可重复使用的Claude代码系统思维技能，摘自Bayram Annakov的AI + Systems Thinking课程（Empatika，2026赛季）。可作为Claude Code插件市场安装，也可复制粘贴在Codex / ChatGPT / Cursor中运行的超级提示词。

课程注重实践：参与者手绘库存流程图，进行实时多人模拟，并将这些AI技能作为批评者、构建者和放大器使用——绝不作为设计师。这些技能强化了这种教学法：它们拒绝为你绘制图表。

可用技能

/ai-systems-coach — 库存流图批评者及原型标识符 （随W2出货）

你画图。技能评分。

批评手绘的库存流/因果循环图，识别系统原型（增长限制、负担转移、失败修复），并展示Meadows杠杆点。输出美人鱼图，验证库存，标记缺失延迟，准备清晰的库存流规范以供Workshop 3模拟。

拒绝从零设计图表，发明你没命名的变量，或强行套入一个原型。

示例：

Systems Thinking — Skills

Reusable Claude Code skills for systems thinking, drawn from the AI + Systems Thinking course (Empatika, Season 2026) by Bayram Annakov. Installable as a Claude Code plugin marketplace, also runnable as copy-paste mega-prompts in Codex / ChatGPT / Cursor.

The course is hands-on: participants draw stock-flow diagrams by hand, run live multiplayer simulations, and use these AI skills as a critic, builder, and amplifier — never as a designer. The skills enforce that pedagogy: they refuse to draw the diagram for you.

Available skills

/ai-systems-coach — Stock-flow diagram critic & archetype identifier (ships with W2)

You draw the diagram. The skill grades it.

Critiques a hand-drawn stock-flow / causal-loop diagram, identifies the system archetype (Limits to Growth, Shifting the Burden, Fixes that Fail), and surfaces Meadows leverage points. Outputs a Mermaid diagram, validates stocks, flags missing delays, prepares a clean stock-flow specification for Workshop 3 simulation.

Refuses to design a diagram from scratch, invent variables you didn’t name, or force-fit an archetype.

Example:

/ai-systems-coach

Stock: Active Customers
Inflow: New signups (driven by referrals from Active Customers)
Outflow: Churn (driven by Service Quality, which drops past Capacity)
R: Active Customers → Referrals → New signups → Active Customers
B: Active Customers → Service Quality (delay 2 weeks) → Churn → Active Customers

/leverage-finder — Map your model to Meadows’ 12 leverage points (ships with W4)

You bring a model and a goal. The skill returns 3 candidate interventions, ranked.

Takes a stock-flow model you have already built and a measurable goal you have already stated, then maps elements of your model to Donella Meadows’ 12 leverage points and returns the 3 highest-leverage candidate interventions for your goal.

The skill enforces the asymmetry lesson structurally: at least one of the 3 candidates must be at knob ≤5 (rules, info flow, goals, paradigm). Most teams reach for parameters (knob 12) first because they have numbers to tune; the skill forces you to consider stronger leverage you can’t see as easily.

Three structural rules:

1. Phase 0 gate — no measurable goal, no output. The skill refuses to rank leverage without a stated purpose. “Improve the system” gets pushed back with three sharpening questions.
2. No inventing structure — only maps stocks, flows, and parameters the model already contains. Won’t add elements the user didn’t draw.
3. Forced choice — returns exactly 3 candidates, not a long list. Forcing the choice is part of the discipline.