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philipludington

GameLegend

by PhilipLudington · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ✓ Security Clean
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Install in OpenClaw
/install gamelegend
Description
Game discovery and recommendations powered by GameLegend's Gameplay DNA engine. Use when users ask for game recommendations, games like a specific title, wha...
README (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

Usage Guidance
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.
Capability Analysis
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.
Capability Assessment
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.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install gamelegend
  3. After installation, invoke the skill by name or use /gamelegend
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
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.
Metadata
Slug gamelegend
Version 1.0.0
License MIT-0
All-time Installs 0
Active Installs 0
Total Versions 1
Frequently Asked Questions

What is GameLegend?

Game discovery and recommendations powered by GameLegend's Gameplay DNA engine. Use when users ask for game recommendations, games like a specific title, wha... It is an AI Agent Skill for Claude Code / OpenClaw, with 209 downloads so far.

How do I install GameLegend?

Run "/install gamelegend" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is GameLegend free?

Yes, GameLegend is completely free, licensed under MIT-0. You can download, install and use it at no cost.

Which platforms does GameLegend support?

GameLegend is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created GameLegend?

It is built and maintained by PhilipLudington (@philipludington); the current version is v1.0.0.

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