# Android Skills: Philosophy, Selection Criteria, and Evaluation Methodology

DevFeed: [Android Skills: Philosophy, Selection Criteria, and Evaluation Methodology](<https://devfeed.tech/articles/inside-android-skills-built-for-deprecation-22688.md>)

Original publisher: [Read original article](<http://android-developers.googleblog.com/2026/08/android-skills-philosophy.html>)

Author: Android Developers (noreply@blogger.com)

Published: 2026-08-06T16:00:00Z

Content type: opinion

Language: en

Sources: [Android Developers Blog](<https://devfeed.tech/sources/android-developers-blog-3.md>)

Topics: [Android skills](<https://devfeed.tech/topics/android-skills.md>), [Large Language Model](<https://devfeed.tech/topics/llm.md>), [Android Studio](<https://devfeed.tech/topics/android-studio.md>), [Command-line interface](<https://devfeed.tech/topics/cli.md>)

Tags: [agent](<https://devfeed.tech/tags/agent.md>), [agents](<https://devfeed.tech/tags/agents.md>), [ai-assisted-coding](<https://devfeed.tech/tags/ai-assisted-coding.md>), [android-skills](<https://devfeed.tech/tags/android-skills.md>), [android-studio](<https://devfeed.tech/tags/android-studio.md>), [antigravity](<https://devfeed.tech/tags/antigravity.md>), [cli](<https://devfeed.tech/tags/cli.md>), [docs](<https://devfeed.tech/tags/docs.md>), [gemini](<https://devfeed.tech/tags/gemini.md>)

## AI overview

Android Developer Relations explains how official Android Skills are selected, focusing on verifiable knowledge gaps in state-of-the-art models and fast-moving topics. The article also discusses context costs, evaluation requirements, model compatibility, and use of the Android Knowledge Base.

## Source excerpt

Posted by Jose Alcérreca, Developer Relations Engineer, Android Developer Relations We released the official Android Skills in April, and the response surpassed all our expectations. In this blog post, I'll address some of the feedback we received, explaining the philosophy and methodology behind the project. Hopefully, this will also help you understand what happens behind the scenes when you install and use skills, allowing you to make better use of tokens and your own time. Why are there so few official skills? Currently, we only consider new skills when there's a verifiable knowledge gap in state-of-the-art (SOTA) models. Put simply: you don't need to teach the model what it already knows. (Though there are a few exceptions--read on!) We've released around 20 official skills so far, and they intentionally target highly specific, fast-moving areas that standard models aren't fully grounded on yet--things like AGP 9, Navigation 3, advanced Camera APIs, and Perfetto SQL. What about core, more general, skills? Every installed skill injects 100-200 tokens into the baseline context of every task you start. If that skill actually activates, that count can quickly jump into the thousands. In most cases, hoarding basic skills is both counterproductive and expensive. Before installing a skill for writing basic Kotlin or Compose, consider if your LLM of choice really needs it, or if it knows those topics well enough already. Evaluating skills Before their release, each skill is tested against a comprehensive set of evals that prove that the skill delivers clear value. These evals should pass when the skill is active, and fail otherwise. Evals are to skills what integration tests are to code. timeout_s: 1200 repository: url: [redacted - internal git repo] working_dir: wear_compose_m3_empty_app category_ids: - wear prompt: |- Add a horizontal pager to MainActivity.kt. Have three pages in the pager. Each page should contain the text "Page 1", "Page 2", and "Page 3" respectively