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Gplay Vitals Monitoring

Community
hanamizuki
gplay-vitals-monitoring

Monitor Android app stability and performance from the Play Developer Reporting API via gplay vitals. Use to query crash/ANR rates, detect release regressions with anomaly detection, filter error issues/reports with AIP-160 expressions, and break down startup/rendering/battery metrics by dimension. Use when asked to check crash rates, ANR rates, error trends, performance data, or to gate a release on stability.

Overview

Publisherhanamizuki
Repositorysolopreneur
Skill namegplay-vitals-monitoring
Stars
150
Forks
9
Bundled files
1
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.

  • 1 bundled files

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

  • Open source

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

Installation

Install the Gplay Vitals Monitoring 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.
  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/hanamizuki/solopreneur.git /tmp/solopreneur
mkdir -p .claude/skills
cp -r /tmp/solopreneur/plugins/claude/android-dev/skills/gplay-vitals-monitoring .claude/skills/gplay-vitals-monitoring
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Gplay Vitals Monitoring 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 Gplay Vitals Monitoring 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 Gplay Vitals Monitoring 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.

App Vitals Monitoring

gplay vitals hits the Play Developer Reporting API (separate from the Android Publisher API used by most other commands). Every subcommand outputs JSON by default; add --output table|markdown for humans or --pretty to indent JSON. Dates are ISO 8601 (YYYY-MM-DD).

Preconditions

  • Credentials set (gplay auth login or GPLAY_SERVICE_ACCOUNT).
  • Service account needs "View app information and download bulk reports" permission.
  • The app must have enough installs to generate vitals data (small apps return empty sets).

The real surface

There are exactly three groups. There is no crashes list/get, no errors list/get, no performance overview/permissions, no --cluster-id, --version-code, --start-time/--end-time, --severity, or --error-id.

CommandPurpose
vitals crashes queryCrash / ANR rate metrics over a date range
vitals crashes anomaliesAuto-detected regressions — the release gate
vitals performance startup|rendering|batteryPerformance metric breakdowns
vitals errors issuesGrouped error issues (AIP-160 filterable)
vitals errors reportsIndividual error reports with stack traces

Crash & ANR rate metrics

gplay vitals crashes query returns rate metrics, not a cluster list. Switch metric with --type crash|anr; group with --dimension.

bash
# Crash rate for a window
gplay vitals crashes query --package com.example.app --from 2026-06-01 --to 2026-06-30 --output table

# ANR rate
gplay vitals crashes query --package com.example.app --type anr --output table

# Break down by version to spot a bad build
gplay vitals crashes query --package com.example.app --dimension versionCode --output table

# By device model
gplay vitals crashes query --package com.example.app --dimension deviceModel --paginate

Other valid dimensions include deviceModel, deviceBrand, apiLevel, countryCode. Use --paginate to pull every page.

Anomaly detection — the regression / release gate

gplay vitals crashes anomalies lists automatically detected deviations that likely indicate a regression from a new release. This is the command to run in a post-release watch or a CI gate — it does the "is this worse than baseline?" judgement for you across crash, ANR, error, and performance metric sets.

bash
# All anomalies in the last 7 days (default window)
gplay vitals crashes anomalies --package com.example.app --output table

# Just ANR regressions, most recent 20
gplay vitals crashes anomalies --package com.example.app --type anr --limit 20

# Scope to a release window
gplay vitals crashes anomalies --package com.example.app --from 2026-06-25 --to 2026-07-02

--type accepts crash, anr, errors, performance, or all (default). --limit is 1–1000 (default 50).

Performance metrics

Three subcommands, each with an optional --dimension (e.g. apiLevel, deviceModel, country):

bash
# Cold/warm/hot startup percentiles, broken down by API level
gplay vitals performance startup --package com.example.app --dimension apiLevel --output table

# Slow (16ms) and frozen (700ms) frame rates
gplay vitals performance rendering --package com.example.app --from 2026-06-01 --to 2026-06-30

# Battery: excessive wakeups vs. stuck wake locks (choose with --type)
gplay vitals performance battery --package com.example.app --type wakeup --output table
gplay vitals performance battery --package com.example.app --type wakelock

Errors: issues vs. reports, filtered with AIP-160

  • errors issues — reports grouped into issues (counts, distinct users). Start here to triage.
  • errors reports — individual reports with stack traces and device info. Drill in from an issue.

Both filter via a single --filter AIP-160 expression. Supported fields: errorIssueType (CRASH, ANR, NON_FATAL), apiLevel, versionCode, deviceModel, deviceBrand, deviceType, appProcessState (FOREGROUND, BACKGROUND), isUserPerceived; reports additionally supports errorIssueId and errorReportId.

bash
# Top crash issues by report count
gplay vitals errors issues --package com.example.app \
  --filter 'errorIssueType = CRASH' \
  --order-by 'errorReportCount desc' --page-size 10 --output table

# ANR issues most impacting distinct users
gplay vitals errors issues --package com.example.app \
  --filter 'errorIssueType = ANR' --order-by 'distinctUsers desc'

# Compound filter: crashes on a specific version, foreground only
gplay vitals errors reports --package com.example.app \
  --filter 'errorIssueType = CRASH AND versionCode = 105 AND appProcessState = FOREGROUND'

# All reports belonging to one issue (drill-down)
gplay vitals errors reports --package com.example.app \
  --filter 'errorIssueId = 1234567890' --page-size 20

--order-by (issues only) accepts errorReportCount / distinctUsers with asc/desc. Use --paginate for everything.

JSON + jq extraction

Default JSON is meant to be piped:

bash
# Pull the errorIssueId of the worst crash issue
WORST=$(gplay vitals errors issues --package com.example.app \
  --filter 'errorIssueType = CRASH' --order-by 'errorReportCount desc' --page-size 1 \
  | jq -r '.errorIssues[0].name')

# Count anomalies flagged in the release window
gplay vitals crashes anomalies --package com.example.app --from 2026-06-25 --to 2026-07-02 \
  | jq '.anomalies | length'

Field names vary by endpoint — inspect once with --pretty before scripting against a path.

Stability workflow

  1. Watch after every release. Run vitals crashes anomalies scoped to the rollout window first — it surfaces regressions without you setting thresholds.
  2. Confirm the trend. vitals crashes query --type crash and --type anr for the rate; add --dimension versionCode to confirm the new build is the culprit.
  3. Triage. vitals errors issues --filter 'errorIssueType = CRASH' --order-by 'errorReportCount desc' to rank by impact.
  4. Drill in. Take the issue id and run vitals errors reports --filter 'errorIssueId = <id>' for stack traces and device breakdown.
  5. Track ANRs separately — they weigh heavily on Play ranking; always check --type anr distinctly.

CI/CD stability gate

Prefer anomalies over hand-rolled thresholds. Note --rollout is a fraction 0.0–1.0, never a percent.

bash
ANOMALIES=$(gplay vitals crashes anomalies \
  --package com.example.app --type all --from "$RELEASE_DATE" \
  | jq '.anomalies | length')

if [ "$ANOMALIES" -gt 0 ]; then
  echo "Vitals anomalies detected ($ANOMALIES). Halting promotion."
  exit 1
fi

# Clean — promote beta to a 10% staged production rollout
gplay promote --package com.example.app --from beta --to production --rollout 0.1

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 Gplay Vitals Monitoring AI skill do?

Monitor Android app stability and performance from the Play Developer Reporting API via gplay vitals. Use to query crash/ANR rates, detect release regressions with anomaly detection, filter error issues/reports with AIP-160 expressions, and break down startup/rendering/battery metrics by dimension. Use when asked to check crash rates, ANR rates, error trends, performance data, or to gate a release on stability.

Why use Gplay Vitals Monitoring on TypingMind?

Because you install it once and use it with any model. Gplay Vitals Monitoring 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 Gplay Vitals Monitoring in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/hanamizuki/solopreneur/tree/main/plugins/claude/android-dev/skills/gplay-vitals-monitoring. 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 Gplay Vitals Monitoring?

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 Gplay Vitals Monitoring?

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

Is the Gplay Vitals Monitoring AI skill free?

Yes. It is published on GitHub by hanamizuki 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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