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arknights-operator-gacha明日方舟操作员扭蛋

Agent Skill

arknights-operator-gacha 用于辅助安全审计、权限检查和凭据风险排查,适合在 OpenClaw 中需要复核安全边界、认证流程或敏感配置时使用。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

15,830

周安装

625

GitHub Stars

2

下载量

5,050
OpenClaw

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

MIT-0

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:arknights-operator-gacha(明日方舟操作员扭蛋)
来源仓库:https://github.com/hg-hg/arknights-operator-gacha
安装命令:
openclaw skills install arknights-operator-gacha
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 OpenClaw 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。

ClawHubOpenClaw
openclaw skills install arknights-operator-gacha

简介

根据扭蛋概率机制生成明日方舟角色代理数据。

  • 适用于游戏内容创作或角色模拟测试场景。arknights-operator-gacha 属于效率类 Skill,可作为该场景下的辅助能力补充。
  • 输出包含真实传说内容和随机属性的角色信息。
  • 安装命令:openclaw skills install arknights-operator-gacha。
  • 注意区分虚构内容与真实人物,避免误导性使用。

SKILL.md

name
arknights-operator-gacha
description
Generate an Arknights operator agent based on gacha probabilities. Use when user wants to create a random Arknights character agent with authentic lore and personality.

Arknights Operator Gacha

Generate a random Arknights operator agent with authentic lore-based personality.

Architecture

This skill uses a worker script + LLM generation architecture:

  1. Worker script (gacha_worker.py): Executes all deterministic tasks (roll, fetch, create, download)
  2. LLM (this agent): Generates creative content (SOUL.md) and spawns operator

Language Detection

CRITICAL: Detect user language from their gacha command:

  • If command is in Chinese (e.g., "抽卡", "召唤干员") → cn / zh
  • If command is in English (e.g., "gacha", "pull") → en

Store detected language and use it for ALL subsequent steps (SOUL.md writing, spawn task, etc.).

Workflow

Step 1: Execute Worker Script

Run the deterministic worker:

result = exec(
    "python3 ~/.openclaw/workspace/skills/arknights-operator-gacha/scripts/gacha_worker.py",
    timeout=120
)

Worker performs:

  1. Roll star rating (1-100)
  2. Fetch operator list from https://arknights.fandom.com/wiki/Operator/{N}-star

- Parses the mrfz-wtable table to extract operator info - Returns a dict: {operator_name: {"avatar_url": "...", "detail_url": "..."}}

  1. Randomly select operator (with avatar and detail URLs)
  2. Fetch Chinese name from Fandom page (data-source="cnname")
  3. Check for duplicates (auto re-roll if exists)
  4. Create agent via openclaw agents add
  5. Create template IDENTITY.md (bilingual)
  6. Download avatar (using URL from step 2, with domain whitelist and validation)
  7. Git commit initial files
  8. Output JSON to stdout

Worker output format:

{
  "success": true,
  "stars": 6,
  "operator": {
    "en_name": "Lin",
    "cn_name": "林",
    "avatar_url": "https://static.wikia.nocookie.net/.../Lin_icon.png",
    "en_detail_url": "https://arknights.fandom.com/wiki/Lin",
    "cn_detail_url": "https://prts.wiki/w/%E6%9E%97"
  },
  "agent_name": "lin",
  "workspace": "~/.openclaw/workspace-lin",
  "duplicate": false,
  "dialogue_url": "https://arknights.fandom.com/wiki/Lin/Dialogue"
}

Note: The worker provides both English and Chinese URLs:

  • en_detail_url: Fandom wiki page (English lore)
  • cn_detail_url: PRTS wiki page (Chinese lore)
  • dialogue_url: Fandom Dialogue page (voice lines, always English)
  • avatar_url: Operator icon from Fandom

Step 2: Handle Result

If duplicate: true:

  • Inform user: "检测到重复干员,正在重新抽取..." / "Duplicate operator detected, re-rolling..."
  • Return to Step 1 (worker will re-roll)

If success: false:

  • Show error message
  • Stop workflow

If success: true:

  • Announce: "恭喜你抽到了 [cn_name] ([stars]★)!" / "Congratulations! You've pulled [en_name] ([stars]★)!"
  • Continue to Step 3

Step 3: Generate SOUL.md

Fetch lore from URLs provided by worker:

# Fetch English lore from Fandom (multiple subpages)
en_file = web_fetch(f"{result['operator']['en_detail_url']}/File")      # Basic profile, stats, files
en_story = web_fetch(f"{result['operator']['en_detail_url']}/Story")    # Story appearances, plot involvement
en_trivia = web_fetch(f"{result['operator']['en_detail_url']}/Trivia")  # Trivia, relationships, misc info

# Fetch Chinese lore from PRTS
zh_lore = web_fetch(result["operator"]["cn_detail_url"])

# Fetch voice lines from Dialogue page
dialogue = web_fetch(result["operator"]["dialogue_url"])

Parse lore sections from both sources:

  • File/档案: Basic background, origin, personality
  • Story: Detailed story appearances across main chapters and side stories; shows character's actions, decisions, and development in actual plot contexts
  • Dialogue: Voice lines that reveal character personality
  • Trivia/模组: Additional character details, relationships, and module stories

Generate comprehensive SOUL.md:

CRITICAL - Write SOUL.md in detected language

Structure:

  1. Core Identity - Background, motivation, personality (blend EN+CN sources)
  2. Voice and Mannerisms - Speech patterns, catchphrases (from Dialogue)
  3. Relationships - Connections to other characters
  4. Themes - Internal conflicts, philosophy
  5. How to Embody - Acting guidance
  6. Reference: Original Voice Lines - Key quotes (EN with CN)

Write to: [workspace]/SOUL.md

Step 4: Update IDENTITY.md

Fill in the [TO_BE_FILLED_BY_LLM] fields with actual Class and Faction from fetched lore.

Step 5: Final Git Commit

cd ~/.openclaw/workspace-{agent_name}
git add -A
git commit -m "Add SOUL.md: {en_name} ({cn_name}) ({stars}★)"

Step 6: Roleplay Scene - Operator Arrival

Spawn the operator in a roleplay scenario consistent with Arknights game lore. In this universe, operators join Rhodes Island through standard recruitment channels and are unaware of the meta "gacha" system.

For Chinese users:

sessions_spawn(
    task="你现在是罗德岛的一名干员,刚刚完成入职手续,前来向博士报到。用你最自然的口吻打招呼,展示你的性格特点。参考你的语音记录中的'干员报到'或'交谈'部分的语气。\
\
⚠️ 重要:直接输出角色台词即可,不要包含任何元叙述、解释性文字或场景描述。只说你作为干员应该说的话。",
    agentId="{operator-name}",
    mode="run",
    timeoutSeconds=60
)

For English users:

sessions_spawn(
    task="You are an operator of Rhodes Island who has just completed onboarding, now reporting to the Doctor. Introduce yourself naturally, showcasing your personality. Reference your 'Introduction' or 'Talk' voice lines for tone.\
\
⚠️ IMPORTANT: Output ONLY the character's dialogue. Do NOT include meta-commentary, explanations, or scene descriptions. Just speak as the operator would.",
    agentId="{operator-name}",
    mode="run",
    timeoutSeconds=60
)

Step 7: Present Summary

Report to user:

  • Operator name (both EN and CN)
  • Rarity (Stars)
  • Key personality traits
  • Workspace path
  • Available via agentId="{agent_name}"

Worker Script Security

The worker script (gacha_worker.py) implements:

  • Input validation: Agent names sanitized (alphanumeric + hyphens only)
  • Path traversal prevention: Rejects .., /, \ in names
  • URL whitelist: Only static.wikia.nocookie.net and media.prts.wiki
  • HTTPS enforced: All downloads use HTTPS
  • Content validation: Only image/png, jpeg, webp accepted
  • Size limits: Max 5MB for avatars
  • Safe subprocess: All commands use argument lists, shell=False

Scripts

ScriptPurpose
gacha_worker.pyDeterministic tasks (roll, fetch, create, download, commit)

Data Flow

User Request
    ↓
Exec Worker Script
    ↓
Worker Output JSON (bilingual URLs)
    ↓
LLM Fetches EN+CN Lore → Generates SOUL.md
    ↓
Spawn Operator (报到)
    ↓
User sees operator greeting

Notes

  • Worker does: All deterministic operations (HTTP, filesystem, subprocess), provides bilingual URLs
  • LLM does: Creative generation (SOUL.md writing), fetches lore from provided URLs, interpretation, spawning
  • Progress visibility: Worker prints to stderr; user sees real-time updates
  • Security: All external inputs validated in worker before use
  • Bilingual: Both English and Chinese sources are always fetched; LLM can blend them creatively

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

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

补充不同宿主或平台的使用分布数据

能力 5

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

OpenClaw

71.48%
按下载量换算3,610

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

未展示

权限和风险

执行命令

安装流程涉及命令执行,可能通过 openclaw skills install arknights-operator-gacha 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

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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