Puzzle
Skill gamedev-skills/awesome-gamedev-agent-skills/skills/genres/puzzle
Game-development Agent Skills for AI coding agents: install once and a master router loads the right skill for your engine and task. 66 original, version-pinned skills (plus a master router) in the portable SKILL.md format that runs across Claude Code, Cursor, Codex, Copilot, Gemini CLI and more, for Godot, Unity, Unreal, web and beyond.
npx -y skills add gamedev-skills/awesome-gamedev-agent-skills --skill puzzleAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
What its author says it does
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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.
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SKILL.md
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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.