mcpField
G
game-soft-launch-review

game-soft-launch-review

github.com/sylphxaiMarketing & growth146 installsUpdated today
Repository

About game-soft-launch-review

A marketing skill for planning and reviewing a game's soft launch. It structures cohort-based evaluation across product, monetization, technical readiness, acquisition, and store tests, producing gates and a scale, iterate, or stop decision record.

Key features

  1. 01Soft-launch context definition
  2. 02Cohort gates across key metrics
  3. 03Separation of learning and monetization tests
  4. 04Live-ops and instrumentation planning
  5. 05Scale, iterate, or stop decision record

Use cases

  1. 01Plan a regional game soft launch
  2. 02Compare cohort results before scaling acquisition
  3. 03Review retention, economy, and crash gates

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/sylphxai/skills --skill game-soft-launch-review

After installing, type/game-soft-launch-reviewin Claude Code to confirm it loaded.

Bundled filesagents/openai.yamlreferences/game-soft-launch-patterns.md

Details

From the project README

Game Soft Launch Review

Use this skill to convert a high-stakes product decision into a concrete, measurable, reviewable operating artifact.

Workflow

  1. Identify game genre, target market, test region, acquisition source, monetization model, core loop, and launch decision horizon.
  2. Read references/game-soft-launch-patterns.md.
  3. Define cohort gates across retention, session quality, economy, IAP, ads, crashes, store conversion, support, and community sentiment.
  4. Separate product learning, monetization tuning, technical readiness, acquisition quality, and creative/listing tests.
  5. Produce soft-launch plan, gate matrix, live-ops calendar, instrumentation, and scale/iterate/kill decision record.

When not to use

  • Do not use for generic advice the base model already handles without this skill's specific artifact contract.

Guardrails

  • Do not scale paid acquisition from blended metrics that hide low-quality cohorts.
  • Do not over-monetize early cohorts in ways that invalidate retention learning.
  • Do not treat one test market as global proof without market-fit caveats.
  • Protect player trust around economy resets, purchases, ads, and support during test periods.

Output format

Soft-launch context:
Game / market / cohort / monetization:

Gate matrix:
| Gate | Metric | Segment | Pass | Watch | Stop | Action |
| --- | --- | --- | --- | --- | --- | --- |

Live-ops and economy review:
- <event/economy/ad/IAP/support item>

Decision record:
- <scale / iterate / hold / kill with evidence>

Comments

Markdown supported