gamedev-skills/awesome-gamedev-agent-skills

puzzle

Build a puzzle game: grid/board state, move input, rule-based resolution (match-3 cascades, sokoban pushes, tile logic), scoring, and undo.

소스 보기

사용 방법

  1. 설치 명령을 복사하고 자신의 에이전트 환경에 설치하기 전에 소스 패키지를 확인하세요.
  2. 필요한 도구, 인증 정보, 지원 환경은 원본 문서에서 확인하세요.
  3. 입력과 원하는 산출물을 설명하고 출처와 결과를 대조하세요.
npx skills add https://github.com/gamedev-skills/awesome-gamedev-agent-skills --skill puzzle

시작 전 확인

  • 설치에는 모델 구독, API 한도, 파일 접근 권한이 포함되지 않습니다.
  • 별점 수와 설치 수는 활동 지표이며 독립적인 품질·보안 검증이 아닙니다.
원본 Skill 문서

원본 저장소의 제목, 예시, 코드, 표, 링크, 이미지를 유지해 표시합니다.

Puzzle

A playbook for grid/board puzzle games — the board model, move input, rule resolution (matching, pushing, logic), scoring, undo, and level progression. This is a compositional skill: it models board state and rules and presents them through a tilemap/UI. It does not re-teach tilemaps; it defines the resolution loop and the correctness rules (clean state, deterministic resolution, undo) that keep a puzzle fair and bug-free.

When to use

  • Use when the game is a discrete board the player changes with moves, and the board

resolves by rules: match-3/tile-matching, sokoban/block-pusher, sliding puzzle, logic grid.

  • Use when designing match/cascade resolution, undo, level progression, or solvability.

When not to use:* real-time grid action with permadeath → roguelike. Card zones/turns → card-game. Physics-based "puzzle platformer" → platformer + physics-tuning. For the tile rendering, use godot-tilemap / unity-tilemap-2d.

Core loop

Read the board → plan a move → make the move → the board resolves by its rules (match, push, fall, fill, cascade) → see progress toward the objective → repeat until solved/failed. The fun is the planning; the engine's job is to resolve each move deterministically and present it clearly.

Must-have systems

  1. Board model — a grid of cells holding pieces; the single source of truth (logic, not visuals).
  2. Move input — swap, push, drag, rotate, or place; validate legality before applying.
  3. Rule resolution — detect and apply the genre's rule (matches, pushes, logic) until stable.
  4. Cascades/chains — when resolution changes the board, re-resolve until no more changes.
  5. Objectives + scoring — win/lose conditions (score, clear all, reach goal); move/time limits.
  6. Undo — revert the last move (and its resolution) exactly; essential for thinky puzzles.
  7. Level progression + (often) generation — hand-authored or generated solvable boards.
  8. Feedback ("juice") — clear, satisfying animation/sound for matches, falls, and chains.

Design knobs

KnobEffectNotes
Grid size / shapecomplexitySquare is standard; hex/irregular change feel.
Match/push rulegenre identity3-in-a-row, shapes, push-into-goal, etc.
Cascade scoringreward depthBigger chains = exponential payoff.
Move / time limitpressureMove-limited = puzzly; time = arcade.
Difficulty curvelearningIntroduce one mechanic at a time.
Undo depthforgivenessSingle-step vs. full history.
Solvability guaranteefairnessGenerated boards must be solvable.
Deadlock handlingno dead endsDetect no-moves; shuffle or end (refs).

Patterns

1. Board model + match detection (logic separate from visuals)

python
# Pseudocode. The board is the truth; rendering reads from it. (0,0) top-left, y grows down.
board = [[piece_or_empty for _ in range(W)] for _ in range(H)]

def find_matches(board):
    matched = set()
    for y in range(H):                       # horizontal runs of >= 3 equal pieces
        run = 1
        for x in range(1, W):
            if board[y][x] and board[y][x] == board[y][x-1]: run += 1
            else:
                if run >= 3: matched |= {(y, k) for k in range(x-run, x)}
                run = 1
        if run >= 3: matched |= {(y, k) for k in range(W-run, W)}
    # ... repeat the same scan vertically (columns) ...
    return matched

2. Resolve → collapse → refill → cascade (repeat to stability)

python
# Pseudocode. One player move can trigger a chain; loop until the board stops changing.
def resolve(board):
    chain = 0
    while True:
        matches = find_matches(board)
        if not matches: break                 # stable: resolution complete
        chain += 1
        score += score_for(matches, chain)    # later chain steps score more (see refs)
        clear(board, matches)                  # remove matched pieces
        apply_gravity(board)                   # pieces fall into the gaps
        refill(board, rng)                      # spawn new pieces at the top (seeded RNG)
    return chain

3. Undo via state snapshot or command

python
# Pseudocode. Snapshot before each move; undo restores it exactly (board + score + counters).
def make_move(move):
    history.append(snapshot(board, score, moves_left))   # push BEFORE applying
    apply(move); resolve(board); moves_left -= 1

def undo():
    if history:
        board, score, moves_left = history.pop()         # exact revert, including resolution

For large boards prefer the command pattern (store the move + enough to invert it) over full snapshots to save memory; snapshots are simplest and fine for small boards.

Pitfalls / failure modes

  • Mixing logic and visuals → animations desync from state and cause bugs. The board model is

the single source of truth; the view only renders it.

  • Resolving only once → cascades/chains are missed. Loop resolution until the board is stable

(Pattern 2).

  • Undo that doesn't restore everything → score/move-count/random-state drift. Snapshot all

state, or make the move fully invertible.

  • Unseeded refill RNG → can't reproduce a level / no deterministic undo or daily puzzle. Seed it.
  • Generated boards that aren't solvable → unfair dead ends. Generate-and-verify, or generate

from a known solution backward (refs).

  • No deadlock detection (match-3) → board with no valid moves softlocks. Detect "no moves"

and shuffle or end the level (refs).

  • Difficulty spikes → too many mechanics at once. Teach one mechanic per level before combining.
  • Resolution mid-animation accepts input → double-moves/corruption. Lock input until the

board is stable.

Composition (build it from these skills)

  • Board rendering: godot-tilemap / unity-tilemap-2d for the grid; godot-ui-control for HUD, score, and menus.
  • Levels: level-design for hand-authored puzzles and difficulty pacing; procedural-gen for solvable generated boards.
  • Persistence: save-systems for level progress, high scores, and seeded daily puzzles.
  • Juice: game-feel for match/cascade pop, screen shake, and chain feedback; the engine animation/Tween skill for swaps/falls/clears; audio-design for match and chain cues.
  • Scripting: godot-gdscript / unity-csharp-scripting for the resolution loop and rules.

References

  • For match-3 detection/gravity/refill/cascade detail, deadlock detection and reshuffles,

sokoban/rule-based puzzles, undo strategies, solvable generation, and scoring, read references/board-and-resolution.md.

관련 작업

같은 저장소의 Skills

더 많은 Skills

모든 Skills
gamedev-skills
커뮤니티

game-feel

Add "juice" and game feel that makes actions satisfying — screen shake, hit-stop/freeze frames, tweened/eased motion, squash & stretch, knockback, and layered audio-visual feedback — as engine-neutral techniques that pair with the detected engine's tween, particle, and camera APIs. Use when the user mentions game feel, juice, "make it feel good/punchy", screen shake, hit stop, screen freeze, easing, squash and stretch, impact frames, or feedback/polish on hits, jumps, pickups, and deaths.

설치 수
16
GitHub Stars
4.3천
업데이트
10월 24일
gamedev-skills
커뮤니티

audio-design

Implement game audio practice — bus/mixer architecture and gain in decibels, ducking (sidechain), adaptive/dynamic music via layering and re-sequencing, SFX variation, and beat synchronization. Engine-neutral. Use when the user mentions audio mixing, audio buses, adaptive/dynamic music, ducking, SFX variation, music layers, or syncing gameplay to the beat.

설치 수
13
GitHub Stars
4.3천
업데이트
10월 24일
gamedev-skills
커뮤니티

performance-optimization

Find and fix game performance problems methodically — measure with the engine profiler first, reason about the frame-time budget, locate the CPU-vs-GPU bottleneck, then apply the right fix: object pooling, draw-call batching, fewer allocations/GC spikes, and asset budgets. Engine- neutral method that pairs with each engine's profiler. Use when the user mentions performance, optimize, low/dropping FPS, frame drops, stutter, lag, profiler, frame budget, draw calls, batching, garbage collection/GC

설치 수
13
GitHub Stars
4.3천
업데이트
10월 24일
gamedev-skills
커뮤니티

shader-programming

Write game shaders from cross-engine fundamentals — the vertex→fragment pipeline, coordinate spaces, UV math, and common 2D/3D effects (tint, UV scroll, dissolve, outline, fresnel rim, vignette) in GLSL with HLSL equivalents. Use when the user mentions shaders, fragment/pixel shader, vertex shader, UV, GLSL, HLSL, or effects like dissolve, outline, or rim light.

설치 수
13
GitHub Stars
4.3천
업데이트
10월 24일