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 TheArcForge/Hades --skill data-modelinggit clone --depth 1 https://github.com/TheArcForge/HadesWrote 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/thearcforge/hades/data-modeling)<a href="https://agentmods.dev/skills/thearcforge/hades/data-modeling"><img src="https://agentmods.dev/badge/skills/thearcforge/hades/data-modeling/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/thearcforge/hades/data-modeling"><img src="https://agentmods.dev/badge/skills/thearcforge/hades/data-modeling.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00028 | $0.04326 |
| Opus 5.5 | $0.00011 | $0.01730 |
| Sonnet 5.5 | $0.00006 | $0.00865 |
| Haiku 4.5 | $0.00003 | $0.00433 |
Grade A, and why
data-modeling 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 1mo 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 — 551 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Data Modeling
Guidance for structuring game data in Unity: choosing the right ScriptableObject pattern, separating config from runtime state, and designing a save system that survives versioning.
When to Apply
Activate when the conversation involves:
- Deciding whether to use a ScriptableObject, a plain C# class, or MonoBehaviour fields to hold data
- Designing item stats, enemy configs, ability definitions, or other designer-facing data
- Building or extending a save/load system
- Choosing how to serialize data (JSON, binary, PlayerPrefs, SQLite)
- Managing a runtime registry of active entities (current enemies, items in world, etc.)
- Inspector annotation and editor-time data authoring conventions
Do NOT activate for pure component-structure questions (single MB vs. split) — those go to hades:component-design. Do NOT activate for prefab organization questions — those go to hades:prefab-architecture.
Project Context Check
Before making recommendations:
-
Check existing assets and types in the graph:
- Call
search_by_name("*.asset")to discover existing ScriptableObject assets and understand naming conventions - Call
graph_query(edgeKind: "references", edgeTargetNamePattern: "ScriptableObject", edgeTargetKind: "Class")to find SO-derived types already defined in the project - Call
get_project_summary()to understand project scale — asset count and assembly structure inform whether a lightweight pattern or a formal save-system layer is appropriate
- Call
-
Check team decisions in memory:
- Call
recall_memory("data modeling serialization save")to find documented data and save conventions - Check validation status — if a recalled decision shows
warning, surface the conflict to the user before proceeding
- Call
-
Adapt recommendations based on findings:
- If the project already has a save system → extend it rather than introduce a parallel one
- If the project has established SO naming conventions → follow them in new assets
- After agreeing on a new pattern, call
propose_memory_updateto record the decision
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.
- 1mo ago First seen · 551 lines · 28 tokens per session scan A c6638f319be9
data-modeling is a skill published in the GitHub repository TheArcForge/Hades (29 stars, last pushed 1mo ago), licensed MIT. It adds 28 tokens to every session and 4,326 once invoked, about $0.0001 per session on Opus 5.5. 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 2026-08-30.
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