puzzle
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.
概览
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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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.
文件元数据
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.
查看原始文本
---
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
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
| 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)
```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`.
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安装前审查: 避免自动安装
许可证: Apache-2.0
- Potential broker, wallet, exchange, or real-money execution surface; sandbox and explicit approval are required
- This skill may touch real-money trading, broker, wallet, or exchange operations; use only in a sandbox with explicit approval.
- Quality score needs review
工具列表来自元数据，并非已测试的兼容性；Agent 提示词是建议的交接方式。
从一个小任务开始
- 1阅读来源，确认输入、预期输出、依赖和权限。
- 2先让 Agent 提出计划，批准环境配置和费用，再进行隔离的小规模测试。
- 3检查输出和变更文件，只报告实际执行结果，并保留来源版本以便复现。
请在来源中核实依赖、API 密钥及第三方费用。公开仓库不代表所有服务免费。
来源与使用须知
已收录
仓库元数据和审核信号仅供参考。受欢迎、已发现来源、成功运行是不同的事实。
- 来源仓库
- gamedev-skills/awesome-gamedev-agent-skills
- 许可证
- Apache-2.0
- 版本
- 1.0.0
- 最近 GitHub 推送
- 2026年8月24日
- 目录更新于
- 2026年9月2日
版本来自目录元数据，使用前请核实来源发布记录。
质量
73/100
强
信任
72/100
仅限沙盒
审计
82/100
高风险
- Potential broker, wallet, exchange, or real-money execution surface; sandbox and explicit approval are required
- This skill may touch real-money trading, broker, wallet, or exchange operations; use only in a sandbox with explicit approval.
- Quality score needs review
- Verified installs
- —
- 结果
- —
复制不等于安装。安装数需有成功安装回报，不代表全面的质量保证。
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本页通过 Registry API 提供相同的决策、信任、审计、场景和安装信号，让 Agent 无需抓取界面即可排序。
更多详情
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"auto_install_policy": "block",
"auto_install_allowed": false,
"human_review_required": true,
"blocked": true,
"recommended_action": "Do not auto-install. Inspect the source, dependencies, and permission surface first."
},
"quality": {
"score": 73,
"label": "Strong"
},
"supply": {
"track": "Design and creative production",
"scenario": "Design and creative",
"maintenance": "2mo since push",
"risk": "Risky"
},
"alternative_skills": [],
"do_not_use_when": [
"teams that need a vendor-supported SLA",
"high-compliance environments without internal security review",
"No major risk signals from current metadata",
"Audit risk risky exceeds max_risk=medium",
"High-risk permission hints: Shell or command execution",
"Potential broker, wallet, exchange, or real-money execution surface; sandbox and explicit approval are required",
"This skill may touch real-money trading, broker, wallet, or exchange operations; use only in a sandbox with explicit approval.",
"Quality score needs review"
],
"agent_contract": {
"task_input": "Use puzzle in an agent workflow",
"recommended_action": "Do not auto-install. Inspect the source, dependencies, and permission surface first.",
"install_policy": "block",
"minimum_review_before_use": [
"Trust: 80/100 Strong shortlist",
"Audit: 82/100 Risky",
"Safety: 58/100 Avoid automatic install",
"Review repository, license, install command, and permission surface before production use."
],
"expected_agent_output": {
"selected_skill": "gamedev-skills-puzzle (puzzle)",
"install_command": "npx skills add gamedev-skills/awesome-gamedev-agent-skills --skill puzzle",
"risk_summary": "Risky; Blocked for auto-install; Review before production",
"verification_result": "Report the smallest successful task, files touched, warnings, and any missing setup."
}
},
"outcome_feedback": {
"endpoint": "https://www.openagentskill.com/api/agent/outcome",
"method": "POST",
"requires_resolve_event_id": true,
"event_id_source": "Use install_receipt.outcome_feedback.event_id or feedback.event_id returned by /api/agent/resolve for the current task.",
"expected_outcomes": [
"success",
"failed",
"not_relevant",
"blocked_by_risk",
"setup_required"
],
"payload_template": {
"event_id": "<install_receipt.outcome_feedback.event_id or feedback.event_id from /api/agent/resolve>",
"skill_slug": "gamedev-skills-puzzle",
"task": "Use puzzle in an agent workflow",
"agent": "codex",
"outcome": "success",
"install_used": true,
"risk_blocked": false,
"setup_required": false,
"task_success": true,
"output_quality": 4,
"error_type": null,
"human_review_required": false,
"workspace": "sandbox",
"time_to_useful_ms": 120000,
"notes": "Report the smallest successful task, setup friction, files touched, and risk notes."
}
},
"endpoints": {
"web": "https://www.openagentskill.com/skills/gamedev-skills-puzzle",
"api": "https://www.openagentskill.com/api/agent/skills/gamedev-skills-puzzle",
"audit": "https://www.openagentskill.com/skills/gamedev-skills-puzzle/audit",
"eval": "https://www.openagentskill.com/api/agent/evals?slug=gamedev-skills-puzzle&task=Use%20puzzle%20in%20an%20agent%20workflow&max_risk=medium",
"resolve": "https://www.openagentskill.com/api/agent/resolve?task=Use%20puzzle%20in%20an%20agent%20workflow&agent=codex&max_risk=medium",
"receipt": "https://www.openagentskill.com/api/agent/receipt?task=Use%20puzzle%20in%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text",
"install": "https://www.openagentskill.com/api/skills/gamedev-skills-puzzle/install",
"manifest": "https://www.openagentskill.com/api/registry/manifest/gamedev-skills-puzzle"
}
}创作者工具
收录来源
Registry 收录
此列表来自公开来源，维护者认领获批前不会标记为官方。
- 收录方
- OpenAgentSkill 社区索引
归属链接指向公开仓库或创作者主页。创作者可认领列表以更新所有权信号。
认领此 Skill所有者认领
认领此 Skill 页面
这条 Registry 收录 列表归属于 gamedev-skills，但尚未标记为官方。认领后可增加已验证所有者信号，使后续发布、安装和审计更新更值得信赖。
分享工具包
创作者外链工具包
将证据徽章加入你的 README
在开发者评估仓库的位置展示规范页面、当前信任与审计信号，以及真实的 Agent 验证证据。
[](https://www.openagentskill.com/skills/gamedev-skills-puzzle?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)
[](https://www.openagentskill.com/skills/gamedev-skills-puzzle?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)
[](https://www.openagentskill.com/skills/gamedev-skills-puzzle/audit)
[](https://www.openagentskill.com/skills/gamedev-skills-puzzle?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)社区信号
告诉我们这个 Skill 是否对你的 Agent 工作流有帮助。汇总反馈会持续改善排序。