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 deciqAI/knowledge-skills --skill emergencegit clone --depth 1 https://github.com/deciqAI/knowledge-skillsWrote 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/deciqai/knowledge-skills/emergence)<a href="https://agentmods.dev/skills/deciqai/knowledge-skills/emergence"><img src="https://agentmods.dev/badge/skills/deciqai/knowledge-skills/emergence/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/deciqai/knowledge-skills/emergence"><img src="https://agentmods.dev/badge/skills/deciqai/knowledge-skills/emergence.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 | $0.00099 | $0.01548 |
| Opus 5 | $0.00049 | $0.00774 |
| Sonnet 5 | $0.00020 | $0.00310 |
| Haiku 4.5 | $0.00010 | $0.00155 |
Grade A, and why
emergence 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 8d 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 — 109 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Emergence
Overview
Emergence: many interacting parts produce whole-level properties that cannot be predicted from the parts alone. Wetness, consciousness, market dynamics — none exist at the part level; they emerge from interaction at scale. Philip W. Anderson (Nobel 1977) formalized this in "More Is Different" (1972): reducing things to fundamental laws does not give you the ability to reconstruct the whole.
Composes with cynefin, feedback-loops, network-effects, tipping-point, first-principles.
When to Use
- Strategy in markets, cultures, ecosystems; platform / community / open-source design
- Diagnosing why a previously-working approach fails at scale
- Cultural change; codebase architecture at scale
- Reasoning about AI capex bets, AI adoption dynamics, or AI-native competition where capabilities appear unpredictably at scale
Not when: the system is simple or complicated with knowable causal structure.
Coaching Novices (Adaptive Front Door)
- Engine mode: concrete case → run The Process directly.
- Coach mode: new to framework → guide step by step.
In Coach mode, respond one step at a time. Each [WAIT] is a hard stop — output only that step's question, then stop.
- One-line: many interacting parts + no central control = emergent whole. Design seed conditions; observe; adjust. Don't predict and control.
- Check fit: mechanical system (few parts, knowable causation)? Emergence doesn't apply.
- Elicit: what's the system, the intervention, the outcome sought? > [WAIT — do not advance until user responds]
- Diagnose: complex or complicated? What conditions and rules can you shape? What feedback loops operate? > [WAIT — do not advance until user responds]
- Close: design intervention as "shape conditions and observe" + monitoring plan. > [WAIT — do not advance until user responds]
What ships with it
3 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.
- 8d ago First seen · 109 lines · 99 tokens per session scan A 4fe49ddca5a7
emergence is a skill published in the GitHub repository deciqAI/knowledge-skills (10 stars, last pushed 10d ago), licensed MIT. It adds 99 tokens to every session and 1,548 once invoked, about $0.0005 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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