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Game Design Feature Prioritization

该 Skill 用于在多个游戏设计功能或方案之间做取舍:先列出候选,再按影响、实现成本、战略契合、风险与时机做 1-5 分结构化评分,结合路线图排序,将每个候选归为立即做、先验证、以后做或暂缓,并给出下一步建议。输出为文本形式的候选清单、评估矩阵、优先级排序与推荐理由,另附快速模式提问和共享约定参考文件。

stanestane
stanestane
热度 43.43
最近更新 2026-05-11 17:44:51
分类:数据依赖:纯提示词应用场景:推荐 / 报告撰写 / 任务管理

安装技能

复制下面的话术发给你的 Agent,它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill: npx secure-skills-cli add game-design-feature-prioritization
Metadata
name
game-design-feature-prioritization
description
Prioritize game design feature options by comparing expected impact, implementation cost, strategic fit, and roadmap context. Use when choosing between competing feature ideas, deciding what to do now versus later, ranking solution paths after ideation, or identifying which option is best immediately and which is better long-term.

Game Design Feature Prioritization

Choose the strongest next move, not just the loudest idea.

Use this skill to compare candidate features or solution paths and decide what should happen now, later, or not at all. Keep the process practical. Rough structured judgment is better than fake precision, but explicit comparison is still useful.

Read references/family-conventions.md when you need the shared conventions for this GROW-derived skill family.

What to produce

Generate:

  1. Candidate list - what is being prioritized
  2. Evaluation matrix - impact, cost, fit, risk, timing
  3. Priority ranking - now, later, discard, or monitor
  4. Recommendation - what should happen next and why

Process

1. List the candidates

Make sure the compared items are clear and meaningfully distinct.

2. Score the options

Use rough structured scoring such as 1-5 for:

  • Impact - expected player or business value
  • Implementation cost - time, resources, complexity
  • Strategic fit - alignment with game direction and roadmap
  • Risk - uncertainty, dependency burden, fragility
  • Timing - whether this is right now or later

3. Interpret in context

Do not choose purely by raw score. Also consider:

  • roadmap sequencing
  • enabling value for future features
  • opportunity cost
  • whether a slightly weaker option is smarter in the long run

4. Recommend action

For each option, classify it as:

  • Do now
  • Test first
  • Do later
  • Discard for now

Response structure

Candidates

  • ...

Evaluation Matrix

Option Impact Cost Strategic Fit Risk Timing Notes

Priority Ranking

  • ...

Recommendation

  • ...

Fast mode

  • What are we choosing between?
  • Which option has the best impact-to-cost profile?
  • Which option best fits the roadmap right now?
  • What should we do now, later, or not at all?

Working principle

The locally optimal choice is not always the strategically best one.