Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/guillemroca/agent-skills-android/performance-optimizationnpx skills add GuillemRoca/agent-skills-android --skill performance-optimizationgit clone --depth 1 https://github.com/GuillemRoca/agent-skills-androidWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/guillemroca/agent-skills-android/performance-optimization)<a href="https://agentmods.dev/skills/guillemroca/agent-skills-android/performance-optimization"><img src="https://agentmods.dev/badge/skills/guillemroca/agent-skills-android/performance-optimization.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00043 | $0.01876 |
| Opus 5 | $0.00022 | $0.00938 |
| Sonnet 5 | $0.00009 | $0.00375 |
| Haiku 4.5 | $0.00004 | $0.00188 |
Grade A, and why
performance-optimization scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 4d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 263 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Performance Optimization
Overview
"Performance optimization without measurement is guessing." Measure first, identify bottlenecks with data, fix with targeted changes, verify the improvement, and guard against regressions. Never optimize based on assumptions.
When to Use
- App startup exceeds 500ms (cold) or 200ms (warm)
- UI jank (dropped frames, janky scrolling)
- ANR (Application Not Responding) reports
- APK/AAB size exceeds budget
- Before a release (performance regression check)
- Users report slowness or battery drain
Skip when: No performance issue is observed or measured.
Android Vitals Targets
| Metric | Target | Critical |
|---|---|---|
| Cold startup | < 500ms | > 1s |
| Warm startup | < 200ms | > 500ms |
| Frame rendering (jank) | < 5% slow frames | > 10% slow frames |
| ANR rate | < 0.47% | > 1% |
| APK size (compressed) | < 10MB | > 50MB |
| Memory usage | < 150MB typical | > 256MB |
Core Process
Step 1: Measure
- Baseline Profiles (startup and scrolling):
// benchmark/src/main/java/BaselineProfileGenerator.kt
@RunWith(AndroidJUnit4::class)
class BaselineProfileGenerator {
@get:Rule
val rule = BaselineProfileRule()
@Test
fun generateBaselineProfile() {
rule.collect(packageName = "com.example.app") {
// Cold start
pressHome()
startActivityAndWait()
// Critical user journeys
device.findObject(By.text("Tasks")).click()
device.waitForIdle()
// Scroll the list
val list = device.findObject(By.res("task_list"))
list.setGestureMargin(device.displayWidth / 5)
list.fling(Direction.DOWN)
device.waitForIdle()
}
}
}
- Macrobenchmark (startup timing):
@RunWith(AndroidJUnit4::class)
class StartupBenchmark {
@get:Rule
val rule = MacrobenchmarkRule()
@Test
fun coldStartup() {
rule.measureRepeated(
packageName = "com.example.app",
metrics = listOf(StartupTimingMetric()),
startupMode = StartupMode.COLD,
iterations = 5,
) {
pressHome()
startActivityAndWait()
}
}
}
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 4d ago First seen · 263 lines · 43 tokens per session scan A c32530bdc8dd
performance-optimization is a skill published in the GitHub repository GuillemRoca/agent-skills-android (2 stars, last pushed 2mo ago), licensed MIT. It adds 43 tokens to every session and 1,876 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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