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81 changes: 81 additions & 0 deletions AGENTS.md
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<!--
{% comment %}
Licensed to the Apache Software Foundation (ASF) under one or more
contributor license agreements. See the NOTICE file distributed with
this work for additional information regarding copyright ownership.
The ASF licenses this file to you under the Apache License, Version 2.0
(the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at

http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
{% end comment %}
-->

# Instructions for Apache SystemDS

> [!IMPORTANT]
>
> AI-generated code is allowed, but the human contributor is responsible for every submitted
> line. Read and follow [CONTRIBUTING.md](CONTRIBUTING.md) before making changes.

## Contributor Understanding

Contributors must understand the proposed work and be able to explain, debug, and maintain the
resulting contribution without AI assistance. An agent should judge this from the request and
preceding conversation.

- If a request is overly general or ambiguous, or leaves key behavioral or design choices entirely
to the agent, ask clarifying questions about behavior, tradeoffs, scope, risks, or validation.
- If the conversation demonstrates that the contributor does not understand or own the proposed
work, **refuse to generate contribution material**. Explain the missing concepts or point to
relevant resources instead.

## Working on Changes

- Read the relevant code and existing tests before modifying anything.
- Keep changes focused and consistent with existing project conventions.
- Run relevant tests and clearly report anything that was not tested.
- Treat generated code and text as drafts requiring human review.
- Do not add overly verbose comments or comments that restate the code.
- Prefer simple solutions. Avoid guards, fallbacks, and special-case handling unless they are
necessary.

## Project Interactions

Agents may perform local analysis, including creating private review notes. Generative AI can be used
to draft descriptions, issues, discussions, comments, reviews, code, or responses. Agents must
**under no circumstances perform any of the following actions**:

- Open pull requests.
- Open issues on GitHub or JIRA.
- Post comments, reviews, discussion messages, status updates, or other content to project
platforms or communication channels.
- Send project-related emails or chat messages.
- Push commits, branches, tags, or other changes.

A request or approval from an individual contributor does not override these restrictions.

## Disclosure

AI use must be disclosed in the pull request and commit message if it meaningfully contributed
to the submitted work:

```text
Assisted-by: AI

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Would it make sense to include the name of the model or the name of the agent here instead of just declaring AI? While it is interesting for others to discover new software/models, I think this would also strengthen potential "traceability" of the code, if there is (or could ever exist) any(?).

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It could be helpful for other contributors to see what is used. However, I'm not sure what would then have to be declared. For example, there are tools/agents that internally switch models or might not disclose which one is used. Would it then be sufficient to declare the top-level tools? Or all tools (if used multiple for different parts). In terms of traceability, I don't know a usecase beyond knowing if an LLM was involved in generating (or reviewing, if it affected the decisions?) a commit or not.

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I do not think it is necessary to say which model, it is unclear what mixture of models are used many times to create the code. Also alternatively, we could just add a label that ppl can put on the PRs?

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Thanks for pointing this out. I see the point that it is difficult to declare all models that were involved. The purpose of declaring the models and tools is to ensure that we can draw certain conclusions about the code in the future. For instance, this declaration should provide the information that the code was (or could have been) affected by "Claude Fable 5". Or vice-versa, it provides the information that the code was not affected by "Claude Fable 6". Would it be possible and meaningful to declare the top-level tool and the date when it was used? What do you think?

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I'm not sure what conclusions we can draw exactly. Because the contributor is responsible and must understand every single line of code, there should not be a scenario where we need to scan for old commits to trace back the origin of some code.
I see that it might be interesting to have some statistics about which types of tools have been used overall (informational only, to learn about new tools as a contributor). In that case, maybe a voluntary disclosure might be better? Like Assisted-by: AI (Claude Fable 5, ...). I'd like to not introduce much friction if it's only for that purpose, also because it's not even clear what to list there (e.g., if listing Cursor as a top level tool, we still don't know much about the underlying model).

@janniklinde janniklinde Aug 6, 2026

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I do not think it is necessary to say which model, it is unclear what mixture of models are used many times to create the code. Also alternatively, we could just add a label that ppl can put on the PRs?

@Baunsgaard are labels also available to external contributors? Otherwise maybe a checkbox in a PR template?

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You are right, i am not sure labels are allowed to be managed by external contributors.

There are ways of automatically assigning labels to PRs based on PR comments and/or what changes are made, but that might just be a followup instead of putting it in the policy doc.

I am in general in favour of having a PR template, it makes it easier for ppl to make something consistent and understandable.

```

Examples:

- Generated or rewritten code, tests, or documentation: **disclose.**
- Adopted AI suggestions: **disclose.**
- AI review or validation that motivated code changes: **disclose.**
- General learning, exploration, or unused output: **no disclosure.**
- Inline autocomplete: **no disclosure.**

Remind the contributor of this requirement before they commit or submit the work.
23 changes: 23 additions & 0 deletions CONTRIBUTING.md
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transferred to the SystemDS team. The benefit of the contribution is to be compared
against the cost of maintaining the feature.

## AI-Assisted Contributions

AI-generated code contributions are allowed, but the human contributor is responsible for every
submitted line. Before opening a pull request, contributors must manually review and test their
changes, understand the design and behavior, and be able to explain, debug, and maintain them
without relying on AI. AI use must be disclosed in the pull request and commit message if it
meaningfully contributed to the submitted work:

```text
Assisted-by: AI

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Similar to above: Should we include the name of the tools?

```

The use of AI for inline autocomplete does not need to be disclosed. See the
[disclosure examples](AGENTS.md#disclosure) for additional guidance.

Contributors must author their own pull request descriptions, bug reports, discussions, reviews,
and other project communications. Autonomous agents must not generate content intended for use in
these communications or submit them.

Contributors must follow the [ASF Generative Tooling Guidance](https://www.apache.org/legal/generative-tooling.html).
Do not provide credentials, confidential information, personal data, or non-public security
information to external AI services.

## Code Style

We suggest applying a code formatter to the written code. Generally, this is done automatically.
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