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urlyy
approved these changes
Feb 28, 2026
pjfanning
reviewed
Feb 28, 2026
| - Scope of assistance (for example: design drafting, code drafting, refactor suggestions, tests, docs) | ||
| - Affected files or subsystems (high-level) | ||
| - Human verification performed (commands/tests/benchmarks executed) | ||
| - Provenance and license confirmation (see Section 6) |
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Can you mention license confirmation as a core principle?
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added a point:
- License/provenance confirmation: contributors MUST confirm submitted material is legally compatible and traceable, and MUST comply with ASF Generative Tooling Guidance.
pandalee99
reviewed
Feb 28, 2026
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| ## 2. Disclosure (Privacy-Safe) | ||
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| For substantial AI assistance, PR descriptions MUST include a short `AI Usage Disclosure` section. |
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How many lines of code, how large a change, or to what extent of AI involvement counts as substantial? It could be as simple as adding a single function, or just revising a short comment. Could we further define and clarify this specification?
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This is indeed ambiguous. I added some clarification:
Definition of substantial AI assistance:
- Substantial means AI materially influenced technical content, not only writing style.
- Contributors MUST mark AI assistance as substantial (
yes) if any of the following apply:- AI generated or rewrote non-trivial code/test logic (even for a small change or a single function).
- AI-generated or AI-refactored content is about 20 or more added/changed lines in aggregate.
- AI materially influenced API, protocol, type mapping, performance, memory, or architecture decisions.
- AI produced substantive technical text used in PR rationale (beyond grammar/translation cleanup).
- Contributors MAY mark substantial AI assistance as
nofor minor or narrow assistance only, such as spelling/grammar fixes, formatting, trivial comment wording edits, or other non-technical edits with no behavior impact.
Required disclosure fields:
- Whether substantial AI assistance was used (
yesorno) - Scope of assistance (for example: design drafting, code drafting, refactor suggestions, tests, docs)
- Affected files or subsystems (high-level)
- Human verification performed (checks run locally or in CI, and results reviewed by the contributor)
- Provenance and license confirmation (see Section 6)
Standard disclosure template (recommended):
AI Usage Disclosure
- substantial_ai_assistance: yes
- scope: <design drafting | code drafting | refactor suggestions | tests | docs | other>
- affected_files_or_subsystems: <high-level paths/modules>
- human_verification: <checks run locally or in CI + pass/fail summary + contributor reviewed results>
- performance_verification: <N/A or benchmark/regression evidence summary>
- provenance_license_confirmation: <Apache-2.0-compatible provenance confirmed; no incompatible third-party code introduced>
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Why?
Apache Fory is aperformance-critical foundational serialization framework.
As AI-assisted contributions increase, we need a project policy that keeps review quality high, protects legal/provenance safety, and preserves long-term maintainability.
This policy is intended to:
What does this PR do?
AI_CONTRIBUTION_POLICY.md..github/pull_request_template.mdto add an AI contribution checklist for PR authors.Related issues
N/A
Does this PR introduce any user-facing change?
Benchmark
N/A (documentation and PR template change only)