Appfunctions

OrganizationPopular

android

appfunctions

Analyzes Android apps to identify key user workflows for AppFunctions such as creating a note, playing media, or sending an automated or AI agent triggered message, voice commands, or system shortcuts, without needing to open the app UI. Generates Kotlin code to expose these workflows to the Android system, allowing agents to discover and execute them on-device. Also refines KDoc documentation to ensure AI agents correctly understand and use the provided functionality.

Overview

Publisher	android
Repository	`skills`
Skill name	`appfunctions`
Stars	7.4K
Forks	484
Bundled files	6
License	Apache-2.0
Links	Skill source Repository

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.
6 bundled files
Scripts, templates, and references the model can read while it works. Files are read-only and never executed.
Open source
Published by android on GitHub. Read the source before you install it.

Installation

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

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.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
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.

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/android/skills.git /tmp/skills
mkdir -p .claude/skills
cp -r /tmp/skills/device-ai/appfunctions .claude/skills/appfunctions

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Appfunctions 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 Appfunctions 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 Appfunctions 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.

Generates Kotlin code to expose these workflows to the Android system, allowing agents to discover and execute them on-device.

Also refines KDoc documentation to ensure AI agents correctly understand and use the provided functionality.

Prerequisites

The app must targetSdk 36 or newer and use compileSdk 37 or newer as AppFunctions, part of the Android platform API, are available from Android 16 onwards. Always use the Jetpack library because it handles backward compatibility.

Workflows

This skill enables the caller to discover features that will be provided to system agents, implement these with AppFunctions, improve function description for agents, and use ADB commands for local evaluation and testing.

The full AppFunction development flow consists of these four steps:

Step 1: Discovery: Analyze Android codebases to identify and recommend potential AppFunctions. Use this step when a user asks to "discover AppFunctions," "find features for AI," or "analyze my app for agentic tools."
Step 2: Implementation and configuration: Generate Kotlin implementations of AppFunctions, manage system-wide configuration, and configure build dependencies. Use this step when a user asks to "implement AppFunctions," "set up the AppFunctions framework," or "configure Hilt for AppFunctions."
Step 3: KDoc refinement: Optimize AppFunction KDoc for AI agents and Model Context Protocol. If a user asks to "write KDoc", "optimize for MCP", or "refactor tool descriptions for LLMs", use this step.
Step 4: Testing and debugging: Provide commands to interact with AppFunctions using ADB for testing and debugging. If a user wants to "list app functions", "invoke an app function", or "verify app function registration" on a device, use this step.

If users request a subset of steps, you must encourage them to use all steps.

If they apply, you must load the following references:

Context and terminology: Defines the ubiquitous language, architecture definitions, and design patterns across the AppFunctions skill suite. Load when you need to understand core architecture terminology or check the distinctions between modern and legacy AppFunctions APIs.
Migration to service entry point : Documents the systematic procedure for migrating Android applications using AppFunctions versions 1.0.0-alpha09 and lower to AppFunctionServiceEntryPoint architecture introduced in version 1.0.0-alpha10. Load when a user asks to migrate or upgrade existing AppFunctions code, or when you encounter legacy AppFunctionConfiguration.Provider implementations.

Critical constraints

Modular consistency: You must refine KDocs immediately after you generate AppFunction implementations.
Security: Don't expose sensitive data or run destructive actions without user confirmation.

Troubleshooting

If you encounter build-time errors such as Kotlin Symbol Processing (KSP) issues, see Implementation and configuration.
If you encounter runtime errors such as missing services or execution failures, see Testing and debugging.
If you need architecture definitions and vocabulary, see Context and terminology.
If you encounter issues when upgrading legacy configurations, see Migration to service entry point.

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 Appfunctions AI skill do?

Why use Appfunctions on TypingMind?

Because you install it once and use it with any model. Appfunctions 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 Appfunctions in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/android/skills/tree/main/device-ai/appfunctions. 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 Appfunctions?

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 Appfunctions?

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

Is the Appfunctions AI skill free?

Yes. It is published on GitHub by android under the Apache-2.0 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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Verification Before Completion

obra

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Use when about to claim work is complete, fixed, or passing, before committing or creating PRs - requires running verification commands and confirming output before making any success claims; evidence…

Writing Plans

Use when you have a spec or requirements for a multi-step task, before touching code

Ask Matt

Ask which skill or flow fits your situation. A router over the skills in this repo.

Code Review

Review the changes since a fixed point (commit, branch, tag, or merge-base) along two axes: Standards (does the code follow this repo's documented coding standards?) and Spec (does the code match what…

Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Prerequisites

Workflows

Critical constraints

Troubleshooting

Bundled files

Frequently asked questions

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