agentleFS
Sign inStart free
krutikJainkrutikJain/android-agent-skills/.github/skills/android-ci-cd-release-playstore/SKILL.md

android-ci-cd-release-playstore

Skill14 starsChanged 8 months agoMITView on GitHub

Automate Android CI, versioning, signing boundaries, release channels, and Play-ready delivery workflows.

The file

We split this skill into the rules it gives an agent

5 rules. About 0 are common, 5 are distinctive, and 0 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈5

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 0

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Use this skill when the request is about: android ci cd pipeline, play store release automation, android signing and release.

    line 17
  2. Distinctive:

    Run the relevant checks on the showcase apps and packaging outputs.

    line 27
  3. Distinctive:

    Prefer reproducible checks in CI over one-off local heroics.

    line 31
  4. Distinctive:

    Keep secrets, signing material, and production credentials out of examples and fixtures.

    line 33
  5. Distinctive:

    Treat performance and security work as engineering tasks with evidence, not folklore.

    line 34

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Android CI CD Release PlayStore

When To Use

  • Use this skill when the request is about: android ci cd pipeline, play store release automation, android signing and release.
  • Primary outcome: Automate Android CI, versioning, signing boundaries, release channels, and Play-ready delivery workflows.
  • Handoff skills when the scope expands:
  • android-gradle-build-logic
  • android-security-best-practices

Workflow

  1. Scope the risk surface: correctness, security, performance, test depth, or release automation.
  2. Pick the narrowest verification strategy that still catches the likely regressions.
  3. Instrument the workflow so failures are actionable rather than just red.
  4. Run the relevant checks on the showcase apps and packaging outputs.
  5. Capture any residual risk with explicit follow-up work and owner skills.

Guardrails

  • Prefer reproducible checks in CI over one-off local heroics.
  • Fail with a precise remediation path instead of a vague quality gate.
  • Keep secrets, signing material, and production credentials out of examples and fixtures.
  • Treat performance and security work as engineering tasks with evidence, not folklore.

Anti-Patterns

  • Adding more tests without increasing signal.
  • Shipping benchmarks or security scans that no one can reproduce.
  • Hard-coding release credentials into build logic.
  • Using synthetic metrics with no user-impact interpretation.

Examples

Happy path

  • Scenario: Validate the repo CI workflow, adapter generation, and version metadata flow.
  • Command: python3 scripts/validate_repo.py

Edge case

  • Scenario: Check canary and stable release script behavior before tagging.
  • Command: python3 scripts/release.py --channel canary --dry-run

Failure recovery

  • Scenario: Avoid routing pure build-logic or security work into release automation.
  • Command: python3 scripts/eval_triggers.py --skill android-ci-cd-release-playstore

Done Checklist

  • The implementation path is explicit, minimal, and tied to the right Android surface.
  • Relevant example commands and benchmark prompts have been exercised or updated.
  • Handoffs to adjacent skills are documented when the request crosses boundaries.
  • Official references cover the chosen pattern and the main migration or troubleshooting path.

Official References

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

Check your setup, free