Token导航 LogoToken导航

Agent Skill · 研究检索

abstract-strategy(抽象策略)

abstract-strategy 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

abstract-strategy 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为需要联网;许可证为 MIT,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 19,839。

总安装 5,438周安装 220GitHub Stars 67下载 1,707核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:abstract-strategy(抽象策略)
来源仓库:https://github.com/jwynia/agent-skills
仓库路径:skills/abstract-strategy
安装命令:
npx skills add https://github.com/jwynia/agent-skills --skill abstract-strategy
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。不同来源提供的安装方式可能略有差异;本站展示可直接复制的安装命令,安装前请核对来源页面。

skills.shnpx skills
npx skills add https://github.com/jwynia/agent-skills --skill abstract-strategy

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

用于设计抽象策略类游戏,聚焦完美信息、无随机性和深度战略机制。提供游戏框架构建、机制设计与评估方法,强调玩家决策主导性。适用于开发如 Hex、Go、Chess 类纯策略型桌游或数字游戏原型。

安装命令:npx skills add https://github.com/jwynia/agent-skills --skill abstract-strategy 支持 Codex、Claude、Cursor、Gemini CLI,通过 GitHub 安装。

来源仓库内路径:skills/abstract-strategy

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/jwynia/agent-skills --skill abstract-strategy;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要需要联网,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

abstract-strategy 怎么安装?

在终端执行 npx skills add https://github.com/jwynia/agent-skills --skill abstract-strategy。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

abstract-strategy 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

abstract-strategy 需要什么权限?

权限级别是需要联网。该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

abstract-strategy 是免费的吗?

来源标注的许可证是 MIT。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

abstract-strategy 用的人多吗?

公开数据是累计安装 5,438 次,近一周安装 220 次,下载 1,707 次,GitHub 67 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

abstract-strategy 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 3 个目录同时收录,说明这个 Skill 流传比较广。
  • 许可证明确为 MIT,商用和分发边界好判断。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。
  • 需要许可证清楚、并且有第三方扫描结果的团队项目。

不太适合

  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
abstract-strategy

抽象策略 · 本页

5,43867需要联网MIT通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

Abstract Strategy Game Design

Purpose

Design abstract strategy games—games with perfect information, no randomness, and strategic depth. Provides frameworks for ideation, design, and evaluation.

Core Definition

Abstract strategy games require:

  • Perfect Information: All game state visible to all players
  • No Randomness: Outcomes determined solely by player decisions
  • Minimal Theme: Mechanics over narrative
  • Player Agency: Success depends on strategic thinking

Quick Reference: Game Types

TypeCore MechanicExamples
ConnectionForm paths/networksHex, TwixT
TerritoryControl areasGo, Othello
CaptureEliminate piecesChess, Checkers
PatternCreate arrangementsGomoku, Pentago
RacingReach goal firstChinese Checkers

Design Principles

The Holy Grail: Depth-to-Complexity Ratio

Maximum strategic depth with minimum rules complexity.

How to achieve:

  • Start with single strong core mechanism
  • Remove anything that doesn't support the core
  • Every rule should create multiple strategic implications
  • Prefer emergent complexity over explicit rules

Meaningful Decision Architecture

Four components of meaningful choice:

  1. Awareness: Players understand options
  2. Consequence: Immediate and long-term effects
  3. Permanence: Decisions have lasting impact
  4. Reminders: Game state reflects past choices

Ideal Parameters:

  • Branching factor: 20-40 moves/turn for human play
  • Horizon: 3-5 moves ahead with effort
  • Multiple paths: 3-4 viable strategies minimum

Core Mechanisms Toolkit

Board Topology

  • Grids: Square, hexagonal, triangular, irregular
  • Connectivity: How spaces relate
  • Edges: How boundaries affect strategy
  • Size: Larger = exponentially more complex

Piece Systems

  • Uniform: All pieces identical (Go)
  • Differentiated: Unique abilities (Chess)
  • Transforming: Change during play (Checkers kings)
  • Ownership: Fixed vs. capturable

Movement & Placement

  • Placement only: Pieces don't move once placed (Go)
  • Movement only: Pieces start on board (Chess)
  • Hybrid: Both placement and movement (Hive)

Victory Conditions

  • Elimination, Position, Pattern, Territory, Points, Stalemate

Balance Considerations

First-Player Advantage Mitigation

  • Pie Rule: Second player can swap after first move
  • Komi: Point compensation for second player
  • Variable Setup: Randomized starting positions
  • Simultaneous: Both move at once

Avoiding Degenerate Strategies

  • No single dominant path
  • Counter-strategies exist for every strong position
  • Passive play punishable
  • Aggressive play doesn't guarantee victory

Design Process

Three Starting Points

1. Mechanism-First

  1. Identify interesting core mechanic
  2. Build minimal game around it
  3. Add only what enhances core
  4. Remove everything else

2. Experience-First

  1. Define target player experience
  2. Identify mechanisms that create it
  3. Prototype and test rapidly
  4. Iterate on feedback

3. Constraint-Based

  1. Set specific limitations (components, time, space)
  2. Find creative solutions within constraints
  3. Often leads to elegant designs

When to Add/Remove Complexity

Add when:

  • Core feels solved too quickly
  • Players master in <10 plays
  • Decisions feel obvious

Remove when:

  • Rules take >10 minutes
  • Players forget rules
  • Strategies feel arbitrary

Scrap when:

  • No tweaking fixes fundamentals
  • Core mechanism isn't interesting
  • Feels like inferior version of existing game

Brainstorming Techniques

1. Mechanism Extraction from Non-Games

Extract from physics, biology, economics, chemistry, social systems:

  • Pieces that "decay" unless refreshed (entropy)
  • Moves creating "waves" along patterns (physics)
  • Pieces forming "bonds" limiting movement (chemistry)
  • "Market" squares with fluctuating values (economics)

2. Extreme Property Isolation

Take one property to absolute extreme:

  • Game where pieces visible only when adjacent to your others
  • Every move must maintain rotational symmetry
  • Pieces exist only one turn unless refreshed
  • Board wraps in non-intuitive ways (Klein bottle)

3. Impossible Constraint Challenges

Start with seemingly impossible constraints:

  • Game on a 1D line
  • Pieces in probability clouds until observed
  • Victory condition voted on by piece positions
  • Pieces leave "trails" becoming new pieces

4. Anti-Pattern Starting Points

Design intentionally bad games, then invert:

  • Always-draw game → Add accumulating positional advantages
  • Pure calculation → Add pieces that change rules
  • Dominant strategy → Make it vulnerable to specific counters

5. Mathematical Structure Mining

  • Pieces move along Hamiltonian paths only
  • Positions valued by prime factorization
  • Fractal boards with repeating patterns
  • Moves must preserve mathematical invariants

Evaluation Framework

Strategic Richness Indicators

Depth:

  • Games last 20+ meaningful turns
  • Opening, midgame, endgame feel distinct
  • Multiple viable opening strategies
  • Comebacks possible but not trivial

Complexity:

  • New players grasp rules in <5 minutes
  • Experts keep discovering patterns
  • High-level play looks different from beginner

Common Failures

ProblemSymptomsSolution
Analysis ParalysisExcessive turn timeLimit options, clearer objectives
Solved GameSame outcome alwaysIncrease branching, add variety
KingmakerLoser picks winnerSimultaneous resolution

Testing Protocol

Phase 1: Proof of Concept

  • Test core mechanic in isolation
  • Verify basic fun factor
  • Identify broken strategies

Phase 2: Mechanics

  • Test each subsystem
  • Look for unintended interactions
  • Measure game length

Phase 3: Integration

  • Full game, all systems
  • Different skill levels
  • Quantitative data

Phase 4: Blind Testing

  • Players learn from rulebook only
  • Identify ambiguities
  • Test learning curve

Testing Checklist

Mechanical

  • All rule interactions verified
  • Edge cases resolved
  • Victory achievable but not trivial
  • No unbreakable stalemates

Balance

  • First player wins 45-55%
  • Multiple strategies win regularly
  • No dominant opening
  • Skill affects outcome

Experience

  • Games complete in target time
  • Players want rematch
  • Decisions feel meaningful
  • Players improve with practice

Accessibility

  • Rules learned in <5 minutes
  • Rules fit one page
  • No ambiguous situations
  • Components distinguishable

Quick Evaluation Filters

30-Second Test: Can you explain core concept in 30 seconds?

Originality Test: Does it feel like variant of existing game?

Decision Test: Are there obviously interesting decisions?

Depth Test: Could this sustain interest for 50+ plays?


Session Structure (2 Hours)

  1. 10 min: Pick 3-4 brainstorming techniques
  2. 60 min: Generate 15-20 ideas per technique
  3. 20 min: Expand 5-10 promising ideas
  4. 20 min: Combine and explore hybrids
  5. 10 min: Apply filters, select for prototyping

Anti-Patterns

1. Complexity as Depth

Pattern: Adding rules, exceptions, and special cases to make the game feel "deeper." Why it fails: Complexity and depth are different. Complex rules create burden; depth emerges from simple rules with rich interactions. Chess has simpler rules than many shallow games. Fix: Ruthlessly remove complexity that doesn't add strategic options. If a rule requires explanation but doesn't create interesting decisions, cut it.

2. Solved Game Blindness

Pattern: Creating a game where optimal play always produces the same outcome—often draws or first-player wins. Why it fails: Once players discover the solution, the game becomes rote execution rather than strategic exploration. No amount of polish fixes a solved game. Fix: Test extensively with strong players. If games start converging on identical patterns, add asymmetry or increase branching factor. The pie rule helps but doesn't solve fundamental issues.

3. Decision Paralysis

Pattern: Every position has dozens of equally viable options with unclear consequences. Why it fails: Strategic games need meaningful comparison between choices. When all options seem equivalent, decisions become random rather than strategic. Fix: Reduce branching factor or create clearer evaluation heuristics. Players should be able to identify 3-5 promising moves without analyzing every possibility.

4. Theme Creep

Pattern: Adding narrative or thematic elements that don't connect to mechanical decisions. Why it fails: Abstract strategy games work because mechanics are the content. Theme that doesn't inform decisions is decoration that slows play without adding depth. Fix: Either commit to a themed game (different framework) or keep theme purely cosmetic. Don't let theme suggest mechanics that don't serve strategy.

5. Perfect Information Violations

Pattern: Adding hidden information, simultaneous resolution, or dice "for variety." Why it fails: Abstract strategy games are defined by perfect information and determinism. Adding randomness or hidden elements creates a different game type with different design principles. Fix: If the game needs variety, add it through board setup, victory condition selection, or piece starting positions—not through mid-game randomness.

Integration

Inbound (feeds into this skill)

SkillWhat it provides
brainstormingIdeation techniques for mechanism discovery
researchHistorical game analysis and mathematical structure research

Outbound (this skill enables)

SkillWhat this provides
(playtesting)Designs ready for player validation
(rulebook writing)Tested mechanics ready for documentation

Complementary

SkillRelationship
brainstormingUse brainstorming for raw idea generation; abstract-strategy provides evaluation and refinement frameworks

平台分布

Claude Code

28.55%
按下载量换算487

OpenCode

22.34%
按下载量换算381

Antigravity

18.8%
按下载量换算321

Codex

10.88%
按下载量换算186

Gemini CLI

7.76%
按下载量换算132

windsurf

3.68%
按下载量换算63

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。

继续浏览同类 Skills