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docs: revisit AI/LLM policy in CONTRIBUTING.md

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This summarizes the latest state all relevant parties have agreed on
in the last meeting.

This commit was rephrased and improved with the help of Claude Code
using the Sonnet 4.6 model.

Signed-off-by: Philipp Schuster <philipp.schuster@cyberus-technology.de>
On-behalf-of: SAP philipp.schuster@sap.com
This commit is contained in:
Philipp Schuster
2026-03-24 18:40:42 +01:00
committed by Bo Chen
parent 81495241eb
commit 00b3a48900
1 changed files with 44 additions and 7 deletions
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CONTRIBUTING.md
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@@ -164,12 +164,49 @@ Signed-off-by: Sebastien Boeuf <sebastien.boeuf@intel.com>
Then, after the corresponding PR is merged, GitHub will automatically close that issue when parsing the
[commit message](https://help.github.com/articles/closing-issues-via-commit-messages/).
## AI Generated Code
## AI/LLM Assistance & Generated Code
Our policy is to decline any contributions known to contain contents
generated or derived from using Large Language Models (LLMs). This
includes ChatGPT, Gemini, Claude, Copilot and similar tools.
We recommend **a careful and conservative approach** to LLM usage, guided by
sound engineering judgment. Please use AI/LLM-assisted tooling thoughtfully and
responsibly to ensure efficient use of limited project resources, particularly
in code review and long-term maintenance. Our primary goals are to avoid
ambiguity in license compliance and to keep contributions clear and easy to
review.
The goal is to avoid ambiguity in license compliance and optimize the
use of limited project resources, especially for code review and
maintenance. This policy can be revisited as LLMs evolve and mature.
Or in other words: please apply common sense and don't blindly accept LLM
suggestions.
This policy can be revisited as LLMs evolve and mature.
### Code Review
We generally recommend doing early coarse-grained reviews using state-of-the-art
LLMs. This can help identify rough edges, copy & paste errors, and typos early
on. This reduces review cycles for human reviewers.
Please **do not** use GitHub Copilot directly in PRs to keep discussions clean.
Instead, ask an LLM of your choice for a review. A convenient way to do this is
- appending `.patch` to the GitHub PR URL
(e.g., `https://github.com/cloud-hypervisor/cloud-hypervisor/pull/1234.patch`)
and pasting it into the LLM of your choice, or
- using a local agent in your terminal, such as `codex` or `claude`.
### Contributions assisted by LLMs
All contributions **must** be submitted by a human contributor. Automated or
bot-driven PRs are not accepted.
You are responsible for every piece of code you submit, and you must understand
both the design and the implementation details. LLMs are useful for prototyping
and generating boilerplate code. However, large or complex logic must be
authored and fully understood by the contributor - LLM output should not be
submitted without careful review and comprehension.
Please disclose LLM use in your commit message and PR description if it
meaningfully contributed to the submitted code. Again, we recommend careful and
conservative use of LLMs, guided by common sense.
Maintainers reserve the right to request additional clarification or decline
contributions where LLM usage raises concerns. Ultimately, acceptance of any
contribution is at the maintainers' discretion.