
AI coding tools like Anthropic’s Claude Code feel like magic. You can hand off a complex task, grab a coffee, and come back to see the work done. At least, that’s the dream. The reality is often coming back to find it’s been patiently waiting for your permission to run a simple mkdir
command. This constant need for approval is a vital safety net, but let’s be honest, it can seriously slow you down.
Getting a handle on Claude Code permissions is how you unlock a truly autonomous workflow without just tossing security aside. It’s all about finding that perfect balance where the AI can work without interruption on tasks you trust it with, but still asks for a quick check on the more important stuff.
This guide will walk you through everything you need to know. We’ll cover the basics, dive into advanced settings, and look at some powerful flags to help you find the right mix of speed and safety for your workflow.
What are Claude Code permissions and why do they matter?
Claude Code permissions are basically a set of rules that tell the AI assistant what it’s allowed to do on your computer. Out of the box, it’s locked down tight with read-only access. It can look at your files, but it can’t change anything or run commands without getting your okay first.
This permission-first design is in place for a few very good reasons:
-
Security: It’s the main thing stopping the AI from running a catastrophic command (like
rm -rf /
) or poking around in sensitive files like your.env
folder. You wouldn’t give a new intern root access on their first day, and the same idea applies here. -
Control: It keeps you in charge. You get the final say on every file change, shell command, and network request. This makes sure the AI stays focused on its job and doesn’t start "helpfully" refactoring files it shouldn’t be touching.
-
Transparency: The permission prompts show you exactly what the AI is trying to do, one step at a time. This helps you follow its logic and gives you a chance to spot potential mistakes before they happen.
Of course, while this is all great for safety, the default "ask for everything" method gets old fast, especially for repetitive tasks you know are safe. That’s why figuring out how to configure these permissions is so important.
A practical guide to configuring your Claude Code permissions
The best way to set up lasting permission rules is with a settings.json
file. This file lets you define what Claude Code is allowed to do, so you aren’t stuck approving the same safe commands again and again.
Understanding the settings.json file hierarchy for Claude Code permissions
You can put a settings.json
file in a few different places, and Claude Code reads them in a specific order. This layered approach is handy because it allows for personal rules, team-wide standards, and even stricter corporate policies to coexist.
Here’s how it works, from the highest priority to the lowest:
-
Enterprise managed policies (
managed-settings.json
): These are set by system admins for company-wide security and can’t be overridden by anything else. -
Command line arguments: Temporary settings you can apply for a single session.
-
Local project settings (
.claude/settings.local.json
): For your own preferences within a project. This file is ignored by git, so your settings won’t affect anyone else. -
Shared project settings (
.claude/settings.json
): This is the most common spot for team-wide rules. You check this into source control so everyone on the project uses the same permissions. -
User settings (
~/.claude/settings.json
): Your personal global settings that apply to all of your projects.
The three core Claude Code permissions rules: allow, deny, and ask
Inside your settings.json
file, you’ll find a permissions
object where you define your rules. There are three types of rules you can set:
-
allow
: This list automatically approves any matching commands without asking. It’s perfect for safe, common tasks you do all the time, likegit status
ornpm run lint
. -
deny
: This completely blocks any matching command. It’s key for preventing access to sensitive files (Read(./.env)
) or blocking destructive actions. Adeny
rule always overrides anallow
rule. -
ask
: This forces a confirmation prompt, even if there’s a matchingallow
rule. It’s useful for actions you want to double-check before they run, likegit push
.
Here’s a simple example of what a .claude/settings.json
file might look like:
"`json
{
"permissions": {
"allow": [
"Bash(npm run lint)",
"Bash(npm run test:*)",
"Read(~/.zshrc)"
],
"deny": [
"Bash(curl:*)",
"Read(./.env)",
"Read(./secrets/**)"
],
"ask": [
"Bash(git push:*)"
]
}
}
"`
Managing tool-specific Claude Code permissions
You can also get really specific with your rules to control individual tools. This is where you can start to fine-tune your workflow.
-
Bash: You can use wildcards (
*
) to match different versions of a command. For example,Bash(npm run test:*)
will allownpm run test:unit
,npm run test:e2e
, and any other command that starts withnpm run test:
. -
Read & Edit: These rules use a syntax a lot like
.gitignore
for file paths. It’s good to know the difference between a path relative to the settings file (/src/**/*.ts
) and an absolute path on your computer (//Users/you/project/src/**/*.ts
). -
WebFetch: You can allow network requests to certain domains, which is great for letting Claude Code look up documentation or hit an API. For example,
WebFetch(domain:docs.anthropic.com)
would let it read Anthropic’s docs without having to ask you first.
Beyond the basics: advanced Claude Code permissions for power users
Once you have your settings.json
file dialed in, you can use more dynamic, session-based controls to adapt to whatever you’re working on.
Streamlining workflows with Claude Code permissions modes
Permission modes let you change Claude Code’s behavior on the fly. You can set a default mode in your settings.json
file or cycle through them during a session by pressing shift+tab
.
Permission Mode | Description | Best For |
---|---|---|
default | Prompts for permission the first time each tool is used. | Everyday coding where you want a bit of a safety check. |
acceptEdits | Automatically accepts all file modifications for the session. | Rapidly prototyping or refactoring inside a trusted project. |
plan | A read-only mode. Claude can look at code but not change or run it. | Safely exploring a new codebase or just planning out some changes. |
bypassPermissions | Skips all permission prompts. Full autonomy. | Fully automated tasks, ideally running in a secure, isolated environment. |
The ultimate power move for Claude Code permissions: using –dangerously-skip-permissions safely
The –dangerously-skip-permissions
flag is the nuclear option. It gives you a completely uninterrupted session by bypassing all permission checks. And yes, the "dangerously" part is there for a reason. Using it without thinking is a fast way to accidentally delete your project or mess with critical system files.
If you’re going to use it, you have to be smart about it.
-
Use isolated environments: The safest way to use this flag is inside a sandboxed environment like a Docker container. This keeps the AI contained so it can’t make any changes to your main system.
-
Scope your tasks tightly: Don’t just tell it to "build a web app." Give it a very specific, well-defined prompt with clear boundaries. The smaller the task, the lower the risk.
-
Protect sensitive data: Never, ever use this flag in a directory that has API keys, production configs, or any important data that isn’t backed up.
This flag is incredibly useful for long, hands-off tasks, but it requires a lot of discipline.
A better approach to AI agent permissions for support teams
So far, we’ve been talking about a tool that’s clearly built for developers. Managing JSON files, command-line flags, and Docker containers is all in a day’s work for an engineer, but it’s just not practical for business users like customer support or IT teams. They need the power of AI without all the complexity and risk.
The command-line approach to permissions simply doesn’t translate for business teams.
-
It’s too complex: Your support team isn’t going to be editing JSON files or running terminal commands to manage an AI’s permissions. They need a simple, visual interface.
-
It’s too risky: The very existence of a
–dangerously-skip-permissions
flag shows how high the stakes are. You can’t just cross your fingers and hope an AI agent does the right thing with customer data. There’s no safe way to test and confirm its behavior on real-world problems. -
It lacks business context: Claude Code’s permissions are all about system actions:
Read
,Write
,Bash
. A support AI needs permissions for business actions, likelook up order #12345
,tag ticket as ‘urgent’
, orescalate to Tier 2
.
The eesel AI solution: total control without the code
This is where a platform designed specifically for business teams, like eesel AI, comes into play. It gives you the same level of fine-tuned control but in a way that’s accessible, safe, and built for a support environment.
-
Go live in minutes, not months: Forget about a complicated setup. With eesel AI, you get one-click helpdesk integrations for platforms like Zendesk and Freshdesk. You can have a secure, permissioned AI agent working in minutes, no code needed.
-
Test with confidence: Instead of taking a risky leap of faith, eesel AI provides a powerful simulation mode. You can test your AI on thousands of your past support tickets to see exactly how it will perform, what its resolution rate will be, and how much you’ll save before it ever talks to a live customer.
-
Granular, UI-based control: eesel AI lets you define permissions visually. You can use a simple prompt editor to decide exactly which types of tickets the AI should handle, set its tone of voice, and create custom actions like API lookups. It gives you the power of a
settings.json
file, but through an intuitive interface that anyone can use.
Take control of your AI with Claude Code permissions and beyond
Claude Code permissions are a powerful, if a bit complex, system that lets developers tune the balance between safety and automation. Getting comfortable with the settings.json
file, understanding permission modes, and knowing when (and how) to safely use advanced flags are key skills for getting the most out of agentic coding.
But that level of technical detail isn’t the right fit for every team. Business teams need a different way to manage AI agents, one that focuses on security, ease of use, and confident deployment.
That’s where platforms designed for the enterprise really stand out. They give you the power and control of an AI agent without forcing your support team to become command-line wizards.
Ready to deploy an AI agent with confidence?
Tired of tricky configurations and risky flags? With eesel AI, you can build, test, and deploy a powerful AI support agent in just a few minutes. Use our risk-free simulation to see your ROI before you ever go live.
Frequently asked questions
The best way is to create a .claude/settings.json
file in the root of your project directory. This file should be checked into source control, so everyone on the team automatically uses the same set of allow
, deny
, and ask
rules.
Start by being very specific with your allow
rules and avoid broad wildcards like Bash(*)
. Make sure you add explicit deny
rules for sensitive files, such as Read(./.env)
or Read(./secrets/**)
, to prevent any accidental exposure.
You can create a .claude/settings.local.json
file in the same project directory. This file is ignored by git, and any rules you set in it will override the shared settings.json
, letting you customize permissions without affecting your teammates.
The most likely cause is a conflicting deny
rule or a higher-priority setting. Remember that deny
rules always override allow
rules, and settings in a local or enterprise file can override your project-level settings.
Yes, you can use permission modes. During a session, press shift+tab
to cycle through modes like acceptEdits
or plan
, which temporarily change the AI’s behavior without requiring you to modify your settings.json
file.
This flag should only be used for well-defined, automated tasks running in a secure, isolated environment like a Docker container. It’s not for general development, as it bypasses all safety checks that protect your system and data.