GoKawiilOpen-source project formalizes IRS tax forms as citable, machine-checkable data
A proof-of-concept project encodes US federal individual income tax forms and instructions as YAML files, each line tied to a citation of the archived IRS source page it was drawn from. A build process and a citations checker verify that every line, parameter and gate has a traceable citation, and the software uses this data to run a self-preparation interview that computes values without ever filing or transmitting return data. Much of the encoding was produced by language-model agents, but the authors say the structure lets anyone verify its citations independent of who wrote it.
GoKawiil's interpretation of the reporting above, not reported fact.
The project separates IRS procedural forms from the underlying tax code, suggesting a reusable, auditable layer that other tax tools could build on without re-deriving citations themselves. Its emphasis on machine-checkable sourcing could be a response to concerns about trusting AI-generated tax logic, though the authors acknowledge citations confirm only that a line points to a source page, not that it was interpreted correctly. The approach may offer a template for applying similar verifiable-citation structures to other complex regulatory domains.
- IRS forms are encoded as YAML with mandatory citations to archived source pages for every line.
- A build process and citation-checking tool verify 2,313 anchors and 1,252 quotes, flagging 305 under-verified locator segments.
- The software only computes a values sheet for self-filing and never transmits or files tax data itself.
Source: github.com, 2026-10-28
Published there as: “Show HN: A proof-of-concept formalization of the IRS federal tax forms”
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