puzzle
gamedev-skills/awesome-gamedev-agent-skills
Build grid/board puzzle games with deterministic rule resolution, cascades, undo, and level progression.
What is puzzle?
A playbook for discrete-board puzzle games (match-3, sokoban, sliding puzzles, logic grids). Covers board state modeling, move validation, rule-based resolution with cascades, scoring, undo, and level progression. Use this to design fair, bug-free puzzle mechanics where the player plans moves and the engine resolves them deterministically.
- Model a grid board as the single source of truth, separate from rendering
- Detect and apply genre-specific rules (matches, pushes, logic) until the board stabilizes
- Implement cascades/chains: when resolution changes the board, re-resolve until no more changes occur
- Support move input validation (swap, push, drag, rotate, place) before applying
- Provide full undo that reverts board state, score, move counters, and random state exactly
- Define win/lose conditions, scoring, and move/time limits for objectives
How to install puzzle
npx skills add https://github.com/gamedev-skills/awesome-gamedev-agent-skills --skill puzzleHow to use puzzle
- 1.Define your board model: a 2D grid of cells holding pieces (the single source of truth)
- 2.Implement move input validation: check legality before applying swaps, pushes, or placements
- 3.Write rule-resolution logic: detect matches/pushes/logic changes and apply them
- 4.Loop resolution until stable: after each change, re-scan for new matches/cascades
- 5.Implement gravity and refill: pieces fall into gaps, new pieces spawn at the top (use seeded RNG)
- 6.Add undo via state snapshots or command pattern: store board, score, move count, and RNG state before each move
- 7.Define objectives and scoring: set win/lose conditions and reward chain depth
- 8.Integrate with tilemap rendering (godot-tilemap, unity-tilemap-2d) and UI for HUD/menus
Use cases
- Build a match-3 game with cascading combos and exponential chain scoring
- Design a sokoban-style block-pusher with deterministic push resolution and undo
- Create a sliding-puzzle or logic-grid game with move validation and solvability guarantees
- Implement a daily puzzle system with seeded RNG for reproducible boards
- Add undo depth and move limits to make a puzzle feel fair and thinky rather than arcade
- Game designers building turn-based puzzle games
- Developers implementing match-3, sokoban, or grid-logic mechanics
- Teams designing difficulty curves and level progression for puzzle games
- Anyone needing deterministic board resolution and undo for fairness
puzzle FAQ
No. The board model is the single source of truth; rendering only reads from it. Mixing them causes animations to desync and bugs to hide. Keep logic and visuals separate.
A single move can trigger cascades: matches clear, pieces fall, new pieces spawn, and new matches form. Loop until no more changes occur, or you'll miss chains and break scoring.
Snapshot all state before each move: board, score, move counters, and random state. On undo, restore the entire snapshot exactly. Partial undo (e.g., forgetting score) causes drift and unfairness.
Detect when no valid moves remain. Either shuffle the board or end the level. For generated boards, generate-and-verify solvability, or generate backward from a known solution.
Seed your RNG so refill is deterministic. This lets you reproduce levels, support daily puzzles, and ensure undo works correctly without storing the full piece sequence.
Full instructions (SKILL.md)
Source of truth, from gamedev-skills/awesome-gamedev-agent-skills.
name: puzzle description: > 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.
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
- Board model — a grid of cells holding pieces; the single source of truth (logic, not visuals).
- Move input — swap, push, drag, rotate, or place; validate legality before applying.
- Rule resolution — detect and apply the genre's rule (matches, pushes, logic) until stable.
- Cascades/chains — when resolution changes the board, re-resolve until no more changes.
- Objectives + scoring — win/lose conditions (score, clear all, reach goal); move/time limits.
- Undo — revert the last move (and its resolution) exactly; essential for thinky puzzles.
- Level progression + (often) generation — hand-authored or generated solvable boards.
- Feedback ("juice") — clear, satisfying animation/sound for matches, falls, and chains.
Design knobs
| Knob | Effect | Notes |
|---|---|---|
| Grid size / shape | complexity | Square is standard; hex/irregular change feel. |
| Match/push rule | genre identity | 3-in-a-row, shapes, push-into-goal, etc. |
| Cascade scoring | reward depth | Bigger chains = exponential payoff. |
| Move / time limit | pressure | Move-limited = puzzly; time = arcade. |
| Difficulty curve | learning | Introduce one mechanic at a time. |
| Undo depth | forgiveness | Single-step vs. full history. |
| Solvability guarantee | fairness | Generated boards must be solvable. |
| Deadlock handling | no dead ends | Detect no-moves; shuffle or end (refs). |
Patterns
1. Board model + match detection (logic separate from visuals)
# 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)
# 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
# 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-2dfor the grid;godot-ui-controlfor HUD, score, and menus. - Levels:
level-designfor hand-authored puzzles and difficulty pacing;procedural-genfor solvable generated boards. - Persistence:
save-systemsfor level progress, high scores, and seeded daily puzzles. - Juice:
game-feelfor match/cascade pop, screen shake, and chain feedback; the engine animation/Tweenskill for swaps/falls/clears;audio-designfor match and chain cues. - Scripting:
godot-gdscript/unity-csharp-scriptingfor 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.
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