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game-prototype-loop

game-prototype-loop

github.com/lvtd-llcCreative & media160 installsUpdated 7w ago
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About game-prototype-loop

A game-design skill for turning broad ideas into testable, buildable experiments. It prioritizes risky assumptions and defines prototypes, success signals, and iteration decisions for design teams and coding agents.

Key features

  1. 01Frames intent as a design problem
  2. 02Ranks assumptions by risk
  3. 03Selects a prototype for each major risk
  4. 04Defines success signals and decision criteria
  5. 05Guides iterative testing and build work

Use cases

  1. 01Testing whether a core mechanic is fun
  2. 02Checking control or feasibility assumptions early
  3. 03Choosing what to cut, change, or develop

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/lvtd-llc/skills --skill game-prototype-loop

After installing, type/game-prototype-loopin Claude Code to confirm it loaded.

Bundled filesreferences/core/guide.mdworkflows/risk-first-prototype.md

Details

From the project README

Game Prototype Loop

Use this skill to convert vague game intent into buildable experiments. The default stance is risk-first: identify what must be true for the game to work, then build the cheapest prototype that can answer that question.

Source Traceability

Primary source: The Art of Game Design: A Book of Lenses, Third Edition by Jesse Schell, especially chapters 7-8 on idea generation, problem statements, filters, risk, prototyping, and iteration. The workflow is transformed and paraphrased from those ideas rather than copied.

Supporting source: Hunicke, LeBlanc, and Zubek's MDA framework for separating mechanics, dynamics, and aesthetics during prototype evaluation.

Workflow

  1. State the target player experience in one sentence.
  2. Reframe the idea as a design problem with constraints, not as a feature list.
  3. List the riskiest assumptions: fun, clarity, feasibility, controls, production cost, content burden, performance, market fit, and multiplayer or systems complexity.
  4. Choose one prototype per major risk. Prefer paper, spreadsheet, greybox, or throwaway code before production code.
  5. Define the prototype's success signal before building it.
  6. Run the build-play-observe-decide loop until the risk is retired, reframed, or accepted.
  7. Convert learning into a next action: cut, keep, change, defer, or productionize.

Required Output

When invoked, produce:

  • Design Problem: the player-facing experience and constraints.
  • Assumption Map: ranked risks with why each matters.
  • Prototype Plan: prototype type, scope, build time, success signal, and kill/change criteria.
  • Iteration Loop: cadence, test method, evidence to collect, and next decision.
  • Build Notes: exact implementation guidance for the coding agent.

Local References

Before producing a full plan, read:

  • references/core/guide.md
  • workflows/risk-first-prototype.md

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