Do these 3 things before closing this tab:
1Clear out junk files and repair common Windows errors2Scan for outdated or missing drivers - takes under a minute3Repair Windows errors before they cause bigger problemsDisclose included AI-generated material, not merely the fact that you used an AI tool. Flathub requires submitters to identify any AI-generated code, documentation, packaging, or other material they know or reasonably believe is included in the application or its Flathub packaging, and to describe the affected parts and approximate extent. The policy does not provide a special listing field or a mandatory sentence, so placement and wording require careful judgment.
This guide explains how to audit a project, write a defensible disclosure, keep prohibited AI content out of manifests, and separate AI-policy compliance from ordinary MetaInfo quality work. Flathub’s requirements can change; check the live requirements before submitting.
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What Flathub requires you to disclose
Flathub’s Requirements page states: “Submitters must disclose any AI-generated code, documentation, packaging, or other material they know or reasonably believe is included in the application or its Flathub packaging.” The trigger is the presence of generated material in the app or in the packaging submitted to Flathub, not the mere use of an AI service during development.
Your disclosure should identify three things:
- The material: code, documentation, artwork, translations, build files, scripts, metadata, or another included deliverable.
- The affected part: a module, directory, feature, document, build step, runtime asset, or other identifiable area.
- The approximate extent: for example, a named file, a percentage of a module, a number of generated screens, or “the initial version of the user guide.”
These are the policy’s information requirements. Flathub does not publish a required percentage formula, disclosure template, or fixed vocabulary for estimating extent. Use a description that a reviewer can understand and verify from the submitted source.
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What counts as included material
Count material that ships in the application or is part of its Flathub packaging. Examples include source code compiled into the app, bundled documentation, user-facing help, localization files, icons or other artwork, build scripts, patches, dependency instructions, and files used by the Flathub build.
If an AI-generated draft was discarded and no portion remains in the app or packaging, it is not included material. If a draft was substantially rewritten but identifiable generated passages, code, or assets remain, treat the remaining portion as included and describe the part that survived.
Generated versus assisted work
Keep an audit trail that distinguishes an AI-produced deliverable from ordinary human editing. A person who asks an AI system for suggestions and writes the final text independently may have no generated material to disclose. By contrast, pasted code, generated paragraphs, generated translations, or generated packaging files that remain in the submission are included deliverables.
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When the boundary is unclear, describe what remains rather than claiming that the entire project was generated. A precise statement such as “AI-generated error-message text remains in four user-interface files; the surrounding code was written and reviewed by the maintainers” is more useful than a broad claim that the app is “AI-assisted.”
Four boundaries that change the answer
| Situation | What to do | Why |
|---|---|---|
| AI-generated code, documentation, assets, or packaging is included in the app or Flathub packaging | Disclose the affected parts and approximate extent. | This is the policy’s stated disclosure trigger. |
| AI used only for research, discussion, or debugging, with no generated material included | No disclosure is required under this rule. | Tool use alone is not the trigger when no generated deliverable remains in the app or packaging. |
| AI-generated or AI-assisted content appears in a Flathub manifest | Remove and replace it with human-produced content; do not rely on a disclosure. | Disclosure does not create an exception to the manifest prohibition. |
| An AI agent opens or automates a submission pull request or writes related submission communications | Do not use the agent for those actions. Have a human prepare and send them. | Flathub prohibits agents from opening or automating submission pull requests and from generating related commit messages, descriptions, review comments, or replies. |
AI use that does not normally require a disclosure
Flathub’s policy expressly distinguishes research, discussion, and debugging from included generated material. You can use an AI system to explain an error, suggest questions to investigate, compare documentation, or discuss an implementation when none of the generated output is placed in the application or its Flathub packaging.
That exception is conditional. If a debugging answer becomes a pasted code block, if a research response becomes bundled documentation, or if a generated command is copied into a build script, the resulting file is now included material. Recheck the project after development rather than relying on how the tool was originally used.
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Examples of non-disclosable assistance
- You ask for possible causes of a compiler error, then fix the issue yourself and commit only your own code.
- You use an AI conversation to brainstorm feature names, but none of its wording appears in the app, help files, or metadata.
- You ask for a summary of a protocol while reading the primary documentation and write the implementation and documentation independently.
Examples that become disclosable
- You paste generated function bodies into the source tree and retain them after review.
- You include generated release notes, help text, translations, or accessibility labels in the installed app.
- You use generated build instructions or packaging scripts in the files submitted to Flathub.
Keep AI-generated content out of the manifest
The disclosure rule and the manifest rule are separate. Flathub does not permit AI-generated or AI-assisted content in its manifests. A disclosure cannot legalize such content.
Before submission, inspect every manifest and related build-definition file that will be reviewed. Replace generated descriptions, comments, commands, variable names, and other AI-assisted material with content written and checked by the maintainers. Do not assume that a generated comment is harmless simply because it does not affect compilation; the prohibition applies to content in the manifest, not only executable lines.
A practical manifest check
- List the manifest files and any included snippets, scripts, patches, or metadata they reference.
- Compare each file with the version maintained by your project, not only the final rendered build.
- Mark text or commands that originated from an AI tool, including content later lightly edited by a person.
- Rewrite or remove those portions and have a maintainer review the result.
- Record the review so you can explain how the manifest was produced if a reviewer asks.
Generated material elsewhere in the app may still require disclosure after the manifest has been cleaned.
How to audit your app before writing the disclosure
- Freeze the submission candidate. Use the exact commit, branch, source archive, and packaging files you intend to submit. Auditing an earlier working copy can miss generated material added later.
- Inventory included outputs. Review source, bundled assets, translations, help, license notices, build scripts, patches, tests shipped in the package, and Flathub packaging.
- Search your development records. Check commits, pull requests, editor history, and team notes for files created by an AI tool. Do not publish private prompts or unrelated conversation logs; use them to identify affected files.
- Classify each item. Label it human-written, AI-generated and retained, AI-assisted with retained generated portions, or AI-used only for research, discussion, or debugging.
- Resolve uncertainty. If you know or reasonably believe a generated portion remains, include it in the disclosure. If you cannot identify an exact line count, use a defensible file- or component-level estimate.
- Audit manifests separately. Remove AI-generated and AI-assisted material from manifests even when the same work is disclosed elsewhere.
- Prepare an extent estimate. Count files, modules, screens, paragraphs, or another meaningful unit. State that the figure is approximate when it is not exact.
How to write a defensible disclosure
Use plain language and name the affected area. The following examples are editorial wording, not official Flathub templates:
- Code: “AI-generated code is included in the import wizard under
src/import/, covering approximately three of twelve source files. Maintainers reviewed and modified the code before submission.” - Documentation: “The installation and troubleshooting sections of the bundled user guide were generated with an AI tool and then edited by maintainers; together they comprise approximately four of the guide’s sixteen sections.”
- Packaging: “The packaging helper used to assemble the optional language data was AI-generated and remains in
packaging/l10n.sh. The manifest itself was written and reviewed by maintainers.” - Mixed material: “AI-generated interface text appears in the onboarding and export dialogs, approximately 40 strings across two translation files. No AI-generated content is included in the Flathub manifest.”
Do not describe the whole app as “made by AI” when only one component contains generated material. Conversely, do not say “AI-assisted” without naming the files or components if generated output remains. A reviewer needs enough information to understand scope and assess maintainability.
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There is no published minimum word count or percentage threshold. A useful disclosure lets a reviewer map your statement to the source. Prefer “the parser’s error messages in src/parser/errors.rs, about 25 of 180 lines” to “some code.” Prefer “the first two chapters of the bundled manual” to “documentation.” If exact measurements would create false precision, use “approximately” and identify the unit you used.
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Where to put the disclosure
The reviewed policy does not require a particular MetaInfo element, listing field, manifest field, or submission comment. It also does not supply a standard sentence. Do not present one location as an official requirement.
Choose a location that is visible to the people reviewing the application and that does not place prohibited AI content into a manifest. Depending on the facts of your submission, a project-maintained disclosure document, clearly identified listing text, or another reviewer-visible part of the submission may be appropriate. If the correct placement is consequential or unusual, ask Flathub reviewers before submitting and follow their current instructions.
| Possible location | What is established | Practical caution |
|---|---|---|
| MetaInfo description or related listing text | The policy does not designate it as mandatory, but it may be a visible place for factual information. | Keep the description useful to users and do not treat ordinary metadata guidance as an AI-policy template. |
| Manifest | Not an acceptable place for AI-generated or AI-assisted content. | Never add a disclosure by inserting generated text into the manifest. |
| Submission discussion or review comment | The policy does not require this placement. | Do not let an AI agent generate the comment, reply, commit message, or description. |
| Project documentation included with the source | Can identify affected components when maintained by humans. | If the document itself was AI-generated, disclose that fact and its extent too. |
MetaInfo quality is a separate responsibility
Flathub requires a valid MetaInfo file for an app to appear on its website. Its guidance calls for a short, informative description with supported markup and applicable screenshot metadata. Quality recommendations encourage concise, nontechnical summaries, descriptions that explain the app beyond the summary, and screenshots that clearly show the current application.
Those metadata recommendations do not replace the AI disclosure rule. A listing can have excellent screenshots and a valid MetaInfo file while still needing an AI disclosure, and a disclosure does not make an invalid MetaInfo file acceptable. Review both workstreams independently.
Metadata review checklist
- Confirm the MetaInfo file is valid and corresponds to the app being submitted.
- Make the summary short, informative, and understandable without implementation knowledge.
- Use the longer description to explain what the app does, not to hide the disclosure in promotional language.
- Provide current screenshots and the metadata required for them.
- Check that any generated text included in the MetaInfo file is identified if it falls within the disclosure trigger.
Submission conduct and the role of AI agents
Flathub’s requirements prohibit AI tools or agents from opening or automating submission pull requests. They also prohibit agents from generating submission commit messages, descriptions, review comments, or replies. This restriction applies even when the app itself contains no generated code or documentation.
Use a human maintainer to create the submission, write its messages, answer reviewer questions, and decide how to describe AI-generated material. An AI tool may help you understand a build error or organize a private checklist, but do not delegate the submission communication itself to an agent.
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What happens after disclosure
Disclosure is not acceptance. Flathub reviewers may reject disclosed material because of its extent or role, or because of concerns about review, quality, or maintainability. Material that is undisclosed or materially misrepresented can also lead to rejection.
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If a reviewer asks for clarification
- Identify the exact version and files under discussion.
- Provide a narrower component-level estimate if your original statement was broad.
- Explain what human review changed without claiming that review removes the generated origin.
- Remove or rewrite material if the reviewer considers its role or extent unsuitable.
- Update the disclosure if the submitted content changes.
New applications, renames, and ordinary updates
Flathub’s submission guide covers new applications and renaming. An ordinary update does not need to repeat the new-application process. That distinction does not give permission to omit a newly introduced disclosure: if an update adds AI-generated material to the application or its packaging, audit the new version and keep the listing information accurate.
For an update that removes previously disclosed generated material, revise the disclosure so it describes the version actually being submitted. For an update that expands a disclosed component, change the approximate extent rather than leaving an outdated statement in place.
Common mistakes and fixes
“We used AI, so we disclosed the entire app.”
Problem: This does not identify what is included or how much.
Fix: Name the files, components, or user-facing areas that contain retained generated material and provide an approximate extent.
“We put the disclosure in the manifest.”
Problem: The manifest itself must not contain AI-generated or AI-assisted content.
Fix: Remove generated manifest content and use a human-maintained, reviewer-visible location whose suitability you have confirmed.
“The code was edited by a person, so it is no longer AI-generated.”
Problem: Human editing does not erase the origin of a retained generated portion.
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“The AI only helped with debugging.”
Problem: The exception applies only when no generated material enters the app or packaging.
Fix: Check whether any suggested code, text, script, or asset was copied into the submission. If it was, classify and disclose it.
“The agent can open the pull request faster.”
Problem: Automated submission pull requests and generated submission discussion are prohibited.
Fix: Have a human open the pull request and write the associated messages and replies.
Quick Recap
Final pre-submission checklist
- Have you frozen the exact source and packaging version you will submit?
- Have you identified every retained AI-generated code, documentation, packaging, asset, translation, or other deliverable?
- Does the disclosure name each affected part and give a sensible approximate extent?
- Have you removed AI-generated and AI-assisted content from every Flathub manifest?
- Have you verified that research, discussion, or debugging use did not leave generated output in the app or packaging?
- Is the disclosure placed somewhere suitable without treating an unassigned field as officially required?
- Was the submission pull request, commit message, description, review comment, and reply written and sent by a human?
- Is the MetaInfo file valid, with an informative summary, useful description, and current screenshot metadata?
- Does the disclosure describe the version you are actually submitting?
- Have you checked Flathub’s live requirements for policy changes before submission?
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