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Macos Permissions

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daymade
macos-permissions

Diagnoses and repairs macOS TCC dialogs and silent denials: Full Disk Access, Screen Recording, Microphone, Camera, Accessibility, Automation. Use for recurring prompts, LaunchAgent/uv jobs that fail only in background, broken grants, or automating Full Disk Access (权限弹窗 / 授权了没用 / 完全磁盘访问). Checks requester and grants first. Not for launchd design (macos-watchdog) or app permission UX (developing-ios-apps).

Overview

Publisherdaymade
Repositoryclaude-code-skills
Skill namemacos-permissions
Stars
1.4K
Forks
222
Bundled files
3
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 3 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by daymade on GitHub. Read the source before you install it.

Installation

Install the Macos Permissions AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/daymade/claude-code-skills/tree/main/daymade-macos/macos-permissions
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/daymade/claude-code-skills.git /tmp/claude-code-skills
mkdir -p .claude/skills
cp -r /tmp/claude-code-skills/daymade-macos/macos-permissions .claude/skills/macos-permissions
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Macos Permissions in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Macos Permissions on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Macos Permissions is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

macOS Permissions (TCC)

macOS gates per-app, per-resource access through TCC (Transparency, Consent, Control). TCC records permission decisions in its databases and controls what a process can do. Several common traps need different fixes:

TrapSymptomFix lives in
Wrong subject grantedDialog names python3.11/2.1.232/node; you granted that but it still promptsThe attribution trap below
Grant doesn't surviveWorked, then a binary/uv/CLI update → prompt returnsreferences/uv-fda-trap.md
Silent denialFeature "unavailable", no dialog, grant looks ONreferences/tcc-mechanics.md § auth_value
Can't read TCC.dbPermission denied reading the DB; need FDA to diagnose FDAreferences/tcc-mechanics.md § SIP

The attribution trap

The name in the dialog does not prove who to grant. macOS attributes a request to the responsible process in the process tree, but displays the name of the accessing executable — and for an unsigned binary with no bundle (uv-managed python, per-version CLI, node helpers) that display name is just the last path component, which changes with every version. Granting the displayed name is the mistake that costs the most rounds.

Before touching System Settings, inspect the request and any readable grant state:

bash
# 1. Who is actually requesting — the responsible process in the attribution chain
/usr/bin/log show --last 30m --predicate 'subsystem == "com.apple.TCC"' --info --debug \
  | grep -E 'from Sub:|responsible=|accessing=' | tail -20

# 2. Grant candidates, if this terminal can read the system database
sudo -n sqlite3 '/Library/Application Support/com.apple.TCC/TCC.db' \
  "select service, client, auth_value from access where service='kTCCServiceSystemPolicyAllFiles' and client like '%<name>%';"

Use from Sub: to identify a candidate requester, then verify its exact path and a real protected read before choosing what to authorize. An unreadable TCC.db leaves grant state unknown; its FDA bootstrap is in references/tcc-mechanics.md.

Decision tree

The situation is…Go to
User asks to complete Full Disk Access repair automatically, or a background job needs protected filesreferences/automated-full-disk-access.md (reuse a verified existing grant first; otherwise drive System Settings and read back)
Dialog reappears after clicking Allow; or a LaunchAgent / uv run job prompts every few minutesreferences/uv-fda-trap.md (identify the requester; follow the automated repair route before adding a grant)
Need the full kTCCService catalog, schema, auth_value/auth_reason semantics, tccutilreferences/tcc-mechanics.md
Reading TCC.db gives "Permission denied"references/tcc-mechanics.md § SIP and the FDA bootstrap
A granted permission silently stopped working after an updatereferences/tcc-mechanics.md § common failure modes (toggle off/on, or tccutil reset <Service> <bundle-id>)
Grant won't stick for Automation / Apple Eventsreferences/tcc-mechanics.md — BOTH controller AND target need the grant

Core rules (each from a real incident)

  • Dialog name ≠ responsible process. from Sub: in the TCC log is the requester; the title is the accessing binary's basename and it drifts with versions. Grant by the real path. (2026-09-19: a uv FDA dialog showed python3.11; authorizing python, changing session type, and pinning the version all failed because the requester was ~/.local/bin/uv.)
  • Grants are keyed to the exact binary path, not identity. An unsigned executable (uv-managed python, per-version CLI, node helper) is a new app to TCC every time its path changes. This is why "worked yesterday, prompts today" after any update. Same root cause as Claude Code issues #74234 / #84948 / #86706.
  • "0 hits / can't catch it" is an instrument problem, not a conclusion. fs_usage can emit 0 bytes on some machines; short-lived processes fall between log time windows; an empty grep file looks identical to a real zero. To pin which operation triggers a prompt, use in-process sys.addaudithook to log open events aligned to the tccd timestamp — not fs_usage.
  • SIP protects the system TCC.db read-only. You cannot INSERT/UPDATE a grant from the command line — authorization must go through the GUI. auth_value is readable, writable is not.
  • After granting, restart the requesting process. Grants are read at launch; a running process keeps its old (denied) state until relaunched.

Scope

This skill owns permission diagnosis and repair. It does not own: building an app's permission-onboarding UX (app-development work, out of scope here), launchd job design (macos-watchdog), or disk cleanup (macos-cleaner) — those link here when they hit a TCC wall.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Macos Permissions AI skill do?

Diagnoses and repairs macOS TCC dialogs and silent denials: Full Disk Access, Screen Recording, Microphone, Camera, Accessibility, Automation. Use for recurring prompts, LaunchAgent/uv jobs that fail only in background, broken grants, or automating Full Disk Access (权限弹窗 / 授权了没用 / 完全磁盘访问). Checks requester and grants first. Not for launchd design (macos-watchdog) or app permission UX (developing-ios-apps).

Why use Macos Permissions on TypingMind?

Because you install it once and use it with any model. Macos Permissions is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Macos Permissions in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/daymade/claude-code-skills/tree/main/daymade-macos/macos-permissions. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Macos Permissions?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Macos Permissions?

As many as you like. As long as a model supports skills, you can use Macos Permissions with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Macos Permissions AI skill free?

Yes. It is published on GitHub by daymade under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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