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Gplay Release Flow

Community
hanamizuki
gplay-release-flow

End-to-end release workflows for Google Play tracks (internal, beta, production) using gplay release, promote, and rollout commands. Use when asked to upload a build, distribute to testers, or release to production.

Overview

Publisherhanamizuki
Repositorysolopreneur
Skill namegplay-release-flow
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 Release Flow 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-release-flow .claude/skills/gplay-release-flow
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Gplay Release Flow 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 Release Flow 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 Release Flow 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.

Release flow (Internal, Beta, Production)

Use this skill when you need to get a new build onto Google Play Store.

Preconditions

  • Ensure credentials are set (gplay auth login or GPLAY_SERVICE_ACCOUNT env var).
  • Build must be an AAB (App Bundle) or APK.
  • Version code must be higher than previous releases.
  • Service account needs "Release Manager" permission in Play Console.

Android Release

Preferred end-to-end commands

Internal track (for internal testing):

bash
gplay release \
  --package com.example.app \
  --track internal \
  --bundle app-release.aab

Beta track (for beta testers):

bash
gplay release \
  --package com.example.app \
  --track beta \
  --bundle app-release.aab \
  --release-notes @release-notes.json

Production with staged rollout (gradual release):

bash
gplay release \
  --package com.example.app \
  --track production \
  --bundle app-release.aab \
  --release-notes @release-notes.json \
  --rollout 0.1

Dry run (preview the release without executing):

bash
gplay release \
  --package com.example.app \
  --track production \
  --bundle app-release.aab \
  --dry-run

Release with metadata (listings and screenshots)

Include store listings from a directory:

bash
gplay release \
  --package com.example.app \
  --track production \
  --bundle app-release.aab \
  --listings-dir ./metadata \
  --screenshots-dir ./metadata

Skip metadata or screenshots:

bash
# Upload bundle only, skip metadata sync
gplay release \
  --package com.example.app \
  --track production \
  --bundle app-release.aab \
  --skip-metadata

# Upload bundle and metadata, skip screenshots
gplay release \
  --package com.example.app \
  --track production \
  --bundle app-release.aab \
  --listings-dir ./metadata \
  --skip-screenshots

Combine listings and screenshots directories:

bash
gplay release \
  --package com.example.app \
  --track beta \
  --bundle app-release.aab \
  --listings-dir ./metadata/listings \
  --screenshots-dir ./metadata/images \
  --release-notes @release-notes.json

Manual sequence (when you need more control)

  1. Create edit session:

    bash
    EDIT_ID=$(gplay edits create --package com.example.app | jq -r '.id')
  2. Upload bundle:

    bash
    gplay bundles upload \
      --package com.example.app \
      --edit $EDIT_ID \
      --file app-release.aab
  3. Update track:

    bash
    gplay tracks update \
      --package com.example.app \
      --edit $EDIT_ID \
      --track production \
      --releases @releases.json

    --releases takes a JSON array of track releases (or @file).

  4. Validate edit:

    bash
    gplay edits validate --package com.example.app --edit $EDIT_ID
  5. Commit edit (publishes changes):

    bash
    gplay edits commit --package com.example.app --edit $EDIT_ID

Track Promotion

Promote a release from one track to another:

bash
# Promote from internal to beta
gplay promote \
  --package com.example.app \
  --from internal \
  --to beta

# Promote from beta to production with 25% rollout
gplay promote \
  --package com.example.app \
  --from beta \
  --to production \
  --rollout 0.25

Staged Rollout Management

Start with a 10% rollout (fraction 0.1):

bash
gplay release \
  --package com.example.app \
  --track production \
  --bundle app.aab \
  --rollout 0.1

Increase to 50% (fraction 0.5):

bash
gplay rollout update \
  --package com.example.app \
  --track production \
  --rollout 0.5

Halt rollout (pause distribution):

bash
gplay rollout halt --package com.example.app --track production

Resume rollout:

bash
gplay rollout resume --package com.example.app --track production

Complete rollout (release to 100%):

bash
gplay rollout complete --package com.example.app --track production

Release Notes Format

The single --release-notes flag accepts three shapes: a JSON array (multi-locale), plain text (auto-assigned to en-US), or an @file path pointing to either. There is no separate locale flag.

JSON array format (multi-locale)

release-notes.json — a JSON array of {language, text} entries:

json
[
  { "language": "en-US", "text": "Bug fixes and performance improvements" },
  { "language": "es-ES", "text": "Correcciones de errores y mejoras de rendimiento" },
  { "language": "fr-FR", "text": "Corrections de bugs et améliorations des performances" }
]

Pass it with --release-notes @release-notes.json.

Plain text format (single locale)

Provide release notes as plain text — it is auto-assigned to en-US:

bash
gplay release \
  --package com.example.app \
  --track beta \
  --bundle app.aab \
  --release-notes "Bug fixes and performance improvements"

Or from a file (plain text or a JSON array) with @:

bash
gplay release \
  --package com.example.app \
  --track beta \
  --bundle app.aab \
  --release-notes @release-notes.txt

Release Flags Reference

FlagDescription
--packageApp package name (required)
--trackTarget track (production, beta, alpha, internal; default: internal)
--bundlePath to AAB file (use --bundle or --apk, not both)
--apkPath to APK file (alternative to --bundle)
--release-notesRelease notes: plain text (auto-assigned en-US), a JSON array of {language, text}, or @file
--rolloutStaged rollout fraction (0.0-1.0, default: 1.0 for full rollout)
--listings-dirDirectory containing store listings to sync
--screenshots-dirDirectory containing screenshots to upload
--skip-metadataSkip metadata/listings sync during release
--skip-screenshotsSkip screenshots upload during release
--dry-runPreview the release without executing
--outputOutput format (json, table, markdown)

Pre-release Checklist

Before releasing, verify:

  • Version code is incremented
  • AAB/APK is signed with correct keystore
  • ProGuard/R8 mapping files uploaded (for crash reports)
  • Release notes written for all locales
  • Testing completed on internal/beta track
  • Service account has correct permissions
  • Dry run passes: gplay release ... --dry-run

Common Release Strategies

Strategy 1: Internal -> Beta -> Production

bash
# Week 1: Internal
gplay release --package com.example.app --track internal --bundle app.aab

# Week 2: Beta (after testing)
gplay promote --package com.example.app --from internal --to beta

# Week 3: Production with staged rollout
gplay promote --package com.example.app --from beta --to production --rollout 0.1
gplay rollout update --package com.example.app --track production --rollout 0.5  # Day 2
gplay rollout complete --package com.example.app --track production             # Day 7

Strategy 2: Direct to Production with Staged Rollout

bash
# Day 1: 10%
gplay release --package com.example.app --track production --bundle app.aab --rollout 0.1

# Day 2: 25%
gplay rollout update --package com.example.app --track production --rollout 0.25

# Day 3: 50%
gplay rollout update --package com.example.app --track production --rollout 0.5

# Day 7: 100%
gplay rollout complete --package com.example.app --track production

Strategy 3: Full release with metadata and dry-run verification

bash
# 1. Dry run to verify everything
gplay release \
  --package com.example.app \
  --track production \
  --bundle app.aab \
  --listings-dir ./metadata \
  --screenshots-dir ./metadata \
  --release-notes @release-notes.json \
  --rollout 0.1 \
  --dry-run

# 2. Execute the release
gplay release \
  --package com.example.app \
  --track production \
  --bundle app.aab \
  --listings-dir ./metadata \
  --screenshots-dir ./metadata \
  --release-notes @release-notes.json \
  --rollout 0.1

Notes

  • Always use --help to verify flags for the exact command.
  • Use --output table for human-readable output; default is JSON.
  • For CI/CD, use GPLAY_SERVICE_ACCOUNT environment variable.
  • Upload deobfuscation files after each release for crash symbolication.
  • Use --dry-run in CI to validate releases before actual deployment.

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 Release Flow AI skill do?

End-to-end release workflows for Google Play tracks (internal, beta, production) using gplay release, promote, and rollout commands. Use when asked to upload a build, distribute to testers, or release to production.

Why use Gplay Release Flow on TypingMind?

Because you install it once and use it with any model. Gplay Release Flow 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 Release Flow 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-release-flow. 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 Release Flow?

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 Release Flow?

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

Is the Gplay Release Flow 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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