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Game Design Core Loop Extractor

作者 Stanislav Stankovic · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ✓ 安全检测通过
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在 OpenClaw 中安装
/install game-design-core-loop-extractor
功能描述
Extract the actual core loop from a game, feature set, or pitch based on repeated player actions, feedback, rewards, and renewed motivation. Use when a team...
使用说明 (SKILL.md)

Game Design Core Loop Extractor

Extract the actual repeatable loop that drives the experience, not a decorative feature list pretending to be structure.

Use this skill when a team can describe mechanics, systems, and content, but not the recurring action-feedback-motivation cycle that keeps the game alive. The job is to identify what the player repeatedly does, what the game gives back, why the player wants to do it again, and where the loop is broken, bloated, or fake.

Read references/family-conventions.md when you want the shared style, prioritization, and diagnosis rules for this game-design skill family. Read references/output-patterns.md when you want the preferred recommendation and minimal-fix structure.

Core principle

A core loop is not just a sequence of actions. It is a repeatable motivational circuit.

A useful loop definition identifies:

  • what the player does
  • what the game returns
  • what state changes as a result
  • why the player wants to re-enter the loop

If the loop cannot explain why the player comes back for another cycle, it is incomplete.

What to produce

Generate:

  1. Extracted core loop - the clearest repeatable loop implied by the design
  2. Loop step breakdown - the key stages in order
  3. Loop drivers - what reward, pressure, tension, or fantasy pulls the player back in
  4. Loop breaks and dead steps - where the loop is weak, bloated, confusing, or non-motivating
  5. Design implications - what to simplify, strengthen, cut, or separate

Process

1. Define the extraction target

Clarify:

  • what exact game, feature set, or slice is being analyzed
  • whether you are extracting the top-level game loop or a sub-loop
  • whether a claimed loop already exists in the documentation

Write:

  • Extraction target
  • Loop scope
  • Claimed loop if any

2. Identify the repeated player cycle

Ask:

  • What does the player do over and over?
  • What starts the cycle?
  • What ends one cycle and begins the next?
  • What resource, state, knowledge, or opportunity changes each time?

Look for actual recurrence, not one-time setup or occasional side systems.

3. Break the loop into action, feedback, reward, and renewed intent

For each stage, identify:

  • Player action
  • Game response
  • Reward or consequence
  • Reason to continue

Useful questions:

  • What is the player's immediate objective?
  • What result does the game return?
  • What makes the next cycle attractive or necessary?
  • Where does tension accumulate or release?

4. Distinguish core loop from support systems

Separate:

  • the actual core loop
  • progression loops
  • economy loops
  • meta loops
  • social loops
  • retention wrappers

A design often has many loops. Do not confuse scaffolding with the main engine.

Ask:

  • If optional layers vanished, what loop would still define the game minute to minute?
  • Which systems amplify the loop versus merely decorate it?

5. Test the loop for motivational completeness

Check whether the loop contains:

  • clear initiation
  • meaningful action
  • readable feedback
  • satisfying reward or consequence
  • a genuine reason to repeat

Common failure signs:

  • one or more steps are vague
  • reward does not materially matter
  • repetition exists without renewed motivation
  • the loop is really several disconnected chains awkwardly stapled together
  • the loop is too long to feel cyclical

6. Identify dead steps, bloat, and false loops

Look for:

  • steps that do not change player state meaningfully
  • chores inserted between meaningful beats
  • feedback that is too weak to reinforce repetition
  • loops that are structurally present but emotionally flat
  • claimed loops that are really just content progression, not recurrence

7. Write the extracted loop clearly

Prefer a concise format such as:

  • Observe -> choose -> act -> resolve -> gain -> re-enter or
  • Explore -> fight -> earn -> upgrade -> explore again

Then explain why this loop has pull.

8. Convert the loop into design implications

For each important part of the loop, specify:

  • Loop step
  • Current strength or weakness
  • What to change
  • Expected effect on repeat engagement

Examples:

  • weak reward read -> improve feedback and clearer state change
  • bloated transition step -> shorten or remove the chore layer
  • no renewed tension -> add scarcity, discovery, escalation, or strategic consequence

Response structure

Use this structure unless the user asks for something else:

Extraction Target

  • ...

Extracted Core Loop

  • ...

Loop Step Breakdown

  • ...

Loop Drivers

  • ...

Loop Breaks and Dead Steps

  • ...

Design Implications

  1. ...
  2. ...
  3. ...

Minimal Loop Fix

  • ...

Fast mode

Use this quick pass when speed matters:

  • What does the player repeat most often?
  • What reward or state change closes the loop?
  • Why does the player want another cycle?
  • Which step is dead weight?
  • What one change would make the loop cleaner or more compelling?

Usage notes

This extractor is especially useful for:

  • concept definition
  • pitch sharpening
  • prototype evaluation
  • identifying feature sprawl
  • clarifying the minute-to-minute game engine
  • separating real engagement structure from progression wallpaper

Common patterns to watch for:

  • many teams describe systems, not loops
  • progression is often mistaken for the core loop
  • a long chain of actions is not automatically a loop
  • if the loop depends entirely on external rewards, the core loop may be weak
  • if nobody can state the loop in one breath, it is probably muddy

Working principle

A game stays alive because something in it closes cleanly enough, changes enough, and promises enough to make repetition feel meaningful.

Use this skill to identify that engine and expose where it is sputtering.

安全使用建议
This skill appears safe and coherent: it only contains authoring instructions and two reference docs and does not request credentials or install code. Before using it, avoid supplying sensitive secrets or private production data in the input you ask it to analyze (the skill will produce text outputs based on whatever you give it). If you want extra assurance, review the outputs on representative non-sensitive examples first. No additional red flags were found.
功能分析
Type: OpenClaw Skill Name: game-design-core-loop-extractor Version: 1.0.0 The skill bundle is a legitimate game design analysis tool designed to help an AI agent extract and evaluate 'core loops' from game documentation. The files (SKILL.md, references/family-conventions.md, and references/output-patterns.md) contain only markdown instructions, stylistic guidelines, and formatting templates focused on game mechanics and player motivation. There is no executable code, no evidence of data exfiltration, and no prompt-injection attempts to subvert the agent's behavior for malicious purposes.
能力评估
Purpose & Capability
Name/description (extract a game's core loop) match the SKILL.md content and the included reference files. The skill is instruction-only and does not request binaries, environment variables, or config paths that would be unnecessary for a design-extraction task.
Instruction Scope
Runtime instructions are limited to reading the provided reference docs and producing an analysis (extraction, breakdown, drivers, fixes). There are no directives to read arbitrary system files, call external endpoints, or access secrets. The guidance is specific rather than open-ended.
Install Mechanism
No install spec or code files are present; the skill is instruction-only so nothing is written to disk or downloaded at install time.
Credentials
The skill declares no required environment variables, credentials, or config paths, which is proportional for a text-analysis/design skill.
Persistence & Privilege
always is false and the skill is user-invocable; autonomous invocation is allowed by platform default but there are no other privileged settings or actions requested by the skill.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install game-design-core-loop-extractor
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /game-design-core-loop-extractor 触发
  4. 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v1.0.0
Initial release
元数据
Slug game-design-core-loop-extractor
版本 1.0.0
许可证 MIT-0
累计安装 0
当前安装数 0
历史版本数 1
常见问题

Game Design Core Loop Extractor 是什么?

Extract the actual core loop from a game, feature set, or pitch based on repeated player actions, feedback, rewards, and renewed motivation. Use when a team... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 53 次。

如何安装 Game Design Core Loop Extractor?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install game-design-core-loop-extractor」即可一键安装,无需额外配置。

Game Design Core Loop Extractor 是免费的吗?

是的,Game Design Core Loop Extractor 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

Game Design Core Loop Extractor 支持哪些平台?

Game Design Core Loop Extractor 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。

谁开发了 Game Design Core Loop Extractor?

由 Stanislav Stankovic(@stanestane)开发并维护,当前版本 v1.0.0。

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