Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add natea/fitfinder --skill demo-buildergit clone --depth 1 https://github.com/natea/fitfinderWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/natea/fitfinder/demo-builder)<a href="https://agentmods.dev/skills/natea/fitfinder/demo-builder"><img src="https://agentmods.dev/badge/skills/natea/fitfinder/demo-builder/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/natea/fitfinder/demo-builder"><img src="https://agentmods.dev/badge/skills/natea/fitfinder/demo-builder.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00037 | $0.05535 |
| Opus 5 | $0.00018 | $0.02767 |
| Sonnet 5 | $0.00007 | $0.01107 |
| Haiku 4.5 | $0.00004 | $0.00553 |
Grade A, and why
demo-builder scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 6d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 740 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Demo Builder Skill
Purpose
This skill automatically generates playable game prototypes from game concept documents. It:
- Parses concept documents to extract game mechanics, theme, genre
- Generates Three.js game code using the threejs-game skill
- Creates first playable level with scoring, objectives, characters
- Generates assets (textures, colors, basic models)
- Integrates music (Suno AI generation or 8-bit MIDI)
- Produces web-ready demo that runs in browser
Output: Fully functional game demo with HTML/JS/CSS that can be played immediately.
When to Use This Skill
Use this skill when you have:
- ✅ Game concept document (from brainstorming/design phases)
- ✅ Need to validate gameplay quickly with playable prototype
- ✅ Want to pitch game with interactive demo vs. static mockups
- ✅ Require rapid prototyping for playtesting
- ✅ Need proof-of-concept before full development investment
Prerequisites
Required Input
Game Concept Document (from brainstorming or design)
- Location:
/docs/*-game-concepts-*.mdor/docs/plans/*-design.md - Must include: Title, description, genre, core mechanics, theme
- Example:
fps-game-concepts-market-driven-2025-10-26.md
Dependencies
- threejs-game skill (for 3D game implementation)
- Three.js library (loaded via CDN in generated HTML)
- Optional: Suno API key for music generation (can use MIDI fallback)
Core Workflow
Phase 1: Concept Parsing
1. Load Game Concept
GameConcept = {
title: string,
description: string,
genre: string[], // ["FPS", "Extraction", "Co-op"]
theme: string, // "cyberpunk", "military", "horror", etc.
core_mechanics: string[],
target_persona: string,
price_point: number | "F2P"
}
2. Extract Demo Requirements
DemoRequirements = {
game_type: "FPS" | "third-person" | "top-down" | "side-scroller",
camera_type: "first-person" | "third-person" | "fixed" | "isometric",
movement_type: "WASD" | "mouse" | "touch" | "hybrid",
primary_mechanic: "shooting" | "extraction" | "survival" | "puzzle",
color_palette: extractColorPalette(theme),
character_archetypes: extractCharacters(description),
objectives: extractObjectives(description),
music_style: extractMusicStyle(genre, theme)
}
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 6d ago First seen · 740 lines · 37 tokens per session scan A aa63556b4ecf
demo-builder is a skill published in the GitHub repository natea/fitfinder (4 stars, last pushed 10mo ago), licensed MIT. It adds 37 tokens to every session and 5,535 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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