["MP4 video files","WebM video files","frame sequences"],"categories":["image-visual","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-calesthio--openmontage__cap_5","uri":"capability://tool.use.integration.text.to.speech.with.voice.cloning.and.localization","name":"text-to-speech with voice cloning and localization","description":"Provides multi-provider TTS capabilities supporting both cloud APIs (ElevenLabs, OpenAI, Google Cloud) and local alternatives (Ollama, Coqui). Supports voice cloning for consistent narrator voices across videos, automatic language detection and translation for localization, and voice profile management. The system can generate speech in 50+ languages and apply voice effects (speed, pitch, emotion) without re-recording.","intents":["Generate narration for videos with consistent voice across multiple languages","Clone a specific voice for branded video content","Automatically localize videos to multiple languages with native-speaker voices"],"best_for":["Content creators producing videos in multiple languages","Teams building branded video content with consistent narrator voices","Organizations localizing educational or marketing videos globally"],"limitations":["Voice cloning quality depends on source audio quality; requires 30+ seconds of clean audio","ElevenLabs voice cloning is premium feature; free tier limited to 10K characters/month","Local TTS (Coqui) has lower quality than cloud providers; requires GPU for reasonable speed","Emotion and prosody control varies by provider; not all providers support advanced voice effects"],"requires":["API key for cloud TTS provider (ElevenLabs, OpenAI, Google Cloud) OR local GPU with 4GB+ VRAM","Python 3.9+ with provider SDKs","FFmpeg for audio processing"],"input_types":["text scripts","language codes","voice profile definitions","audio files for voice cloning"],"output_types":["MP3/WAV audio files","audio metadata (duration, sample rate)","voice profile configurations"],"categories":["tool-use-integration","text-generation-language"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-calesthio--openmontage__cap_6","uri":"capability://image.visual.image.generation.with.style.playbooks.and.cinematography.framework","name":"image generation with style playbooks and cinematography framework","description":"Provides image generation capabilities (Flux, Stable Diffusion, DALL-E) with a built-in style system and cinematography framework. The system includes pre-defined style playbooks (cinematic, documentary, animated, etc.) and a shot prompt builder that generates detailed image prompts based on cinematography principles (framing, lighting, composition). The agent can apply consistent visual styles across multiple images without manually crafting detailed prompts.","intents":["Generate images with consistent visual style across a video production","Create cinematic shots using cinematography principles without manual prompt engineering","Apply pre-defined style playbooks to ensure visual cohesion"],"best_for":["Video producers needing consistent visual style across multiple shots","Teams building cinematic or documentary-style content","Builders wanting to automate image generation with cinematography-aware prompts"],"limitations":["Style playbooks are predefined; custom styles require manual prompt engineering","Cinematography framework generates prompts but doesn't guarantee cinematically correct output","Image quality varies significantly between providers (Flux > DALL-E > Stable Diffusion)","Generating 100+ images for a full video production can cost $50-500 depending on provider"],"requires":["API key for image generation provider (OpenAI, Anthropic, Replicate) OR local GPU with 8GB+ VRAM","Python 3.9+","Style playbook definitions in YAML"],"input_types":["text descriptions","style playbook names","cinematography parameters (shot type, lighting, framing)"],"output_types":["PNG/JPEG image files","image metadata (resolution, generation time, cost)","prompt logs for reproducibility"],"categories":["image-visual","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-calesthio--openmontage__cap_7","uri":"capability://data.processing.analysis.cost.tracking.and.budget.management","name":"cost tracking and budget management","description":"Tracks API costs across all provider calls (OpenAI, Anthropic, ElevenLabs, Runway, etc.) in real-time and enforces budget limits per pipeline or per production. The system logs cost per tool execution, aggregates costs by provider and pipeline stage, and can halt expensive operations if budget is exceeded. Provides cost estimates before executing expensive operations (e.g., video generation) to enable informed decision-making.","intents":["Monitor and control API spending across multiple providers","Get cost estimates before executing expensive operations","Set budget limits per production to prevent runaway costs"],"best_for":["Teams with limited budgets wanting to control API spending","Developers prototyping with free/cheap models before upgrading to premium","Organizations tracking production costs for billing or ROI analysis"],"limitations":["Cost tracking is approximate; actual costs may vary based on provider pricing changes","Budget enforcement is soft (warnings) not hard (blocking) — requires agent cooperation","Some providers (local models) have zero API cost but high GPU cost; not tracked","Cost estimates are based on historical data; actual costs depend on model performance"],"requires":["API keys with cost tracking enabled for all providers","Python 3.9+","Cost configuration in .env file"],"input_types":["tool execution logs","provider API responses","budget limits"],"output_types":["cost reports (per tool, per pipeline, per production)","budget alerts","cost estimates"],"categories":["data-processing-analysis","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-calesthio--openmontage__cap_8","uri":"capability://automation.workflow.checkpoint.based.state.persistence.and.recovery","name":"checkpoint-based state persistence and recovery","description":"Implements a checkpoint system that saves the state of each pipeline stage to JSON files, enabling resumption of interrupted productions without re-executing completed stages. Each checkpoint includes stage outputs, tool execution logs, and metadata (timestamp, cost, quality metrics). If a pipeline fails mid-execution, the agent can resume from the last checkpoint, skipping already-completed stages and re-executing only the failed stage.","intents":["Resume interrupted video productions without losing progress","Avoid re-executing expensive operations (image generation, video rendering) after failures","Maintain audit trail of production decisions and outputs"],"best_for":["Teams producing long-running videos with expensive operations","Developers debugging pipeline failures without re-running entire workflows","Organizations needing audit trails and reproducibility"],"limitations":["Checkpoint system adds ~50-100ms per stage transition for state serialization","Requires persistent storage (local filesystem or cloud storage); not suitable for ephemeral environments","Checkpoint recovery assumes tool outputs are deterministic; non-deterministic tools may produce different results on resume","Checkpoints can grow large (100MB+) for productions with many assets"],"requires":["Writable filesystem or cloud storage (S3, GCS) for checkpoint files","Python 3.9+","JSON serialization support for all tool outputs"],"input_types":["stage execution results","tool outputs","metadata (cost, quality, timestamp)"],"output_types":["checkpoint JSON files","recovery instructions","audit logs"],"categories":["automation-workflow","memory-knowledge"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"github-calesthio--openmontage__cap_9","uri":"capability://image.visual.animated.explainer.video.generation.pipeline","name":"animated explainer video generation pipeline","description":"Provides an end-to-end pipeline for generating animated explainer videos from text descriptions. The pipeline includes script generation, scene breakdown, image generation for each scene, text-to-speech narration, and Remotion-based composition. The agent follows the Animated Explainer skill to create visually coherent, well-paced explainer videos with synchronized narration and animations.","intents":["Generate animated explainer videos from text descriptions without manual animation","Create product demos, educational content, or marketing videos programmatically","Produce videos with synchronized narration, visuals, and animations"],"best_for":["SaaS companies creating product demo videos","Educational content creators producing course videos","Marketing teams generating explainer videos at scale"],"limitations":["Animation quality depends on image generation and Remotion composition; complex animations may look simplistic","Typical explainer video (2-3 minutes) costs $20-50 in API calls and takes 15-30 minutes to generate","Scene breakdown is automated but may not match human-designed storyboards","Requires careful prompt engineering to ensure visual coherence across scenes"],"requires":["API keys for image generation (Flux, DALL-E) and TTS (ElevenLabs, OpenAI)","Node.js 18+ for Remotion rendering","Python 3.9+","8GB+ RAM"],"input_types":["text description of topic","style preferences","target duration"],"output_types":["MP4 video file","script","scene breakdown","asset list"],"categories":["image-visual","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":49,"verified":false,"data_access_risk":"high","permissions":["Claude Code, Cursor, or Windsurf IDE with AI assistant enabled","Python 3.9+","YAML pipeline manifests in pipeline_defs/ directory","YAML pipeline manifest files in pipeline_defs/ directory","Checkpoint directory with write permissions","Python 3.9+ with PyYAML support","API key for avatar provider (D-ID, Synthesia, Runway) OR local avatar model","API key for TTS provider (ElevenLabs, OpenAI)","4GB+ RAM","API keys for image generation (Flux, DALL-E) and video generation (Runway, Synthesia)"],"failure_modes":["Requires IDE with integrated AI assistant support — not compatible with standalone CLI or API-only workflows","Agent decision quality depends on LLM capability and context window size","No built-in fallback if IDE connection drops mid-pipeline","Requires upfront YAML manifest design — not suitable for highly ad-hoc, one-off productions","Pipeline changes require manifest updates; no runtime pipeline modification","Checkpoint system adds ~50-100ms per stage transition for state serialization","Avatar quality varies by provider; some look uncanny or robotic","Lip-sync quality depends on provider; some providers have noticeable sync issues","Talking head videos are limited to head-and-shoulders framing; no full-body movement","Premium avatar providers (Synthesia, D-ID) cost $0.10-1.00 per minute of video","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.5704817622916789,"quality":0.5,"ecosystem":0.7000000000000001,"match_graph":0.25,"freshness":0.75,"weights":{"adoption":0.3,"quality":0.2,"ecosystem":0.15,"match_graph":0.3,"freshness":0.05}},"observed_outcomes":{"matches":0,"success_rate":0,"avg_confidence":0,"top_intents":[],"last_matched_at":null},"maintenance":{"status":"active","updated_at":"2026-05-24T12:16:21.549Z","last_scraped_at":"2026-05-03T13:59:47.981Z","last_commit":"2026-04-28T15:12:04Z"},"community":{"stars":3352,"forks":669,"weekly_downloads":null,"model_downloads":null,"model_likes":null}},"distribution":{"claim_url":"https://unfragile.ai/submit?claim=calesthio--openmontage","compare_url":"https://unfragile.ai/compare?artifact=calesthio--openmontage"}},"signature":"WRzO9cN2QoMcKm+p32Ov2t9im5TxXywTVFlMCL8kuScfD0ATD2yxjliBeRxvpII53IHLR5MxxqIECR17eVKTCw==","signedAt":"2026-06-20T08:36:11.550Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/calesthio--openmontage","artifact":"https://unfragile.ai/calesthio--openmontage","verify":"https://unfragile.ai/api/v1/verify?slug=calesthio--openmontage","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"}}