difficulty-design
Skill0 starsChanged 9 months agoMITView on GitHub
Difficulty and challenge design planning. Use when designing difficulty curves, flow state, challenge types, accessibility options, assist modes, boss encounters, dynamic difficulty, skill floor and ceiling, or planning how hard a game should be. Covers difficulty curves, flow channel, challenge variety, accessibility, recovery mechanics, boss design.
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- jammyfu/open-game-skillstheir own version, first seen Oct 11, 2026
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- jammyfu/open-game-skills★ 12same name
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In this repository14 other files it gives its agents.
- AGENTS.mdAGENTS.md
- antipatternsSkill
- architecture-auditSkill
- ascii-wireframingSkill
- content-planningSkill
- design-frameworksSkill
- economy-designSkill
- implementationSkill
- mechanics-paletteSkill
- plan-auditSkill
- playtestingSkill
- scenario-walkthroughSkill
- scopingSkill
- simulation-guideSkill
The file
We split this skill into the rules it gives an agent
2 rules. About 0 are common, 2 are distinctive, and 0 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈2
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
- Distinctive: line 21
Decision rule: Start with fixed curve. Add player-driven modes only if playtesting reveals a wide skill range in your audience.
- Distinctive: line 104
The fairness test: After each death, "Could the player have succeeded with better play?" If yes → fair.
≈ “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.
Files
Difficulty & Challenge Design
Plan challenge systems that keep players in flow. Match difficulty to your target audience and aesthetic.
Quick Reference
Difficulty Approach Selection
| Approach | What It Is | Scope Cost | Best For |
| Fixed curve | Designer-tuned difficulty progression | Low | Linear games, puzzle, platformer |
| Player-driven | Player chooses difficulty (easy/normal/hard) | Medium | Action, RPG, story-driven |
| Adaptive (DDA) | Game adjusts difficulty dynamically | High | Casual, accessibility-focused |
| Assist mode | Granular toggles (Celeste model) | Medium-High | Any game prioritizing accessibility |
Decision rule: Start with fixed curve. Add player-driven modes only if playtesting reveals a wide skill range in your audience. DDA is rarely worth the scope cost for MLP.
"Is This Difficulty Fair?" Checklist
- Player can learn from every failure (failure teaches, not punishes)
- Player had the information needed to succeed before failing
- Challenge tests a skill the game has taught
- No single failure erases more than 2-3 minutes of progress
- Difficulty increase comes from new challenges, not just bigger numbers
Flow State & Difficulty
The Flow Channel
Challenge
↑
│ Anxiety ╱
│ ╱
│ ╱ FLOW
│ ╱ CHANNEL
│ ╱
│ Boredom
└──────────────→ SkillPlayers are in flow when challenge matches skill. As skill grows, challenge must grow too.
Skill floor = minimum skill needed to engage with the game at all. Lower floor = more accessible.
Skill ceiling = maximum skill the game can reward. Higher ceiling = more mastery depth.
Planning implication: Decide your floor and ceiling early. A game with a low floor AND high ceiling (Celeste, Smash Bros) requires more design investment than one with a narrow band.
Difficulty Curve Patterns
| Pattern | Shape | Best For | MLP Viable? |
| Linear | Steady climb | Puzzle games, tutorials | Yes |
| Sawtooth | Hard spike → breather → harder spike | Action games, roguelikes | Yes |
| Exponential | Slow start, steep late game | Strategy, RPGs | Yes (early portion) |
| Player-driven | Player chooses difficulty | Open world, sandbox | Adds scope |
| Sine wave | Intensity oscillates around rising trend | Rhythm, narrative-driven | Yes |
Challenge Types
| Type | Tests | Example | Design Cost |
| Kinesthetic | Reflexes, timing, dexterity | Platforming, bullet-hell, rhythm | Low (tuning values) |
| Strategic | Planning, resource allocation | RTS, card games, tower defense | Medium (balance) |
| Puzzle | Logic, pattern recognition | Portal, Baba Is You | Medium (level design) |
| Knowledge | Memory, game system mastery | RPG builds, fighting game matchups | High (content) |
| Social | Reading others, cooperation | Among Us, co-op puzzles | High (multiplayer) |
Design guideline: Mix 2-3 challenge types to prevent single-note gameplay. Your primary challenge type should match your target aesthetic — a game targeting "Challenge" (MDA) needs kinesthetic or strategic depth, not just knowledge checks.
MLP guidance: Focus on one primary challenge type. Add a secondary type only if it naturally emerges from the core mechanic.
Recovery Mechanics
How a player recovers from failure shapes perceived difficulty more than the challenge itself.
| Recovery Type | Time Lost | Tension | Best For |
| Instant respawn | Seconds | Low | Platformers (Celeste, Super Meat Boy) |
| Checkpoint | 1-5 minutes | Medium | Action-adventure, Metroidvania |
| Run restart | 5-30 minutes | High | Roguelikes, permadeath games |
| Rewind | None (undo) | Low | Puzzle, strategy (Braid, Into the Breach) |
| Soft fail | Variable | Low-Medium | Story games (fail forward) |
Difficulty Anti-Patterns
Fake difficulty = challenge that doesn't come from interesting gameplay decisions.
| Type | Example | Fix |
| Enemy spam | 50 enemies where 5 would do | Fewer, smarter enemies |
| Unclear feedback | Player doesn't know what killed them | Clear death cause indicators |
| Unfair camera | Can't see threats before they hit | Camera shows relevant threats |
| Input lag | Controls feel sluggish | Responsive, tight controls |
| Hidden information | Required knowledge never provided | Teach before testing |
| RNG deaths | Unavoidable random damage | Ensure every death is avoidable |
The fairness test: After each death, "Could the player have succeeded with better play?" If yes → fair. If no → fake difficulty.
Other anti-patterns: Developer blind spot (you're too good at your own game), number inflation (prefer relatable HP ranges), difficulty as content padding (grind walls), punishing experimentation (reduce cost of trying new strategies).
Deep Dives
(see difficulty-design/difficulty-modes.md for Traditional Difficulty Modes, Assist Mode Design (Celeste Model), Accessibility Planning)(see difficulty-design/design-depth.md for Difficulty Curve Guidelines, Recovery Design Guidelines, Boss Design Principles)
See Also
- design-frameworks — Flow theory context, MDA aesthetics for targeting "Challenge"
(see design-frameworks) - playtesting — Testing for difficulty specifically, observation methodology
(see playtesting) - scoping — Difficulty modes as a scope decision
(see scoping → MLP Scoping Process) - content-planning — Difficulty pacing through content
(see content-planning) - antipatterns — Premature Content and Core Loop Neglect apply to difficulty tuning
(see antipatterns) - economy-design — Resource scarcity as difficulty lever, economy progression curves
(see economy-design) - scenario-walkthrough — Narrate difficulty moments in Beat 4 (Rising Stakes)
(see scenario-walkthrough → The 5-Beat Structure) - mechanics-palette — Mechanic choices that determine challenge type
(see mechanics-palette)
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