Player Experience Modeling

SkillAI & models

Model target players, motivations, emotions, pleasures, needs, flow, novelty, judgment, and interest curves. Use when defining who a game is for, shaping retention, diagnosing boredom or confusion, designing progression, or aligning gameplay with a desired emotional arc.

Use Player Experience Modeling in Claude, ChatGPT or Ahel Desktop

Free. Sign in, add Player Experience Modeling and connect your AI. About a minute.

Also: Claude Code · Cursor · Codex

Then ask your AI: use the Player Experience Modeling skill

Details

Instructions available. Your AI can read the instructions. Execution depends on the setup they require.

Add Ahel to your AI once: Claude, ChatGPT, Cursor, Claude Code or Codex. Then ask it to use this.

Player Experience ModelingStart free

What this skill tells your AI

The instructions your AI receives, as published by hashgraph-online/awesome-codex-plugins in plugins/LVTD-LLC/skills/skills/player-experience-modeling/SKILL.md and read by Ahel’s review.

Use this skill to define the experience the game is trying to create before implementing systems. It gives an AI game-building agent a target for taste, pacing, onboarding, and progression decisions.

Source Traceability

Primary source: The Art of Game Design: A Book of Lenses, Third Edition by Jesse Schell, especially chapters 2, 9-11, and 16 on experience, players, pleasure, flow, motivation, novelty, judgment, and interest curves. The workflow is transformed and paraphrased.

Supporting source: Self-Determination Theory for autonomy, competence, and relatedness as durable motivation lenses.

Workflow

  1. Define the target player by behavior and context, not demographic shorthand.
  2. Identify the desired emotional and motivational promise.
  3. Map pleasures, needs, novelty, mastery, and social drivers.
  4. Shape the interest curve across first minute, first session, midpoint, climax, and return session.
  5. Translate experience goals into implementation constraints and telemetry.

Required Output

  • Player Model: target player, context, skills, anxieties, and motivations.
  • Experience Promise: what the game should make the player feel and do.
  • Motivation Map: autonomy, competence, relatedness, novelty, mastery, expression, and reward drivers.
  • Interest Curve: beats, intensity, variety, and recovery.
  • Build Implications: onboarding, feedback, difficulty, pacing, progression, and content priorities.

Local References

Before producing an experience model, read:

  • references/core/guide.md
  • workflows/experience-brief.md

Signals

GitHub stars
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Forks
316
Last commit
Oct 2026
Advanced
Item type
skill
Key
player-experience-modeling
Source
github.com/hashgraph-online/awesome-codex-plugins