# Benschrauwen Wisdom Collector Wisdom Collector > System Behavior Diagnosis and Leverage - Skill: `tomevault-io/benschrauwen-wisdom-collector-wisdom-collector` (Agent Skill, multi-file: 2 files) - Install (CLI): `npx skillmds@latest add tomevault-io/benschrauwen-wisdom-collector-wisdom-collector` - Raw SKILL.md: https://api.skillmd.com/api/skills/tomevault-io/benschrauwen-wisdom-collector-wisdom-collector/raw - Safety review: pending (external: skill-scanner PASS, skillspector PASS) - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: Coding & Dev Tools - Author: tomevault-io (https://skillmd.com/u/tomevault-io) - Updated: 2026-09-17 - Page: https://skillmd.com/skills/tomevault-io/benschrauwen-wisdom-collector-wisdom-collector --- # System Behavior Diagnosis and Leverage ## When to use Use this when a problem keeps recreating itself, growth runs into limits, feedback arrives late or distorted, or a rule, metric, or fix produces side effects instead of lasting change. ## Diagnose from behavior to structure 1. **Observe behavior over time** — What is changing, what is stable, what is oscillating, and over what time scale? 2. **Identify the stock** — What quantity accumulates, drains, or buffers the system? 3. **Trace inflows and outflows** — What moves the stock up or down? 4. **Map feedback loops** — Which loops are balancing, which are reinforcing, and which dominates now? 5. **Separate delays** — Where are the information, decision, response, and physical delays? 6. **Set the boundary by purpose** — What outside stocks or processes matter for the time horizon you care about? 7. **Find the current limit** — What factor is binding now, and what next limit will growth create? 8. **Name the level of explanation** — Is the issue an event, a behavior pattern, or the underlying structure? ## Pattern cues - Stable, recurring, or goal-seeking behavior usually points to a **balancing loop**. - Accelerating growth or decline usually points to a **reinforcing loop**. - Overshoot, oscillation, or repeated target-miss usually means a **delayed or over-strong balancing loop**. - A problem that persists despite repeated fixes usually means the **structure recreates the problem**. - Sustained growth usually means a **reinforcing growth loop** is meeting a **balancing constraint**. - If growth continues, keep asking: **What limit does this growth create next?** ## Quick diagnostic prompts - What is the stock? - What are the inflows and outflows? - What information reaches the decision maker, and when? - Which loop is dominating right now? - What delay keeps the system from correcting immediately? - What hidden stock, leak, or outside process have I left in the cloud? - Is the real bottleneck still the bottleneck, or has it shifted? ## Choose leverage Work from lower leverage to higher leverage only as needed: - **Numbers / parameters** — change constants, taxes, subsidies, or standards only when a threshold can trigger deeper change. - **Buffers** — enlarge buffers when the system is too vulnerable; shrink them when it is too sluggish. - **Stock-and-flow structure** — redesign bottlenecks, congestion, pollution, and capacity limits when the layout itself creates the problem. - **Delays** — shorten delays if possible, but sometimes slowing the system is safer than speeding it up. - **Balancing feedback** — strengthen weak corrective loops and sensing where correction is failing. - **Reinforcing feedback** — weaken runaway compounding loops and the advantage that feeds on itself. - **Information flows** — put timely, accurate, hard-to-distort feedback where the decision actually happens. - **Rules** — change incentives, constraints, permissions, and enforcement when the system optimizes the wrong thing. - **Self-organization** — preserve the ability to adapt, diversify, and create new structure. - **Goals** — change what the system is trying to achieve. - **Paradigms** — change the assumptions that generate goals, structures, and rules. - **Transcending paradigms** — hold models lightly; stay open to surprise and to being wrong. ## Common system traps - **Policy resistance** — multiple actors undo each other’s interventions. Search for a shared goal or a redesigned feedback structure. - **Tragedy of the commons** — restore direct feedback between use and consequence. - **Drift to low performance** — keep standards absolute instead of lowering them after weak results. - **Escalation** — break the competitive loop or agree on limits. - **Success to the successful** — level the playing field or create exits for losers. - **Shifting the burden** — strengthen the system’s own repair capacity before withdrawing symptom relief. - **Rule beating** — align the rule with its purpose, not just compliance. - **Wrong goal** — test whether the metric actually reflects system welfare. ## Working habits - Make assumptions explicit. - Use small steps and monitor effects. - Optimize the whole, not the parts. - Design responsibility so decision makers feel consequences directly. - Use language that names feedback, resilience, sustainability, and carrying capacity. - Expect surprises; treat errors as data. - Do not define the problem as "lack of my preferred solution." ## Quick model sketch When the behavior is unclear, sketch a stock-and-flow model: - `stock(t) = stock(t - dt) + (inflow - outflow) x dt` - mark delays and information paths - label balancing and reinforcing loops - test how behavior changes when you vary rates, delays, buffers, or goals ## Source note Extracted from *Thinking in Systems: A Primer* by Donella H. Meadows. --- > Source: [benschrauwen/wisdom-collector](https://github.com/benschrauwen/wisdom-collector) — distributed by [TomeVault](https://tomevault.io).