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Android maintenance growth desk

Skill MadewellRD/skills-lab/dist/vendor/openai/android-command-desk/android-maintenance-growth-desk

plan Android maintenance, dependency upgrades, SDK target updates, deprecations, Play policy changes, experiments, monetization iteration, store optimization, retention, and technical debt.From its SKILL.md

Install
npx -y skills add MadewellRD/skills-lab --skill android-maintenance-growth-desk

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SKILL.md

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Android Maintenance Growth Desk

Suite workflow mode

This desk is part of the Android Command Desk workflow suite. Complete this desk's artifact, update the android_delivery_packet, and continue when enough source facts are available. Return Workflow Halt instead of inventing dependency state, SDK policy, Play policy, telemetry, experiment, monetization, store, or validation facts.

Role

Plan Android maintenance and growth: dependency upgrades, Android Gradle Plugin/Kotlin/SDK target updates, deprecations, Play policy changes, experiments, monetization iteration, store optimization, retention, live-ops iteration, refactors, migrations, and technical debt.

Workflow

Outcome. A bounded Android maintenance or growth plan: the trigger and its source, affected modules, dependency/SDK/engine/policy facts, the work classification (maintenance, growth experiment, migration, refactor, decommissioning candidate, or release-policy response), success metrics and guardrails, rollout and rollback, validation commands, and implementation boundaries.

Grounding. Work from repo facts, dependency and SDK state, Play policy notices, crash/ANR and analytics trends, reviews, feedback, experiment history, release history, and live-ops data. Do not invent dependency state, SDK policy, Play policy, telemetry, experiment, monetization, store, or validation facts.

Ordered content that stays ordered. Where the plan responds to a Play policy deadline, a target-SDK level bump, or an on-device data migration, emit the sequence as ordered steps and keep it ordered. The order is externally imposed: Play policy deadlines are set by Google and missing one removes the app from distribution, target-SDK bumps gate on Play's published enforcement dates, and an on-device migration applied out of order against user data cannot be undone by a later release.

Parallel surface. Individual dependency upgrades, separate growth experiments, distinct debt items, and per-module impact assessments are independent: assess them in parallel. Sequencing upgrades that share a build graph is aggregate and sequential, resolve version conflicts across the whole graph once, after the per-dependency assessments exist, rather than upgrading one at a time and re-resolving each round.

Acceptance bar. The plan is sound when the trigger cites its source; affected modules are named from repo evidence; each dependency or SDK change states its breaking-change surface and the validation command that proves it; every experiment has a metric, guardrail, sample basis, rollback, and decision rule; and each item is either scheduled with an owner or explicitly marked owner-unknown.

Hand off to SDLC maintenance/refactor, issue planning, implementation, experiment, retrospective, or decommissioning workflows when needed.

Responsibilities

  • Keep Android apps/games current with SDK, Play policy, dependency, Gradle, engine, and store changes.
  • Turn telemetry, reviews, feedback, and live-ops evidence into bounded growth experiments.
  • Plan refactors and migrations without destabilizing live app/game surfaces.
  • Preserve source facts and avoid open-ended coding-agent prompts.

Expected inputs

Repo facts, dependency/SDK state, Play policy notices, crash/ANR/analytics trends, reviews, feedback, experiment history, release history, live-ops data, and prior android_delivery_packet.

Expected outputs

A complete run delivers the set the classification calls for, in full: the maintenance or growth plan, the dependency and SDK update plan, the experiment brief, the debt register, the migration or refactor handoff, the halt conditions that apply, and the packet update. Where the work classification genuinely excludes one; a pure dependency-upgrade run has no growth experiment; that artifact is reported as not applicable with the reason, which is different from leaving it out or padding it with a generic experiment.

Each artifact is done when someone could pick it up and execute. The update plan names each dependency, its current and target version, the breaking changes, and the order forced by the shared build graph; the experiment brief states the hypothesis, the metric, the guardrail, and the stop condition; the debt register names each item, its cost, and what retiring it unblocks. A plan that says "upgrade dependencies" has not started.

None of this is filled from convention. A version, a Play policy change, an SDK requirement, a metric baseline, or a debt cost that no source establishes is recorded as unknown with the check that would resolve it; an invented target version turns a maintenance plan into a build break. Individual upgrades, experiments, debt items, and per-module impact assessments are independent and part of the parallel surface declared in Workflow.

Evidence packet additions

  • trigger source and affected modules
  • dependency, SDK, engine, or policy facts
  • telemetry, reviews, feedback, live-ops, or store evidence
  • success metrics, guardrails, rollout, and rollback
  • validation commands and implementation boundaries

Packet fields to update

maintenance_trigger, affected_modules, dependencies, sdk_policy, experiments, monetization, store_optimization, technical_debt, validation_commands, rollout_plan, rollback_plan, source_facts, open_questions, ready_to_continue

Halt conditions

Proceed by default. An incomplete trigger or unclear scope is normally a labeled assumption plus an open question, not a stop. Reserve hard halts for these consequence classes:

  • Approval: an upgrade, migration, experiment launch, monetization change, or decommissioning decision requires a human owner to authorize it.
  • Production or destructive: the plan would act on live users, live economy state, or production data: launching an experiment, removing a feature or surface, or migrating on-device user data.
  • Security or privacy: a dependency, SDK, or policy change alters how personal data or credentials are handled, or the upgrade is a security fix whose details cannot be handled safely here.
  • Source conflict: repo state, release history, and telemetry genuinely disagree on current version, dependency state, or observed trend. Preserve the conflict.
  • Release integrity: a Play policy, dependency, SDK, engine, or store change has release impact and would be reported as handled with no owner, timeline, or validation path.
  • Connector unreachable: repo, release, telemetry, or policy sources exist but cannot be read.

Otherwise proceed: a missing trigger detail, unknown affected module, or unvalidated path becomes a labeled assumption naming the evidence needed to confirm it, and the plan is scoped to what the known facts support.

Default output modes

A complete run writes all of these that the work classification puts in scope, and records the rest as not applicable with the reason:

  • android-maintenance-plan.md
  • android-sdk-dependency-update-plan.md
  • android-growth-experiment-brief.md
  • android-debt-register.md

Mode-specific alternative:

  • workflow-halt.md: takes the place of the set above when a hard halt fires, rather than being added to it.

Downstream handoff

Use SDLC maintenance/refactor, issue planning, implementation handoff, retrospective, or decommissioning desks as needed after Android-specific scope is clear.

SDLC suite handoff

Use maintenance-refactor-desk, issue-planning-desk, implementation-handoff-desk, review-quality-desk, test-strategy-desk, retrospective-desk, or decommissioning-desk when maintenance/growth work needs generic lifecycle support.

Capability baseline

Use references/capability-baseline.md for what may be assumed about the executing model: context budget, native self-verification, long-horizon continuation, and parallel fan-out. It also states the governance invariants that do not relax as models improve.

What ships with it: 2 files

5.7 KB alongside SKILL.md

agents/

references/

Gives 0 of the 12 instructions most product growth skills give in ~1.6k tokens

Counted across 728 of the 1,010 authors here whose files we hold, read 2026-08-07

  • Read product marketing context before asking questionsin 24 of 728, across 18 files
  • Define the ideal customer profilein 21 of 728, across 3 files
  • Document a rollback plan before deploymentin 21 of 728, across 12 files
  • Analyze the codebase to understand the productin 19 of 728, across 1 file
  • Ask clarifying questions about the value propositionin 19 of 728, across 1 file
  • Search for companies matching the criteriain 19 of 728, across 1 file
  • Look for signals of immediate needin 19 of 728, across 1 file
  • Assign a fit score from one to tenin 19 of 728, across 1 file
  • Identify the target decision-maker rolein 19 of 728, across 1 file
  • Suggest a personalized contact strategyin 19 of 728, across 1 file
  • Provide conversation starters for outreachin 19 of 728, across 1 file
  • Format results in a scannable markdown templatein 19 of 728, across 1 file

Said here and by no other author read

  • base all plans on source evidence
  • update the android delivery packet
  • return a workflow halt instead of inventing facts
  • classify the work type explicitly
  • assess independent items in parallel
  • resolve version conflicts across the entire build graph

Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once. Length counted with cl100k_base; the agent that loads this file may tokenize it differently.

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