Indexed October 6, 2026
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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 work

Compare 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.

Live AI during play
3.2%
792 of 24,946 disclosures with structured analysis.
Compare this group
Visual assets
76.4%
19,390 of 25,376 indexed disclosures mention this category.
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Writing or localization
27.2%
6,893 of 25,376 indexed disclosures mention this category.
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Code assistance
12.6%
3,205 of 25,376 indexed disclosures mention this category.
Compare this category

Categories can overlap. A disclosure may mention several types of AI use.

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.