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systems-thinking

Use for systems thinking, or when a change may ripple beyond its target: "what are the side effects?", "why does this keep coming back?", "how do these teams or services affect each other?". Maps loops, delays and leverage points. Skip for single-step fixes.

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Systems Thinking

See the whole before optimizing a part. End with recommendations that account for loops and delays.

When to use

  • A problem keeps returning after "fixes".
  • A change in one team, service or policy may hit others (unintended consequences, incentives, queues, backlogs).
  • The user asks for root causes beyond a single person or component, or for a holistic view.

Skip: single-step linear tasks, one-variable calculations, fixes that need no map of interactions.

Before you start

  1. State in one block: System in focus (what is inside the boundary) and Pass (Boundary, Structure, Dynamics, Delays, Leverage, Synthesis).
  2. Gather first. Read the code, docs, tickets or metrics that describe how the parts connect before drawing the map. Ask up to 3 scoping questions only for what tools cannot answer.
  3. Light path. Small ask: 2-3 bullets per phase. Never skip Structure before Leverage, even on the light path.
  4. If the user already proposed an intervention, shorten Boundary but keep Structure and Dynamics.

Phases

1. Boundary

What is in and out for this analysis. One sentence on the system's purpose from a stakeholder's view.

2. Structure

Elements (stocks that accumulate, actors, resources) and flows (rates in and out). Short pairs: From -> To: what moves.

3. Dynamics

At least one reinforcing (R) and one balancing (B) loop where plausible:

Loop [R|B]: ... - Mechanism: ...

If no loop applies, say so in one line and why.

4. Delays

Where is the lag between action and effect? How does it change behavior (overshoot, oscillation, giving up too early)?

5. Leverage

Leverage point: ... - Why it matters: ... - Risk of backfire: ...

Prefer changes to rules, information flows, incentives or goals over exhorting people to behave differently. Donella Meadows ranks these as stronger levers than adjusting parameters such as limits and budgets.

6. Synthesis

  1. System story: one plain-language paragraph.
  2. Non-obvious consequence: at least one.
  3. Recommended moves: 2-3 actions consistent with the loops and delays above.

Pitfalls

  • Jumping to solutions before Structure and a light Dynamics pass.
  • Stopping at "X is careless". Translate to the incentive or information gap behind the behavior.
  • Drawing every box you can think of. Include only elements that change the answer.
  • A fix that works now but triggers a balancing loop later. Check Delays against each recommendation.

Diagrams are optional; the bullets must stand alone. Worked example: references/example.md.

Checklist

  • System in focus and Pass stated
  • Boundary and purpose explicit
  • Structure uses elements and From -> To flows
  • Dynamics: R and B loops, or N/A justified
  • Delays considered where time matters
  • Leverage tied to the map, with backfire risk
  • Synthesis tells one coherent story

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概要と使いどころ

Use for analytical thinking, or when a question needs breaking down and evidence: "why did metric X drop?", "what drives this?", "break this down", "what data do we need?". Builds a tree, hypotheses and evidence, ends with an answer and key uncertainty. Skip for quick verdicts.

日本語の概要は準備中です。原文の説明を表示しています。

ysskrishna/ai-agent-skills122026年10月8日 更新

Use for creative thinking, or when the user wants many fresh options before choosing: "give me ideas", "brainstorm names", "other ways to do this", "think outside the box". Diverges first, then picks. Skip when one answer is wanted or the task is pure execution.

日本語の概要は準備中です。原文の説明を表示しています。

ysskrishna/ai-agent-skills122026年10月8日 更新

Use for critical thinking, or when the user wants a claim, plan or decision checked for weak spots: "is this right?", "what am I missing?", "poke holes", "sanity check", "devil's advocate", "red team this". Skip for execution-only tasks and wording edits.

日本語の概要は準備中です。原文の説明を表示しています。

ysskrishna/ai-agent-skills122026年10月8日 更新

Use for design thinking, or when a product or service problem needs user understanding before solutions: "what do users really need?", "how might we...", "plan a discovery sprint", "validate this concept". Skip when the spec is frozen or the task is code maintenance.

日本語の概要は準備中です。原文の説明を表示しています。

ysskrishna/ai-agent-skills122026年10月8日 更新

Use for ethical thinking, or when a plan could harm or unfairly burden people: "should we do this?", "is this fair?", "privacy or bias risk", "who gets hurt?". Maps stakeholders, harms, power and consent. Skip for legal advice, neutral fact lookups and implementation-only work.

日本語の概要は準備中です。原文の説明を表示しています。

ysskrishna/ai-agent-skills122026年10月8日 更新

Use for Fermi estimation, or when a rough number is needed fast: "roughly how many...", "ballpark the cost", "estimate capacity or market size", "is this even feasible?". Decomposes, uses ranges and sanity-checks. Skip when exact data is available or a precise calculation is wanted.

日本語の概要は準備中です。原文の説明を表示しています。

ysskrishna/ai-agent-skills122026年10月8日 更新

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