Disclosure analysis
The game uses live AI while you play
The game integrates local SLMs for runtime generation of 3D models, text labels, and structured JSON output consumed by the game to generate maps and levels.
- Process
- AI-generated and AI-assisted
- Live AI during play
- Yes
Evidence & analysis details
- Evidence used
-
“Pinocchio and Hunyuan were used to generate 3D models of mushrooms”
“the integrated SLM model is used to generate text labels and summaries at runtime”
- Development workflow
- Code help Prototyping
- Model-reported confidence
- 98% A model estimate, not a measured accuracy rate or a human review score.
Auto-classified from the public disclosure. The raw disclosure below remains the source of truth. How classification works.
AI Usage Disclosure
Software engineering is primarily by hand in C# and python, with local SLM's, run via Ollama, and occasional cloud-based LLM's used to research knowledge deficits and prototype code snippets for specific systems that map to those deficits. Any AI-generated code was reviewed line-by-line, hand-integrated and heavily modified. The application requires local file access to files selected by the player from a standard operating system folder browser with permissions. It scans the user's system via the psutil and gputil standard python packages to ascertain the specifications of the user's system to select a model that will match their system's performance profile. Pinocchio and Hunyuan were used to generate 3D models of mushrooms from 19th century public domain botanical illustrations, and the integrated SLM model is used to generate text labels and summaries at runtime. The application has absolutely no chat interface. An SLM is integrated locally as a black-box system with robust system prompts to generate structured output in the form of JSON based on the player's file inputs. The JSON is consumed by the game to generate maps and levels. Additional Specifications & Technical Notes: - A localhost python server is back-compiled to a C executable and deployed with the main executable and invoked from its application domain to host the local model. - The local model is downloaded from the Internet via Ollama. - The end-user needs to have the Ollama client installed to run the model locally. - The python server has robust internal system prompts to prevent violation of the Terms of Service on the Steam and Itch platforms regarding disallowed content. - The python server is run from the main executable's application domain, in the same directory structure. - The python server and main executable communicate via a local socket connection via IANA-approved port numbers according to RFC 6335. Ports are tested and iterated to ensure that they are available on the local system. If an IANA-approved port listed in RFC 6335 is not available, the application will not run. Heaps adheres to the ARTS standard for AI labeling. A full accounting of our use of AI in this game can be found at: droidknot.com/ARTS/Heaps_SIS_082726.pdf
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This disclosure in context
How comparisons workCompare this developer’s disclosure with 25,376 non-mature Steam products in the index. These figures describe published disclosures, not all games on Steam or independently verified AI use.
- Writing or localization
- 27.2%
- 6,893 of 25,376 indexed disclosures mention this category.
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Source and record
- First indexed
- Oct 6, 2026
- Source last checked
- Oct 6, 2026
- Automatic analysis updated
- Oct 6, 2026
- Recorded text changes
- 0
The disclosure is the developer’s statement on Steam. Index dates show when we observed it, not when AI use began. History covers captured versions only. Automatic analysis can be wrong and is not a verification of the game’s content. Read the methodology.