Yes, the README explicitly covers ComfyUI migration and pinning the installer and commit, although the migrated graph’s node semantics and input compatibility still need validation in your workflow.

• scenario-workflow-authoring supports creating, editing, publishing, and migrating workflows from Weavy, ComfyUI, or other node editors.
• scenario-workflows supports discovery, input construction, dry-run pricing, and approval gates.
• The README says the default command fetches the latest skills from main; a reviewed state requires pinning both the CLI and the commit from a release tag.
• Non-interactive installation with -y is available for scripts or CI, but the README does not claim one-to-one migration for every ComfyUI node, control image, or custom model.

Yes, this is suitable because it turns Scenario capability discovery, input validation, execution, asynchronous waiting, downloading, and cost control into an agent-usable workflow.

• The “Scenario Agent Skills” section lists images, video, audio, textures, skyboxes, 3D assets, and custom-trained models.
• The scenario skill defines the core loop: “discover, schema, run, wait, display, download.”
• “Workflows and apps” explicitly supports dry-run pricing and approval gates before workflow execution.
• This is not a local model runner: the Scenario MCP server and OAuth or an API key are required. Actual prices, rate limits, and model availability remain controlled by Scenario.

Yes, the project supports distribution to more than 70 agents, installation by role or goal, and expert-tool families for Unreal, Unity, Godot, and Roblox Studio.

• The README says the skills CLI installs into “70+ agents,” including Copilot.
• “By role or goal” says INSTALL.md groups skills by job and outcome and provides one command for each group.
• The expert-tool section lists Unreal Engine, Unity, Godot, and Roblox Studio, with each family installable as a set.
• This avoids requiring every person to load every skill, but the README does not describe organization-level permissions, member assignment, shared caches, or cross-engine version governance.

It depends on satisfying two separate dependency chains: the cloud MCP path and the local application path. The project supports combining them, but it does not make Blender or Unity environment-free services.

• The README says Scenario skills work through the Scenario MCP, while expert tools drive locally installed ZBrush, Blender, Maya, Unreal, Unity, Godot, or Roblox Studio.
• Expert tools “need the application, not the Scenario MCP,” so local DCC/engine operations and cloud generation are separate runtime paths.
• Expert tools are installed by family, and each family README records its build source and verification scope.
• Modifying a Unity project still depends on software versions, plugins, project structure, permissions, and scripts; cross-project compatibility is not promised.

Yes, because the README extends beyond video generation into delivery-oriented steps such as editing, color grading, music videos, UGC, captions, and ad variants.

• The skill list includes scenario-video, scenario-video-editing, scenario-video-color-grade, scenario-ugc, scenario-caption-studio, and scenario-video-ads.
• It also includes scenario-video-assembly, scenario-ad-variants, and scenario-thumbnails for assembly, variants, and thumbnail production.
• The README says the agent can execute tasks through Scenario MCP, wait for asynchronous results, and download outputs, enabling multi-step workflows.
• However, it does not provide caption-accuracy, audio-sync, advertising-platform export, or maximum long-video duration specifications.

Yes, because the project turns consistency into reusable workflows involving identity libraries, reference images, control images, and custom models rather than relying only on rewriting prompts each time.

• The README skill list includes scenario-consistency, scenario-identity-library, and scenario-model-training.
• The project insights explicitly mention baseline-plus-delta prompting, reference images, control images, and reusable character and prop identity libraries.
• Scenario skills cover images, video, and custom-trained models, allowing consistency methods to span multiple media workflows.
• The README does not promise perfect consistency across different models; the underlying model, source assets, training data, and provider limitations still affect results.