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 rondorkerin/gamestack --skill systemic-emergent-designgit clone --depth 1 https://github.com/rondorkerin/gamestackWrote 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/rondorkerin/gamestack/systemic-emergent-design)<a href="https://agentmods.dev/skills/rondorkerin/gamestack/systemic-emergent-design"><img src="https://agentmods.dev/badge/skills/rondorkerin/gamestack/systemic-emergent-design/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/rondorkerin/gamestack/systemic-emergent-design"><img src="https://agentmods.dev/badge/skills/rondorkerin/gamestack/systemic-emergent-design.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 | $0.00200 | $0.00901 |
| Opus 5.5 | $0.00080 | $0.00360 |
| Sonnet 5.5 | $0.00040 | $0.00180 |
| Haiku 4.5 | $0.00020 | $0.00090 |
Grade A, and why
systemic-emergent-design 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 2mo 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 — 40 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Systemic-Emergent Design
How to author affordances, not solutions: a small set of consistent, deeply-simulated, interacting rules that produce more meaningful play than any volume of scripted content — and, for a procedural/AI-authored game, the only thing that makes generated content cohere rather than collapse into "10,000 bowls of oatmeal."
When to use this
- Designing the rule substrate / "chemistry engine" before authoring or generating content
- Deciding whether to add a system, a verb, or a scripted set-piece
- Auditing for emergence: are systems actually interacting, or siloed behind scripts?
- Making procedural generation produce perceptual variety, not just numerical variety
- Diagnosing: "the world feels inert", "all variety is scripted", "every generated quest is the same", single-solution gates
Scope
This skill owns the emergence-from-interacting-systems discipline. Adjacent concerns live in sibling skills, cross-linked from the guide:
- The "interesting decision" test and general theory →
game-design-fundamentals - Perceptual uniqueness, the oatmeal problem, handcrafted-anchor + constrained-fill →
procedural-generation,procgen-review - Combat verbs, telegraphing, the feel of interactions →
combat-design - Currencies/items as systemic chains (currency-as-material) →
rpg-systems - The spatial affordances systems act on →
open-world-design - Quests that emerge vs. branch →
narrative-and-quest-design
How the pieces fit
GUIDE.md— the cited why, in five sub-domains: the immersive-sim lineage (universal rules; intention & perceivable consequence), emergence from few deep systems vs. scripted events, the "good GM" analogy and its honest limit, multiplicative vs. additive design (Nintendo's chemistry engine), and how emergence + procedural generation multiply each other. Each rule carries an exemplar, source, test-for criterion, named failure mode, and the procedural/headless implication.CHECKLIST.md— Do/Don't + machine-checkable Test-for criteria, grouped by sub-domain, written to be enforced as automated gates in a generation loop.
What ships with it
2 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.
- 2mo ago First seen · 40 lines · 200 tokens per session scan A 8e6b4d63e066
systemic-emergent-design is a skill published in the GitHub repository rondorkerin/gamestack (34 stars, last pushed 4mo ago), licensed MIT. It adds 200 tokens to every session and 901 once invoked, about $0.0008 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.
systemic-emergent-design compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| systemic-emergent-designrondorkerin/gamestack | Skill | 34 | 4mo ago | MIT | A | 200 | Claude Code |
| biopythonK-Dense-AI/scientific-agent-skills | Skill | 56k | 5d ago | MIT | A | 65 | Claude Code |
| neuropixels-analysisK-Dense-AI/scientific-agent-skills | Skill | 56k | 5d ago | MIT | A | 99 | Claude Code, Codex |
| onekgpdK-Dense-AI/scientific-agent-skills | Skill | 56k | 5d ago | MIT | A | 143 | Claude Code |
| pkpd-modelingK-Dense-AI/scientific-agent-skills | Skill | 56k | 5d ago | MIT | A | 273 | Claude Code |
| pydicomK-Dense-AI/scientific-agent-skills | Skill | 56k | 5d ago | MIT | A | 52 | Claude Code, Codex |
| clinical-decision-supportK-Dense-AI/scientific-agent-skills | Skill | 56k | 5d ago | MIT | A | 51 | Claude Code, Codex |