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 qfoldit/Protein-Design-MCP --skill game-designergit clone --depth 1 https://github.com/qfoldit/Protein-Design-MCPWrote 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/qfoldit/protein-design-mcp/game-designer)<a href="https://agentmods.dev/skills/qfoldit/protein-design-mcp/game-designer"><img src="https://agentmods.dev/badge/skills/qfoldit/protein-design-mcp/game-designer/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/qfoldit/protein-design-mcp/game-designer"><img src="https://agentmods.dev/badge/skills/qfoldit/protein-design-mcp/game-designer.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 | $0.00161 | $0.00753 |
| Opus 5 | $0.00081 | $0.00377 |
| Sonnet 5 | $0.00032 | $0.00151 |
| Haiku 4.5 | $0.00016 | $0.00075 |
Grade A, and why
game-designer 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 10d 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 — 33 lines — stays where its author put it; the contents beside it link to each section on GitHub.
game-designer
Purpose
Turns a scene/gameplay concept into a validated Universal Assembly Graph (UAG) -- see references/uag_schema.md for the full schema. This is the FIRST step of the qFoldIT digital-twin pipeline; every engine-specific skill in this plugin consumes a UAG produced here rather than reimplementing scene-design logic per engine.
Workflow
- Gather the scene intent. What is being represented (a greenhouse, a molecular VR lab, an ore-body prospecting map)? Is there qFoldIT science-skill output feeding it (e.g.
plant-growthmorphology multipliers,miningbio-oxidation results)? If the user hasn't specified, ask -- don't invent scientific parameters that should come from the relevant science skill instead. - Design nodes. Break the scene into
nodes(mesh/light/camera/trigger_volume/ui_panel/particle_emitter/audio_source/group/custom) per the schema. Keep transforms and properties engine-agnostic -- no engine class names here (see "Principle" in the schema doc). - Design connections/constraints/interactions. Parent/child hierarchy, physics/interaction constraints, and trigger-based interactions (on_grab, on_proximity, etc.) as needed for the concept.
- Validate. Run
scripts/uag_validate.py <file>(this validator is shared -- the same script lives in every downstream engine skill's expectations, so a UAG that fails here will fail everywhere). Fix allerrorsbefore proceeding; reviewwarnings(usually node/trigger types without a known engine mapping yet) and flag them to the user rather than silently dropping them. - Hand off. Tell the user which engine-adapter skill(s) are appropriate for their target platform, and pass the validated UAG JSON to that skill. Do not attempt engine-specific work yourself -- that's what
digital-twin-builder(for simulation semantics) and the per-engine skills are for.
Example
python3 scripts/uag_validate.py my_scene.uag.json
Output is {"valid": true/false, "errors": [...], "warnings": [...], "node_count": N} -- see the script for exact validation rules (unique ids, valid references, no parent_child cycles).
What ships with it
4 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 10d ago First seen · 33 lines · 161 tokens per session scan A 641968c1cf96
game-designer is a skill published in the GitHub repository qfoldit/Protein-Design-MCP (1 stars, last pushed 14d ago), licensed Apache-2.0. It adds 161 tokens to every session and 753 once invoked, about $0.0008 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 2026-08-31.
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