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systems-thinking

Skill10 starsChanged 38 days agoMITView on GitHub

Analyze a change as part of a wider system by mapping boundaries, dependencies, feedback loops, delays, incentives, and leverage points.

9 other projects use a version of this.

Adopted by

Most recently taken up by

The file

We split this skill into the rules it gives an agent

3 rules. 0 are common, 3 are distinctive, and 0 are very specific to this project.

  • 0

    Common

    Most of the 8 edited versions we read keep these.

  • 3

    Distinctive

    This author's own choices. Worth a look.

  • 0

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Use this skill when a local change may alter agent behavior, tool safety, documentation discoverability, operational load, or downstream …

    line 8
  2. Distinctive:

    Look for second-order effects: what the change makes easier, harder, more likely, or invisible.

    line 13
  3. Distinctive:

    Prefer interventions at high-leverage points: information quality, interfaces, defaults, feedback, and constraints before adding complexity.

    line 14

“Common” is measured: kept by at least 6 in 10 of the 8 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Systems Thinking

Use this skill when a local change may alter agent behavior, tool safety, documentation discoverability, operational load, or downstream workflows.

  1. Define the system boundary, purpose, owners, users, and external dependencies.
  2. Map inputs, outputs, stocks, flows, constraints, and state transitions.
  3. Trace direct and indirect dependencies, feedback loops, delays, bottlenecks, and incentives.
  4. Look for second-order effects: what the change makes easier, harder, more likely, or invisible.
  5. Prefer interventions at high-leverage points: information quality, interfaces, defaults, feedback, and constraints before adding complexity.
  6. Define leading indicators, guardrails, rollback conditions, and a verification plan.

Output a small causal map or table plus the proposed intervention, expected downstream effects, risks, and measurements. Treat local optimization as suspect when it worsens system-level outcomes.

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