tjboudreaux/cc-thinking-skills

thinking-systems

When behavior is emergent across components—fixes elsewhere break, loops/delays dominate—map boundary, stocks/flows, feedback, archetypes, then rank leverage.

First seen Mar 12, 2026

Installation

$ npx skills add tjboudreaux/cc-thinking-skills --skill thinking-systems

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Agent compatibility

Declared targets from SKILL.md / docs. Unmarked agents are not listed — the skill may still install via the CLI.

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Repository health

Stars 1.3K
License LICENSE
Default branch main
Open issues 2
Status Active

Package contents

Files included with this skill beyond the listing page.

  • skill md SKILL.md 4,462 B
  • docs SUMMARY.md 183 B

History

  1. First seen on skills.sh
  2. First recorded snapshot · 398 installs

SKILL.md

Systems Mapping and Leverage

Treat the problem as structure and interaction, not isolated parts. Map boundary, stocks/flows, loops/delays, and recurring patterns; intervene at the highest feasible leverage after a side-effect check.

When to Use

  • Symptom spans services/components; single-stack fixes fail or bounce.
  • A change in one place breaks another; behavior is emergent.
  • Problem recurs despite local fixes (structure, not only symptom).
  • Need to rank interventions when parameter/buffer tweaks do not stick.

When NOT to Use

  • Single-component linear bug with clear stack/diff—trace and fix.
  • Throughput limited by one obvious stage—use theory-of-constraints.
  • Decision is a consequence chain of one proposed action—use second-order.
  • Approach selection (plan vs probe vs stabilize)—use cynefin first.

Procedure

  1. Bound the system. Name purpose, actors, boundary, and in/out flows. Exclude noise outside the decision horizon; include any path that can feed the symptom.
  2. Map stocks and flows. List accumulating stocks (queue depth, debt, cache size, WIP) and the rates that fill/drain them. Note what changes slowly even when flows jump.
  3. Find feedback and delays. For each candidate loop: classify reinforcing (amplifies) vs balancing (resists); mark same-direction (+) vs opposite (-) links; name delays (TTL, deploy lag, metric lag, ramp-up). Even count of opposite links → reinforcing; odd → balancing. Long delay + strong correction → overshoot risk.
  4. Match recurring structure when problems return. Check only if recurrence or policy resistance is present; do not force a pattern:

- Fixes That Fail — quick fix, delayed worse side effect - Shifting the Burden — workaround starves fundamental fix - Limits to Growth — growth hits a balancing constraint - Tragedy of the Commons — local optima deplete a shared stock - Escalation — mutual reaction spiral - Success to the Successful — advantage compounds via allocation - Growth and Underinvestment — capacity lags demand until crisis If none fits after a genuine pass, keep the from-scratch map.

  1. Trace symptom to structure. Walk upstream along flows and loops; separate proximate symptom from structural driver (interaction, delay, wrong goal, missing info).
  2. Rank interventions by leverage, then side effects. Prefer higher feasible class: goals/paradigm → rules/information → loop structure (gain, balancing add, delay shorten) → stock/flow topology → buffers/parameters. For each candidate: feasibility, blast radius, delayed reversal risk. Prefer moves that cut harmful reinforcing gain or strengthen needed balancing loops without creating a new commons/escalation.
  3. Stop. Commit highest feasible intervention plus watch signals for loop/delay response. Re-map only if the structure changes or the intervention fails its watch.

Stop when boundary, key stocks/flows, dominant loop(s)+delay(s), optional archetype, and a ranked intervention with side-effect check are stated—or when the problem collapses to a single linear cause.

Output

boundary: <system purpose and edges>
stocks_flows: <stock → inflow/outflow list>
loops:
  - name: <loop>
    type: reinforcing | balancing
    delay: <where cause lags effect>
    links: <brief +/->
archetype: <name or none>
structural_driver: <one sentence>
interventions_ranked:
  - level: <goals|rules|loops|structure|params>
    action: <what>
    side_effects: <feedback/elsewhere/delay risk>
chosen: <highest feasible>
watch: <signals that confirm or falsify>

Verification

  • Falsify: If removing one component fully explains and fixes the issue with no cross-effects, systems mapping is wrong—drop to local debug. If utilization shows one fixed stage as the sole cap, switch to theory-of-constraints.
  • Stop: Do not keep adding loops after the chosen intervention and watch are set.
  • Over-application guard: No archetype without recurrence evidence. No low-leverage param tweak listed as primary when a feasible higher class exists. Do not recreate standalone archetype/feedback/leverage procedures—those checks live only inside this map.