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 skills add krutikJain/android-agent-skills --skill android-performance-observabilitygit clone --depth 1 https://github.com/krutikJain/android-agent-skillsWrote 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/krutikjain/android-agent-skills/android-performance-observability)<a href="https://agentmods.dev/skills/krutikjain/android-agent-skills/android-performance-observability"><img src="https://agentmods.dev/badge/skills/krutikjain/android-agent-skills/android-performance-observability.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 5.1 | $0.00031 | $0.01131 |
| Opus 5 | $0.00015 | $0.00566 |
| Sonnet 5 | $0.00006 | $0.00226 |
| Haiku 4.5 | $0.00003 | $0.00113 |
Grade A, and why
android-performance-observability 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 3d 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 — 77 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Android Performance Observability
When To Use
- Use this skill when the request is about: android performance profiling, baseline profile or macrobenchmark, app startup issue android.
- Primary outcome: Measure startup, rendering, memory, jank, vitals, logs, and crash signals for Android apps with actionable traces.
- Read
references/patterns.mdwhen you need the measurement ladder for startup, jank, traces, and production signals. - Read
references/scenarios.mdfor repeatable profiling and trace-oriented entry points. - Handoff skills when the scope expands:
android-compose-performanceandroid-ci-cd-release-playstore
Workflow
- Classify the symptom before choosing tools: cold start, warm start, frame/jank, scrolling, memory, ANR, crash, battery, or production vitals drift.
- Measure on release-like builds and physical devices whenever possible; avoid debugging from debug-only traces or profile-unfriendly builds.
- Pick the smallest tool that answers the question: Macrobenchmark for startup/scroll numbers, Baseline Profiles for ahead-of-time optimization, Perfetto/System Tracing for deep traces, JankStats or FrameMetrics for frame quality, and Play Vitals for field evidence.
- Change one thing at a time, then compare before and after traces or benchmark outputs instead of stacking multiple optimizations blindly.
- Hand off UI-specific rendering changes or release rollouts only after the measurement surface is stable and the bottleneck is evidenced.
Guardrails
- Treat benchmarks, traces, and vitals as different evidence sources with different noise profiles; do not mix them casually.
- Prefer reproducible release-build measurements over debug-build intuition.
- Tie optimizations back to user-facing metrics such as startup time, frame pacing, ANRs, or battery impact.
- Keep the profiling setup stable enough that regressions are attributable to code changes instead of device or environment churn.
Anti-Patterns
- Chasing micro-optimizations before identifying whether the problem is startup, rendering, I/O, or field reliability.
- Reading one noisy trace and presenting the result as settled fact.
- Measuring debug builds and assuming the same behavior in production.
- Adding Baseline Profiles or macrobenchmarks without checking whether the target path is stable enough to compare.
What ships with it
5 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 3d ago First seen · 77 lines · 31 tokens per session scan A fa1bbc90df43
android-performance-observability is a skill published in the GitHub repository krutikJain/android-agent-skills (14 stars, last pushed 5mo ago), licensed MIT. It adds 31 tokens to every session and 1,131 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 2026-09-03.
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