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Tuning enemy AI in combat v1.0.0

Use this resource to design, balance and test the combat AI of enemies in an action game

New

  • 370 downloads
  • 210 likes
  • 101 saves

Free

Install with the CLI

In a terminal, from the folder you want:

npx --yes palatekit@latest install enemy-ai-combat-tuning

With no option, the skill goes to ~/.agents/skills/; add --agent claude-code (or codex, cursor…) to target an agent.

First time: connect the CLI with

npx --yes palatekit@latest login

The agent models enemy decisions as explicit states (pursue, reposition, attack, back off), separates perception, intent and movement, then tunes reaction times for readable combat. It adds deterministic decision tests. You get fair, reproducible AI.

Mostly picked by

Updated November 2, 2026

Card for the “Tuning enemy AI in combat” skill

Details

Works in
Install guides
Generates with
Your agent's model
Licence
MIT

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What you get

    Good fit for

    • Your enemies stay frozen or all charge at once
    • A boss feels unfair and you want to tune its attacks

    Not for

      Tags

      • ai
      • enemies
      • combat
      • tests

      About

      You say

      “Tune melee enemies to back off after two attacks and avoid bunching up.”

      Card for the “Tuning enemy AI in combat” skill

      Skill published by MengTo under the MIT license, delivered in its original version.

      Show more

      How to use it

      1. Install the skill in your agent's skills folder
      2. Ask your agent to design, balance and test the combat AI of enemies in an action game
      3. Review and adjust the result

      Content preview

      Files

      • agents/openai.yaml0.2 KB
      • LICENSE1.1 KB
      • NOTICE-PALATEKIT.md0.5 KB
      • SKILL.md1.7 KB

      Origin and licence

      Listed unmodified

      Author
      MengTo
      Source
      github.com/MengTo/Skills/tree/a45892d2fdadab75b31fb16abecc02f101b31c43/agent-skills/game-development/tune-enemy-ai
      Licence
      MIT

      Notice

      « tune-enemy-ai » (MengTo, MIT) livré dans sa version d'origine : fiche en français et en anglais par PalateKit.

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