Puzzle

by gamedev-skillsd4b0e35550c5No license1.3K starsListed Oct 8, 2026Updated Oct 8, 2026Repository updated 11 days ago

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

AI-generated overview

Playbook for building grid/board puzzle games: board state, move input, rule resolution, scoring, undo and levels.

What it does
This skill provides a design and implementation playbook for discrete grid/board puzzle games such as match-3, sokoban, sliding puzzles and logic grids. It defines the board model as the single source of truth, move input and legality checks, rule resolution with cascades, objectives and scoring, exact undo, level progression and solvability, plus feedback. It includes pseudocode patterns for match detection, resolve-collapse-refill loops and snapshot or command-based undo, and points to a reference file for deeper detail.
When to use it
Use it when the game is a discrete board the player changes with moves and the board resolves by rules, including match-3, block-pusher, sliding and logic-grid puzzles. It is also meant for designing match or cascade resolution, undo, level progression and solvability. It is not intended for real-time grid action, card games or physics-based puzzle platformers.
Requirements
No scripts are shipped; it is instructions only. It references a bundled reference document on board and resolution detail. No specific runtime, package, credential or network access is required.

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.

Source and attribution

Source:gamedev-skills/awesome-gamedev-agent-skillsinskills/genres/puzzleat commitd4b0e35

License: No license

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