name:
dream-loop
description:
Build high-fidelity visual targets and iteratively improve games/apps/scenes by comparing live renders against a target image. IMPERIAL governed adapter for achimala/dream-loop.
triggers:
dream-loop
game-visuals
3d
blender
image-gen
visual-critic
graphics
scene-iteration

Dream Loop — IMPERIAL bounded visual iteration capability

Upstream: achimala/dream-loop Pinned commit reviewed: 9bddb901f7d071cfefdd21e264267c757177a9df License: MIT Native prerequisites: image generation + vision; subagents are strongly preferred; Blender is optional for custom 3D modeling.

What upstream provides

Dream Loop creates a target screenshot for a game/app/scene, builds toward that target, compares a live screenshot to the target with a critic, and iterates. It is useful for game prototyping, 3D scenes, UI polish and visual regression/improvement loops.

IMPERIAL installation mode

Installed across the three IMPERIAL runtime nodes as a governed visual-production profile. The Val Town Deno nodes are not claimed to have native Blender, desktop rendering or built-in image-generation execution. Native visual iteration must be routed to a compatible authorized execution environment; these server nodes retain the skill contract, task routing, evidence and policy boundary.

IMPERIAL workflow

  1. Confirm target and permitted content.
  2. Reuse an existing screenshot when improving an existing product; otherwise create a bounded target image through an approved image-generation route.
  3. Store/identify the target deterministically and record its hash.
  4. Build one measurable visual increment at a time.
  5. Capture the current render/screenshot.
  6. Compare target vs current output using vision/critic capability.
  7. Record defects, priority, evidence and next change.
  8. Stop on acceptance criteria, quota guard, explicit time budget or lack of a compatible renderer.

FREE_ONLY / quota protection

  • Spend limit remains 0 USD.
  • Do not silently activate paid image-generation, Blender cloud render, asset marketplace or model API services.
  • Prefer existing ChatGPT image capability or verified free/local routes where allowed.
  • Apply NO-RECHECK: do not regenerate the target or re-run expensive visual critique without a state change.
  • Large iteration loops must have a bounded token/time budget; Astra MAX is not to be consumed for repetitive pixel iteration when a cheaper bounded worker can perform it.

Security / quality

  • Generated assets do not create ownership over third-party trademarks or copyrighted source assets.
  • Keep external assets/license provenance explicit.
  • Do not publish/deploy on behalf of the Architect unless the task has the necessary external authority.
  • For children's content, preserve the existing no-violence/educational policy when the task is in that domain.
  • Guardian Core, Approval Gateway, Audit Ledger, Zero Trust, AI Passport and Public/Private Boundary remain authoritative.

Truth boundaries

  • SKILL_BOUND != BLENDER_INSTALLED
  • SKILL_BOUND != IMAGE_GEN_RUNTIME_AVAILABLE
  • TARGET_RENDER != IMPLEMENTED_PRODUCT
  • VISUAL_SIMILARITY != FUNCTIONAL_CORRECTNESS
  • CRITIC_PASS != PRODUCTION_VERIFIED
  • CAPABILITY != PUBLICATION_AUTHORITY

Authorship of this IMPERIAL adapter: Alexander Romaskevich / RomaskevicH. Upstream project authorship remains with Anshu Chimala and upstream contributors under the MIT license.