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godot-genre-simulation戈多流派模拟

Agent Skill

godot-genre-simulation 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要围绕仓库状态、代码变更或协作事项进行整理时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

2,250

周安装

91

GitHub Stars

138

下载量

706
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:godot-genre-simulation(戈多流派模拟)
来源仓库:https://github.com/thedivergentai/gd-agentic-skills
仓库路径:skills/godot-genre-simulation
安装命令:
npx skills add https://github.com/thedivergentai/gd-agentic-skills --skill godot-genre-simulation
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/thedivergentai/gd-agentic-skills --skill godot-genre-simulation

简介

godot-genre-simulation 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合在 Codex、Claude、Cursor、Gemini CLI 中围绕仓库状态、代码变更或协作事项进行整理。

  • 适用于戈多流派模拟类游戏项目的开发协作管理,辅助 Issue 跟踪与代码审查。
  • 通过 npx skills add 命令从指定仓库安装,需确认宿主环境兼容性。
  • 安装前建议检查仓库维护状态与安全设置,防止执行不可信操作。
  • 该技能可能触发网络或文件操作,请在隔离环境中验证后再正式使用。

SKILL.md

Genre: Simulation / Tycoon

Optimization, systems mastery, and satisfying feedback loops define management games.

NEVER Do (Expert Anti-Patterns)

Simulation & Economy

  • NEVER use floating-point for primary currency; strictly use Integer Cents (or fixed-point math) to prevent accumulated precision errors in financial models.
  • NEVER process 1000+ entities individually in _process(); strictly use a Tick Manager to batch updates or process entities in rotating pools.
  • NEVER rely on linear cost scaling; strictly use Exponential Growth (Base * pow(1.15, Level)) to maintain challenge and strategic tension.
  • NEVER hide critical metrics from the player; strictly provide Detailed Breakdowns (Income vs. Expense) so players can make optimization-based decisions.
  • NEVER allow infinite resource stacking; strictly enforce Logistical Caps (warehouses/silos) to create meaningful space-management gameplay loops.
  • NEVER let the early game become a "Waiting Simulator"; strictly Front-Load Decisions and quick early wins to build player momentum.
  • NEVER modify a shared Resource directly; strictly use duplicate() to avoid unintentionally updating every building of that type.
  • NEVER tie simulation logic to the visual framerate; strictly use _physics_process() or delta accumulators for deterministic simulation results.

Performance & Threading

  • NEVER update UI labels every frame; strictly use Event-Driven Signals to refresh UI ONLY when the underlying data changes.
  • NEVER run heavy economic loops synchronously; strictly use WorkerThreadPool to offload complex calculations and prevent UI stutters.
  • NEVER store massive resource data as Nodes; strictly use RefCounted or Data Resources to avoid the memory/CPU overhead of the SceneTree.
  • NEVER ignore OS.low_processor_usage_mode; strictly enable it for stationary management screens to save massive CPU/Battery life.
  • NEVER manipulate the SceneTree from background threads; strictly use call_deferred() for thread-safe UI updates.
  • NEVER parse large JSON save files on the main thread; strictly use Threaded Serialization or optimized binary .res formats.
  • NEVER use standard equality (==) for needs; strictly use is_equal_approx() to prevent floating-point jitter failures in logic gates.

🛠 Expert Components (scripts/)

Original Expert Patterns

Modular Components


Economy Design

The heart of any tycoon game is its economy. Key principle: multiple interconnected resources that force trade-offs.

Multi-Resource System

class_name TycoonEconomy
extends Node

signal resource_changed(resource_type: String, amount: float)
signal went_bankrupt

var resources: Dictionary = {
    "money": 10000.0,
    "reputation": 50.0,  # 0-100
    "workers": 0,
    "materials": 100.0,
    "energy": 100.0
}

var resource_caps: Dictionary = {
    "reputation": 100.0,
    "workers": 50,
    "energy": 1000.0
}

func modify_resource(type: String, amount: float) -> bool:
    if amount < 0 and resources[type] + amount < 0:
        if type == "money":
            went_bankrupt.emit()
        return false  # Can't go negative

    resources[type] = clamp(
        resources[type] + amount,
        0,
        resource_caps.get(type, INF)
    )
    resource_changed.emit(type, resources[type])
    return true

Income/Expense Tracking

class_name FinancialTracker
extends Node

var income_sources: Dictionary = {}  # source_name: amount_per_tick
var expense_sources: Dictionary = {}

signal financial_update(profit: float, income: float, expenses: float)

func calculate_tick() -> float:
    var total_income := 0.0
    var total_expenses := 0.0

    for source in income_sources.values():
        total_income += source

    for source in expense_sources.values():
        total_expenses += source

    var profit := total_income - total_expenses
    financial_update.emit(profit, total_income, total_expenses)
    return profit

Time System

Simulation games need controllable time:

class_name SimulationTime
extends Node

signal time_tick(delta_game_hours: float)
signal day_changed(day: int)
signal speed_changed(new_speed: int)

enum Speed { PAUSED, NORMAL, FAST, ULTRA }

@export var seconds_per_game_hour := 30.0  # Real seconds

var current_speed := Speed.NORMAL
var speed_multipliers := {
    Speed.PAUSED: 0.0,
    Speed.NORMAL: 1.0,
    Speed.FAST: 3.0,
    Speed.ULTRA: 10.0
}

var current_hour := 8.0  # Start at 8 AM
var current_day := 1

func _process(delta: float) -> void:
    if current_speed == Speed.PAUSED:
        return

    var game_delta := (delta / seconds_per_game_hour) * speed_multipliers[current_speed]
    current_hour += game_delta

    if current_hour >= 24.0:
        current_hour -= 24.0
        current_day += 1
        day_changed.emit(current_day)

    time_tick.emit(game_delta)

func set_speed(speed: Speed) -> void:
    current_speed = speed
    speed_changed.emit(speed)

Entity Management

Workers/NPCs

class_name Worker
extends Node

enum State { IDLE, WORKING, RESTING, COMMUTING }

@export var wage_per_hour: float = 10.0
@export var skill_level: float = 1.0  # Productivity multiplier
@export var morale: float = 80.0  # 0-100

var current_state := State.IDLE
var assigned_workstation: Workstation

func update(game_hours: float) -> void:
    match current_state:
        State.WORKING:
            if assigned_workstation:
                var productivity := skill_level * (morale / 100.0)
                assigned_workstation.work(game_hours * productivity)
                morale -= game_hours * 0.5  # Working tires workers
        State.RESTING:
            morale = min(100.0, morale + game_hours * 2.0)

func calculate_hourly_cost() -> float:
    return wage_per_hour

Buildings/Facilities

class_name Facility
extends Node3D

@export var build_cost: Dictionary  # resource_type: amount
@export var operating_cost_per_hour: float = 5.0
@export var capacity: int = 5
@export var output_per_hour: Dictionary  # resource_type: amount

var assigned_workers: Array[Worker] = []
var is_operational := true
var efficiency := 1.0

func calculate_output(game_hours: float) -> Dictionary:
    if not is_operational or assigned_workers.is_empty():
        return {}

    var worker_efficiency := 0.0
    for worker in assigned_workers:
        worker_efficiency += worker.skill_level * (worker.morale / 100.0)
    worker_efficiency /= capacity  # Normalize to 0-1

    var result := {}
    for resource in output_per_hour:
        result[resource] = output_per_hour[resource] * game_hours * worker_efficiency * efficiency
    return result

Customer/Demand System

class_name CustomerSimulation
extends Node

@export var base_customers_per_hour := 10.0
@export var demand_curve: Curve  # Hour of day vs demand multiplier

var customer_queue: Array[Customer] = []

func generate_customers(game_hour: float, delta_hours: float) -> void:
    var demand_mult := demand_curve.sample(game_hour / 24.0)
    var reputation_mult := Economy.resources["reputation"] / 50.0  # 100 rep = 2x customers

    var customers_to_spawn := base_customers_per_hour * delta_hours * demand_mult * reputation_mult

    for i in int(customers_to_spawn):
        spawn_customer()

func spawn_customer() -> void:
    var customer := Customer.new()
    customer.patience = randf_range(30.0, 120.0)  # Seconds before leaving
    customer.spending_budget = randf_range(10.0, 100.0)
    customer_queue.append(customer)

Feedback Systems

Visual Feedback

# Money flying to bank, resources flowing, etc.
class_name ResourceFlowVisualizer
extends Node

func show_income(amount: float, from: Vector2, to: Vector2) -> void:
    var coin := coin_scene.instantiate()
    coin.position = from
    add_child(coin)

    var tween := create_tween()
    tween.tween_property(coin, "position", to, 0.5)
    tween.tween_callback(coin.queue_free)

    var label := Label.new()
    label.text = "+$" + str(int(amount))
    label.position = from
    add_child(label)

    var label_tween := create_tween()
    label_tween.tween_property(label, "position:y", label.position.y - 30, 0.5)
    label_tween.parallel().tween_property(label, "modulate:a", 0.0, 0.5)
    label_tween.tween_callback(label.queue_free)

Statistics Dashboard

class_name StatsDashboard
extends Control

@export var graph_history_hours := 24
var income_history: Array[float] = []
var expense_history: Array[float] = []

func record_financial_tick(income: float, expenses: float) -> void:
    income_history.append(income)
    expense_history.append(expenses)

    # Keep last N entries
    while income_history.size() > graph_history_hours:
        income_history.pop_front()
        expense_history.pop_front()

    queue_redraw()

func _draw() -> void:
    # Draw income/expense graph
    draw_line_graph(income_history, Color.GREEN)
    draw_line_graph(expense_history, Color.RED)

Progression & Unlocks

class_name UnlockSystem
extends Node

var unlocks: Dictionary = {
    "basic_facility": true,
    "advanced_facility": false,
    "marketing": false,
    "automation": false
}

var unlock_conditions: Dictionary = {
    "advanced_facility": {"money_earned": 50000},
    "marketing": {"reputation": 70},
    "automation": {"workers_hired": 20}
}

var progress: Dictionary = {
    "money_earned": 0.0,
    "workers_hired": 0
}

func check_unlocks() -> Array[String]:
    var newly_unlocked: Array[String] = []

    for unlock in unlock_conditions:
        if unlocks[unlock]:
            continue  # Already unlocked

        var conditions := unlock_conditions[unlock]
        var all_met := true

        for condition in conditions:
            if progress.get(condition, 0) < conditions[condition]:
                all_met = false
                break

        if all_met:
            unlocks[unlock] = true
            newly_unlocked.append(unlock)

    return newly_unlocked

Common Pitfalls

PitfallSolution
Economy too easy to breakExtensive balancing, soft caps, diminishing returns
Boring early gameFront-load interesting decisions, quick early progression
Information overloadProgressive disclosure, collapsible UI panels
No clear goalsMilestones, achievements, scenarios
Tedious micromanagementAutomation unlocks, batch operations

Godot-Specific Tips

  1. UI: Use Control nodes extensively, Tree for lists, GraphEdit for connections
  2. Performance: Process entities in batches, not every frame
  3. Save/Load: Convert all game state to Dictionary for JSON serialization
  4. Isometric view: Use Camera2D with orthographic projection

Reference

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

34.67%
按下载量换算245

Claude

30.76%
按下载量换算217

Cursor

19.81%
按下载量换算140

Gemini CLI

8.83%
按下载量换算62

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

权限需确认

当前来源未能明确判断权限范围,默认进入异常复核队列。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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