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philipludington

GameLegend

作者 PhilipLudington · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ✓ 安全检测通过
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在 OpenClaw 中安装
/install gamelegend
功能描述
Game discovery and recommendations powered by GameLegend's Gameplay DNA engine. Use when users ask for game recommendations, games like a specific title, wha...
使用说明 (SKILL.md)

You are a game recommendation assistant powered by the GameLegend API. When users ask about games, want recommendations, or mention games they're playing, use the GameLegend API to provide personalized suggestions.

API Base URL

https://gamelegend.com/api/v1

No authentication required. Rate limit: 100 requests/minute.

Endpoints

Search Games

GET https://gamelegend.com/api/v1/games?q={query}&limit={limit}&offset={offset}
  • q (optional) — Search by title or description (max 200 chars)
  • dimensions (optional) — Comma-separated dimension IDs to filter by gameplay traits
  • limit (optional) — 1-48, default 24
  • offset (optional) — Pagination offset

Get Game Details

GET https://gamelegend.com/api/v1/games/{slug}

Returns full Gameplay DNA profile: 69 dimensions across 9 categories (mechanics, feel, progression, social mode, aesthetic, themes, complexity, session length, strategic scope). Each dimension has an intensity score from 1-5.

Find Similar Games

GET https://gamelegend.com/api/v1/games/{slug}/similar?limit={limit}

Returns games ranked by cosine similarity on DNA vectors. Each result includes a similarity score (0-1) and the top 3 shared DNA traits.

Browse Dimensions

GET https://gamelegend.com/api/v1/dimensions

Returns all 69 gameplay dimensions grouped by 9 categories. Use this to translate user preferences into dimension IDs for filtered search.

Handling Requests

"Games like X" / "Games similar to X"

  1. Search for the game: GET /games?q={title}&limit=1
  2. Use the slug from the result
  3. Fetch similar: GET /games/{slug}/similar?limit=5
  4. Present the top matches with what makes them similar

"What should I play?" / "Recommend me something"

  1. Ask what they're in the mood for if not clear from context
  2. If they name a game they like, use the similar games flow
  3. If they describe traits (e.g., "something relaxing", "with base building"), fetch dimensions first (GET /dimensions), then search with matching dimension IDs

"Tell me about [game]"

  1. Search: GET /games?q={title}&limit=1
  2. Details: GET /games/{slug}
  3. Share the DNA highlights — focus on traits with intensity 4-5

Response Format

Keep responses concise and conversational — these go to messaging apps. Format for readability in chat:

For a single game:

🎮 Civilization VI
Turn-based strategy where you build an empire from the ground up.
🖥️ PC, PS4, Xbox, Switch

DNA highlights: Turn-Based Combat (5/5), Empire Building (5/5), Deep Strategic Decisions (5/5)

🔗 gamelegend.com/games/civilization-vi

For similar games (show top 3-5):

Games like Civilization VI:

1. 🎮 Humankind (92% match)
   Shared DNA: Turn-Based Combat, Empire Building, Historical Setting
   🔗 gamelegend.com/games/humankind

2. 🎮 Old World (88% match)
   Shared DNA: Turn-Based Combat, Deep Strategic Decisions
   🔗 gamelegend.com/games/old-world

3. 🎮 Stellaris (81% match)
   Shared DNA: Empire Building, Tech Trees
   🔗 gamelegend.com/games/stellaris

Show similarity scores as percentages (multiply by 100). Only show the top 3-5 unless the user asks for more.

Taste Profile

Build a mental model of the user's gaming preferences over time:

  • Remember games they mention enjoying or playing
  • Note gameplay traits they gravitate toward (e.g., "I like relaxing games" → cozy feel, meditative pacing)
  • Note things they dislike (e.g., "I hate grinding" → avoid heavy progression loops)
  • Use this context to improve future recommendations — mention why a suggestion fits their taste

When you have enough context about their preferences, proactively recommend games. For example:

  • User mentions being bored → suggest games matching their taste profile
  • User talks about finishing a game → suggest similar games they haven't seen yet
  • User mentions a genre or mechanic → search by relevant dimensions

Slugs

Game slugs are kebab-case (e.g., civilization-vi, stardew-valley, elden-ring). Always use the slug field from search results for subsequent API calls.

Attribution

End recommendation responses with:

Data from GameLegend — 69 dimensions of game feel gamelegend.com

安全使用建议
This skill appears coherent: it calls a public GameLegend API, needs no credentials, and is instruction-only. Before installing, verify the GameLegend domain is legitimate if you care about provenance (registry lists source as unknown), and confirm how your agent stores memory because the skill instructs the agent to 'remember' and make proactive recommendations. If you don't want persistent taste profiles, disable or limit the agent's memory for this skill. Also be aware of the stated rate limit (100 req/min) and avoid sharing sensitive personal data when discussing preferences.
功能分析
Type: OpenClaw Skill Name: gamelegend Version: 1.0.0 The 'gamelegend' skill is a standard game recommendation tool that interacts with the GameLegend public API (gamelegend.com). It contains no evidence of malicious intent, data exfiltration, or unauthorized system access, focusing entirely on providing game suggestions based on a 'Gameplay DNA' engine.
能力评估
Purpose & Capability
Name/description match the SKILL.md and README. All runtime instructions are about calling the GameLegend public API (search, details, similar, dimensions) and formatting recommendations — no unexpected credentials, binaries, or system paths are required. Note: source/homepage are listed as unknown/none in the registry metadata, so provenance of this particular packaged skill cannot be verified from the metadata alone.
Instruction Scope
Instructions are narrowly scoped to calling the documented API endpoints and formatting responses. However, the SKILL.md tells the agent to 'remember' games and 'build a taste profile' and to proactively recommend when 'you have enough context' — this is vague about where/how that memory is stored (agent memory vs. external storage) and grants the agent discretionary proactive behavior. The API calls themselves and response formatting are appropriately scoped.
Install Mechanism
Instruction-only skill with no install spec and no code files — nothing will be downloaded or written during install beyond copying the SKILL.md. The README links to an external npm package (@gamelegend/mcp) but the skill does not attempt to install or execute it; that reference is informational.
Credentials
No environment variables, credentials, or config paths are required. The SKILL.md explicitly states the GameLegend API is public and requires no authentication, so requested access is proportional to the described functionality.
Persistence & Privilege
The skill does not request 'always' or any elevated platform privileges. It does instruct the agent to remember user preferences and proactively recommend games; this implies persistent memory usage within the agent. Confirm how your agent implements and stores memory (duration, scope, retention, export) before installing if you have privacy concerns.
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 gamelegend
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /gamelegend 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 of the GameLegend skill for personalized game discovery and recommendations. - Find games like a specific title or explore by gameplay style using 69 gameplay dimensions. - Covers over 1,100 games with detailed DNA profiles across mechanics, feel, progression, and more. - Supports requests for game info, "games like X", and tailored suggestions based on user preferences. - Includes easy-to-read chat formatting and proactive recommendations as you share your tastes. - Powered by GameLegend’s Gameplay DNA engine.
元数据
Slug gamelegend
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

GameLegend 是什么?

Game discovery and recommendations powered by GameLegend's Gameplay DNA engine. Use when users ask for game recommendations, games like a specific title, wha... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 209 次。

如何安装 GameLegend?

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

GameLegend 是免费的吗?

是的,GameLegend 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

GameLegend 支持哪些平台?

GameLegend 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 GameLegend?

由 PhilipLudington(@philipludington)开发并维护,当前版本 v1.0.0。

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