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 agentmods add skills/thearcforge/uniclaude/data-modelingnpx skills add TheArcForge/UniClaude --skill data-modelinggit clone --depth 1 https://github.com/TheArcForge/UniClaudeWhat 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 | $0.00029 | $0.00839 |
| Opus 5 | $0.00015 | $0.00419 |
| Sonnet 5 | $0.00006 | $0.00168 |
| Haiku 4.5 | $0.00003 | $0.00084 |
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 2d 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 — 93 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Data Modeling — Full Decision Framework
Use this when unity-architect's condensed data section needs more depth.
DECISION: ScriptableObject Pattern Selection
When this applies: Using SOs for game data.
Options:
-
Data container — simple read-only config.
- Pattern: [CreateAssetMenu], public fields with stats/values.
- Use: item definitions, enemy configs, level parameters.
- Rule: never mutate at runtime (values persist in editor!). Clone first if needed.
-
Runtime set — tracks active objects without FindObjectsOfType.
- Pattern: SO holds List. Objects register in OnEnable, unregister in OnDisable.
- Use: "all active enemies", "all collectibles in range", "all UI panels".
- Benefit: O(1) removal, no per-frame scanning.
-
Event channel — decoupled pub/sub.
- Pattern: SO with UnityEvent or Action. Publisher calls Raise(), subscribers listen.
- Use: game events that cross system boundaries (PlayerDied, LevelComplete).
- Benefit: no scene references needed between systems.
-
Enum-like collection — replaces C# enums with SO instances.
- Pattern: each "enum value" is a SO asset. Systems reference the asset directly.
- Use: damage types, item categories — when you need data attached to enum values.
- Benefit: extensible without code changes; designers add new types.
DECISION: Runtime State Management
When this applies: Data that changes during gameplay.
Options:
-
MonoBehaviour fields — state lives on the component.
- Use when: per-instance, per-frame state (health, position, timers).
- Access: other scripts hold a reference or use events.
-
Dedicated state class (POCO) — plain C# class holding state.
- Use when: state needs to be serialized, copied, or passed around.
- Pattern: [System.Serializable] class, owned by a MonoBehaviour.
- Benefit: easy to serialize for save/load, easy to snapshot for networking.
-
Static/global state — accessible from anywhere.
- Use ONLY for: truly global values (current score, game paused flag).
- Implementation: static class with static properties or singleton SO.
- Rule: minimize this. Most state should be instance-level.
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.
- 2d ago First seen · 93 lines · 29 tokens per session scan A 4c96a53d2753
data-modeling is a skill published in the GitHub repository TheArcForge/UniClaude (51 stars, last pushed 3mo ago), licensed MIT. It adds 29 tokens to every session and 839 once invoked, about $0.0001 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 2026-08-30.
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