AI Tool Permission Checker
AI tools can look simple while still reading user content, drafting outputs, editing files, or taking actions across connected services. Use this checklist before launch to make permissions, confirmations, and disclosure language easier for users to understand.
Last updated: June 2026
Who this is for
Built for practical launch reviews
- Builders launching AI assistants, content tools, workflow automations, or agents that touch user data.
- Teams adding AI features to an existing app and deciding what permissions to ask for.
- Indie makers who need clearer language around AI access, user control, and launch risk.
What to check first
Start with the checks most likely to block launch
List what the AI can access
Write down the files, text, account data, connected tools, and user inputs the feature can read.
Class the risk level
Low risk is usually draft-only or single-page access. Medium risk includes account, file, inbox, or calendar reading. High risk includes sending, deleting, publishing, buying, or changing settings.
Add confirmations where risk rises
Ask users to confirm before the tool performs meaningful actions or changes something outside the current draft.
Practical checklist
Work through these checks before launch
Use simple permission risk levels
Risk depends on what the AI can see and what it can change. Sort permissions before writing copy or connecting tools.
Low risk
The AI works on text the user pastes, a single selected document, or a draft that cannot be sent or published without the user.
Medium risk
The AI can read connected account data, Gmail messages, Calendar events, files, browser pages, repository context, or multiple documents.
High risk
The AI can send email, create or move calendar events, edit or delete files, run commands, merge code, publish content, buy things, or change account settings.
Map the permission boundary
Start with a plain list of what the tool can access and what it cannot.
Separate read and write access
Reading a file, drafting a message, and publishing a change are different levels of permission. Describe them separately.
Name the connected surfaces
If the feature touches Gmail, Calendar, files, browser tabs, repositories, inboxes, or website content, make that visible before users grant access.
Avoid broad access by default
Ask for the narrowest practical permission first, then expand only when a user action requires it.
Review common access risks
These permissions are useful in real products, but they deserve clearer wording and stronger user control.
Gmail and Calendar access
Reading email or calendar data can expose private messages, contacts, meetings, attachments, travel plans, and business context. Sending or rescheduling needs explicit confirmation.
File and drive access
File permissions can expose drafts, contracts, customer lists, financial notes, images, and shared folders. Prefer selected-file access over entire-drive access where possible.
Browser access
Browser tools and extensions can see page content, form fields, URLs, or tab context depending on their permissions. Avoid all-sites access unless it is truly needed.
Check AI extension and coding tool risks
AI tools that operate inside browsers or codebases can cross from suggestion into action very quickly.
AI browser extensions
Check whether the extension can read every site, only selected sites, active tabs, clipboard text, or form fields. Explain what is processed and how users can turn it off.
AI coding tools
Review whether the tool can read private code, edit files, run commands, install packages, create commits, open pull requests, or access secrets in logs.
Command and automation access
Treat shell commands, file deletion, database migrations, deployment changes, and external service actions as high risk unless a human reviews and confirms them.
Explain user control
Users should understand when AI is assisting, suggesting, or taking an action.
Label AI-generated output
Make it clear when text, recommendations, summaries, or actions are produced by an AI feature.
Confirm important actions
Require a clear user confirmation before sending messages, deleting data, publishing content, charging money, or changing account settings.
Provide an escape route
Tell users how to turn off the feature, disconnect access, or correct an output when something is wrong.
Review launch language
Permission copy should be understandable before a user trusts the feature.
Use plain verbs
Prefer words like read, draft, edit, send, delete, and publish over vague language such as manage or optimize.
Do not overpromise accuracy
If users need to review results, say so. Avoid implying the tool is always correct or fully autonomous when it is not.
Place disclosures near the feature
Footer copy is useful, but permission explanations are strongest when users see them at the point of action.
Ask before connecting an AI tool
Use these questions before asking users to connect accounts, files, browsers, or code repositories.
What exactly can it read?
Name the data sources: selected page, current tab, Gmail, Calendar, files, repository, docs, images, customer records, or uploaded text.
What exactly can it change?
Separate draft suggestions from actions such as send, delete, publish, merge, install, deploy, reschedule, or update settings.
How can users review or revoke access?
Show where users can confirm actions, disconnect integrations, narrow permissions, delete outputs, or report a bad result.
Practical examples
What good launch checks look like
Clear permission copy
This assistant can read the document you select and suggest edits. It will not publish changes without your confirmation.
Risky vague copy
This tool manages your workspace is too broad unless the page explains whether it can read files, edit docs, send email, change calendars, or control browser tabs.
Good boundary
Let the AI draft a reply or code change, then require the user to review and press Send, Publish, Merge, or Delete themselves.
Low risk example
A user pastes a short paragraph into a tool and the AI suggests a rewritten draft. It cannot read other pages, save changes, or send anything.
Medium risk example
An assistant can read selected Gmail messages, Calendar events, or project files to summarize context, but it cannot send, reschedule, delete, or publish.
High risk example
An AI tool can send emails, move meetings, edit files, run terminal commands, merge code, or publish content without a separate human confirmation.
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Short answers before launch
What counts as an AI permission?
Any access or action the AI feature can use: reading content, generating drafts, editing records, calling tools, sending messages, or changing settings.
Do AI features always need a disclosure?
If users are interacting with AI-generated output or AI-assisted actions, plain disclosure is usually the clearer and safer product choice.
Where should permission copy appear?
Put the most important permission language near the feature, connection step, or action button, not only in legal pages.
How can I reduce risk before launch?
Start with narrower permissions, require confirmation for meaningful actions, make outputs reviewable, and avoid overstating accuracy.
Are browser extensions higher risk?
They can be. A browser extension may see page content, forms, tabs, or browsing context depending on permissions. Keep access scoped and explain it clearly.
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