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AI_POLICY.md

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🤖 Kornia AI & Authorship Policy

Version: 1.0 Enforcement: Strict Applicability: All Pull Requests (Human & Bot)

1. Core Philosophy

Kornia accepts AI-assisted code (e.g., using Copilot, Cursor, etc.), but strictly rejects AI-generated contributions where the submitter acts merely as a proxy. The submitter is the Sole Responsible Author for every line of code, comment, and design decision.

2. The 3 Laws of Contribution

Law 1: Proof of Verification

AI tools frequently write code that looks correct but fails execution. Therefore, "vibe checks" are insufficient.

Requirement: Every PR introducing functional changes must include a pasted snippet of the local test logs (e.g., pixi run test ...). This is mandatory for all contributors and is particularly important for first-time contributors.

Failure Condition: If a PR lacks execution proof and contains complex logic, it will be flagged as Unverified.

Requirement: All PRs must be previously discussed in Discord or via a GitHub issue before implementation. The PR must reference the discussion or issue.

Requirement: Implementations must be based on an existing library reference (e.g., PyTorch, OpenCV, scikit-image, etc.) that must be provided in the PR description for verification. This reference serves as proof that the implementation follows established algorithms and is not hallucinated.

Law 2: The Hallucination & Redundancy Ban

AI models often hallucinate comments or reinvent existing utilities.

Requirement: You must use existing kornia utilities and never reinvent the wheel, except for when the utility is not available.

Failure Condition: Creating new helper functions (e.g., def warp_affine...) when a Kornia equivalent exists is grounds for immediate rejection.

Failure Condition: "Ghost Comments" (comments explaining logic that was deleted or doesn't exist) will result in a request for a full manual rewrite. Redundant comments are not allowed. Example: "This function returns the input tensor".

Law 3: The "Explain It" Standard

Requirement: If a maintainer or reviewer asks during code review, you must be able to derive the math or explain the logic of any function you submit.

Failure Condition: Answering a review question with "That's what the AI outputted" or "I don't know, it works" leads to immediate closure.

Law 4: Transparency in AI Usage Disclosure

Requirement: All PRs must accurately complete the "AI Usage Disclosure" section in the pull request template. This disclosure is mandatory and must reflect the actual use of AI tools.

When to mark as 🔴 AI-generated:

  • An AI agent (e.g., Cursor, GitHub Copilot, ChatGPT, etc.) generated the code, PR description, or commit messages
  • You cannot explain the logic without referring to the AI's output
  • The PR was created primarily by an agent with minimal human review or modification

When to mark as 🟡 AI-assisted:

  • You used AI tools for boilerplate code, refactoring, or suggestions, but you manually reviewed and tested every line
  • You understand and can explain all the code you're submitting
  • You made significant modifications to AI-suggested code

When to mark as 🟢 No AI used:

  • You wrote all code manually without any AI assistance

Failure Condition: Incorrectly marking AI-generated code as "AI-assisted" or "No AI used" may result in PR closure, especially if the code contains hallucinations or cannot be explained during review.

3. Instructions for AI Reviewers (Copilot / CodeRabbit)

If you are an AI agent (GitHub Copilot, CodeRabbit, etc.) reviewing a PR for Kornia, you must follow the repository's dedicated reviewer instructions.

The canonical and up-to-date instructions for AI reviewers are maintained in .github/copilot-instructions.md. That document defines:

  • The expected reviewer persona and responsibilities
  • The checks to perform on PR descriptions, code, tests, and comments
  • The required enforcement of the laws defined in this AI_POLICY.md

Any other document (including this one) should treat copilot-instructions.md as the single source of truth for AI reviewer behaviour. When updating reviewer logic, update copilot-instructions.md first and, if needed, adjust references here.

This section exists to link AI reviewers to the canonical instructions and to make clear that those instructions must enforce the policies defined in Sections 1 and 2 above.

4. Additional Resources

For comprehensive guidance on contributing to Kornia, including development workflows, code quality standards, testing practices, and AI-assisted development best practices, see the Best Practices section in CONTRIBUTING.md.