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 human-avatar/skills-for-humanity --skill s4h-systems-emergence-detectiongit clone --depth 1 https://github.com/human-avatar/skills-for-humanityWrote 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/human-avatar/skills-for-humanity/s4h-systems-emergence-detection)<a href="https://agentmods.dev/skills/human-avatar/skills-for-humanity/s4h-systems-emergence-detection"><img src="https://agentmods.dev/badge/skills/human-avatar/skills-for-humanity/s4h-systems-emergence-detection/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/human-avatar/skills-for-humanity/s4h-systems-emergence-detection"><img src="https://agentmods.dev/badge/skills/human-avatar/skills-for-humanity/s4h-systems-emergence-detection.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 | $0.00059 | $0.01089 |
| Opus 5 | $0.00030 | $0.00544 |
| Sonnet 5 | $0.00012 | $0.00218 |
| Haiku 4.5 | $0.00006 | $0.00109 |
Grade A, and why
s4h-systems-emergence-detection 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 9d 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 — 99 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Systems Emergence Detection
Emergent properties are the most important features of complex systems and the least designed for. They arise from interactions between components, not from the components themselves — which is why fixing individual parts often fails to fix system-level problems. Identifying emergence requires asking not what each component does, but what arises when they interact.
Your Process
Step 1: State the System-Level Property Name the property to explain or design for. Be precise: "the platform feels trustworthy", "the team produces poor decisions", "the market self-corrects". Vague properties produce vague analysis.
Framing check: Confirm the specific system and emergent property before continuing. State what you've identified — the actual system being analyzed and the property you are tracing — in one sentence, then use AskUserQuestion:
- Question: "I'm reading this as: [your one-sentence framing of the system and the emergent property in focus]. Is that right?"
- Header: "Framing"
- Options:
- Yes — proceed — framing is correct
- Adjust — one element is off; user will correct it before you continue
- Reframe — different situation than read; incorporate the correction before proceeding
Step 2: List Components Enumerate the system's components — people, subsystems, rules, technologies, incentives. These are the parts whose interactions you will examine.
Step 3: Test Each Component For each component: does the property exist in it alone? If trust cannot exist in a single user, the property is emergent. This step confirms emergence and rules out simple aggregation.
Step 4: Trace the Producing Interactions Identify the specific interactions between components that generate the property. Show the full set of candidate interactions before narrowing.
Before narrowing: Show the complete set of interactions identified to the user first. Use AskUserQuestion:
- Question: "I've identified [N] candidate interactions. Before I select the ones most necessary and sufficient for producing the property, are there any you'd flag as especially important, or any I've missed?"
- Header: "Prioritise"
- Options:
- Proceed with your selection — the set looks right
- Flag one — user will name a specific interaction to include
- Add a missing one — user will describe it
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.
- 9d ago First seen · 99 lines · 59 tokens per session scan A b255f5a21cdf
s4h-systems-emergence-detection is a skill published in the GitHub repository human-avatar/skills-for-humanity (223 stars, last pushed 1mo ago), licensed MIT. It adds 59 tokens to every session and 1,089 once invoked, about $0.0003 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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