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Game Design Feature Prioritization

Community
Stanestane
game-design-feature-prioritization

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.

Overview

PublisherStanestane
Repositorygame-design-skills-bundle
Skill namegame-design-feature-prioritization
Stars
87
Forks
18
Bundled files
1
Links
Skill sourceRepositoryHomepage
  • 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 Stanestane on GitHub. Read the source before you install it.

Installation

Install the Game Design Feature Prioritization 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.
    https://github.com/Stanestane/game-design-skills-bundle/tree/master/game-design-feature-prioritization
  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/Stanestane/game-design-skills-bundle.git /tmp/game-design-skills-bundle
mkdir -p .claude/skills
cp -r /tmp/game-design-skills-bundle/game-design-feature-prioritization .claude/skills/game-design-feature-prioritization
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Game Design Feature Prioritization 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 Game Design Feature Prioritization 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 Game Design Feature Prioritization 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.

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

OptionImpactCostStrategic FitRiskTimingNotes

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.

Part of the Game Design Skills Bundle by Stanislav Stankovic. Licensed under PolyForm Noncommercial 1.0.0 — free for personal, academic and nonprofit use. Commercial use requires a licence, sold as skill packs. See https://github.com/Stanestane/game-design-skills-bundle for terms.

Required Notice: Copyright Stanislav Stankovic (https://www.stane-island.net/)

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 Game Design Feature Prioritization AI skill do?

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.

Why use Game Design Feature Prioritization on TypingMind?

Because you install it once and use it with any model. Game Design Feature Prioritization 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 Game Design Feature Prioritization in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Stanestane/game-design-skills-bundle/tree/master/game-design-feature-prioritization. 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 Game Design Feature Prioritization?

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 Game Design Feature Prioritization?

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

Is the Game Design Feature Prioritization AI skill free?

It is published on GitHub by Stanestane. Check the repository for licensing terms. 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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