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ai-behavior-patterns

Skill105 starsChanged 8 months agoMITView on GitHub

Design maintainable AI behavior structures for decision-making, navigation, combat, and systemic interaction.

The file

We split this skill into the rules it gives an agent

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

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈3

    Distinctive · estimate

    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:

    create tuning hooks and readable debug outputs

    line 27
  2. Distinctive:

    Keep this skill aligned with the relevant rules layer and current project documentation.

    line 58
  3. Distinctive:

    If engine-specific constraints materially change the workflow, hand off to the matching engine skill or engine-specific reviewer.

    line 59

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “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

Ai Behavior Patterns

Purpose

Design maintainable AI behavior structures for decision-making, navigation, combat, and systemic interaction.

Use When

  • NPC behavior needs structure
  • AI tuning is opaque
  • behavior authoring is hard to debug

Inputs

  • enemy or NPC roles
  • world rules
  • combat or systemic constraints
  • performance targets

Process

  1. define behavior goals and state or decision model
  2. separate sensing, decision, and action execution
  3. create tuning hooks and readable debug outputs
  4. handle fail states, navigation issues, and fallback behavior
  5. profile high-density scenarios early

Outputs

  • AI behavior model
  • tuning hooks
  • debugging checklist
  • performance risk notes

Quality Bar

  • makes ownership, state flow, and failure behavior explicit
  • improves maintainability without over-abstracting
  • supports testing, debugging, and safe iteration

Common Failure Modes

  • coupling systems through hidden globals or timing assumptions
  • writing logic that is hard to test or debug
  • optimizing the wrong layer before measuring

Related Agents

  • ai-programmer
  • combat-designer
  • performance-reviewer

Related Commands

  • tech-design
  • verify
  • playtest-report

Notes

  • Keep this skill aligned with the relevant rules layer and current project documentation.
  • If engine-specific constraints materially change the workflow, hand off to the matching engine skill or engine-specific reviewer.

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