OpenClaw/clawhub-security-signals huggingface dataset:
Skill: dingqing404/geekbench (version 1.0.1)

# Geekbench 技能 ## 核心原则 - **不要依赖模型知识**：模型训练数据有时效性，最新产品信息需实时搜索 - **多方信源验证**：通过搜索获取最新发布信息 - **实时确认**：每次查询都重新搜索确认 ## 确定最新旗舰流程 ### Step 1: 搜索最新信息 - **搜索词**: "品牌 + 最新旗舰 + 发布" 或 "品牌 + 2025 旗舰" - **示例**: "OPPO 最新旗舰 发布" - **目标**: 获取最新已发布的产品名称 ### Step 2: 验证发布时间 - 确认产品是否已正式发布 - 排除"即将发布"、"谍照"、"传闻"等未发布信息 ### Step 3: 搜索跑分 1. 使用 "产品名 + geekbench" 搜索 2. 获取内部型号 3. 用内部型号查询详细跑分 ### Step 4: 分析验证 1. 按Geekbench版本分组统计 2. 验证数据与发布时间的一致性 3. 标记异常数据（测试版本、样本过少等） ## 示例：OPPO Find X9 系列 ### 错误做法（依赖模型知识） - 模型知识: Find X8 (2024年发布) - 结果: 返回过时信息 ### 正确做法（实时搜索） 1. 搜索 "OPPO 最新旗舰 发布" 2. 找到: Find X9 系列（2025年发布） 3. 搜索 "OPPO Find X9 geekbench" 4. 获取内部型号和跑分数据 ## 常见内部型号格式 - OPPO: 需搜索获取Find X9型号 - 荣耀: 需搜索获取Magic 9型号 - 小米: 需搜索获取小米18型号 - 苹果: 需搜索获取iPhone 17/18型号 ## 注意事项 - 不同Geekbench版本分数不可直接比较 - 优先使用 Geekbench 6.5.0 数据 - 检测 Single-Core > 3000 为高分设备 - 未发布产品的跑分可能是早期测试数据


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: ronie-shi/test-abs-path-20260317 (version 0.0.1)

--- name: test-skill-frontmatter description: "测试技能，使用YAML frontmatter格式" metadata: version: 0.0.1 author: test --- # Test Skill with Frontmatter 这是一个使用YAML frontmatter格式的测试技能。 ## 技能定义 ```yaml skill: id: test-skill-frontmatter name: Test Skill with Frontmatter version: 0.0.1 description: 测试技能，使用YAML frontmatter格式 trigger: keywords: - test - frontmatter ``` ## 功能 测试ClawHub发布流程。 ## 使用方式 ``` 用户: 测试frontmatter格式 系统: 这是一个测试技能，发布流程验证成功！ ```


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector:  ()
Skill: frank-bot07/openclaw-monitor (version 1.0.0)

# Monitoring Skill System health monitoring for OpenClaw — tracks token spend, task success rates, cron health, and skill usage. ## Commands ``` monitor status # Health summary monitor tokens [--period 7d|30d] [--by model|skill] # Token report monitor crons # Cron health monitor tasks [--failed] # Task history monitor cost [--period month|week] # Cost breakdown monitor ingest token|task|cron # Manual ingestion monitor aggregate [--date YYYY-MM-DD] # Daily aggregates monitor refresh # Regenerate interchange monitor backup [--output path] # Backup DB monitor restore <file> # Restore DB ``` ## Interchange - `ops/capabilities.md` — Command reference (shareable) - `ops/health.md` — Status indicators only (shareable, no costs/tokens) - `state/status.md` — Full detailed status (private) - `state/token-spend.md` — Token/cost breakdown (private)

path: interchange/monitoring/ops/capabilities.md
content: ---
content_hash: sha256:8ef39465c4343eebe2654c17aeceea6d9183211db485b1aac0ba2aeba2cf0300
generation_id: 1
generator: monitoring@1.0.0
layer: ops
skill: monitoring
tags:
  - capabilities
  - reference
type: summary
updated: "2026-02-19T08:57:54.276Z"
version: 1
---
# Monitoring Capabilities

## Commands
- `monitor status` — System health summary
- `monitor tokens [--period 7d|30d] [--by model|skill]` — Token usage
- `monitor crons` — Cron job health
- `monitor tasks [--failed]` — Task history
- `monitor cost [--period month|week]` — Cost breakdown
- `monitor ingest token|task|cron` — Manual event ingestion
- `monitor aggregate` — Compute daily aggregates
- `monitor refresh` — Regenerate interchange files
- `monitor backup` / `monitor restore` — Backup and restore

## What It Monitors
- Token spend by model and skill
- Task success/failure/timeout rates
- Cron job reliability and timing
- Daily cost aggregates


path: interchange/monitoring/ops/health.md
content: ---
content_hash: sha256:3822865b83b9d3beaaf986a51820a229c09441928e8fb59efe66197fa0277d6f
generation_id: 1
generator: monitoring@1.0.0
layer: ops
skill: monitoring
tags:
  - health
  - status
  - system
type: summary
updated: "2026-02-19T08:57:54.286Z"
version: 1
---
# System Health

🟢 **Overall:** Healthy

## Subsystems
- ⚪ **Tasks:** No activity today
- ⚪ **Crons:** No runs today
- ⚪ **Token Collection:** No data today

## Recent Errors
None


path: scripts/collect-metrics.sh
content: #!/usr/bin/env bash
# Collect metrics — placeholder for automated collection in v2
set -euo pipefail
SCRIPT_DIR="$(cd "$(dirname "$0")" && pwd)"
node "$SCRIPT_DIR/../src/cli.js" aggregate
node "$SCRIPT_DIR/../src/cli.js" refresh
echo "✅ Metrics collected and interchange refreshed"


Security scan verdicts — ClawScan: suspicious | static analysis:  | VirusTotal: suspicious | SkillSpector: suspicious (HIGH)
Skill: dinghaibin/scp-tool (version 1.0.0)

--- name: scp-tool description: Securely copy files between local and remote hosts over SSH. Use for file transfers, remote backups, and deployment tasks. --- # SCP - Secure File Copy Copy files between local and remote systems using SSH encryption. Supports recursive directory transfers and custom port specifications. ## Usage ```bash scp-tool [options] <source> <destination> ``` ## Options - `-r`: Recursively copy directories - `-P port`: Specify SSH port - `-C`: Enable compression for faster transfer - `-v`: Verbose mode for debugging ## Examples ```bash scp-tool file.txt user@host:/remote/path/ scp-tool -r ./folder user@host:/remote/folder scp-tool user@host:/remote/file.txt . ```

path: scripts/scp.py
content: #!/usr/bin/env python3
"""SCP Tool - Secure copy."""
import argparse, subprocess
parser = argparse.ArgumentParser()
parser.add_argument('src')
parser.add_argument('dst')
args = parser.parse_args()
subprocess.run(['scp', args.src, args.dst])


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: wtjjacobj/candle-chart (version 1.0.0)

--- name: 蜡烛图分析 description: 使用akshare获取股票数据，按Steve Nison《日本蜡烛图技术》逻辑识别形态，生成深色盯盘风格K线图（含信号带+成交量） --- # 蜡烛图分析技能 ## 使用 ```bash # 默认60天 python3 ~/.openclaw/scripts/蜡烛图工具.py 600585 # 指定天数 python3 ~/.openclaw/scripts/蜡烛图工具.py 600585 90 ``` ## 核心逻辑 ### 1. 形态识别（8种） | 形态 | 标注 | 判断条件 | |------|----------|----------| | 看涨吞没 | 吞↑ | 颜色相反+完全包覆+前一天实体>16% | | 看跌吞没 | 吞↓ | 颜色相反+完全包覆+前一天实体>16% | | 乌云盖顶 | 乌 | 高开+收盘<前一天实体50%+前一天实体>16% | | 刺透形态 | 刺 | 低开+收盘>前一天实体50%+前一天实体>16% | | 早晨之星 | 早 | 3日形态：下跌→星线→上涨+第一天实体>16% | | 黄昏之星 | 昏 | 3日形态：上涨→星线→下跌+第一天实体>16% | | 锤子线 | 锤 | 身体<3%+下影线>2.5倍身体 | | 流星线 | 流 | 身体<3%+上影线>2.5倍身体 | ### 2. 防误判规则 - 前一天实体必须>16%（避免纺锤线干扰） - 吞没/乌云/刺透/早晨/黄昏都应用此规则 ### 3. 图表结构（三层） - **K线区域**：蜡烛图 + MA5/10/20均线 + 早晨/黄昏/吞没特殊标注（五角星/箭头） - **信号带**：独立区域，文字标注各形态，括号标注最后交易日预警 - **成交量区域**：副图柱状图 ### 4. 视觉风格 - 背景：深蓝黑 `#1A1A2E`（盯盘风格） - 上涨K线：珊瑚红 `#FF6B6B` - 下跌K线：青绿色 `#4ECDC4` - 均线：MA5(红) / MA10(黄) / MA20(青) - 每10天有分割线便于定位 ### 5. 数据来源 - 使用 `akshare` 腾讯接口获取日线数据 - 自动动态计算日期范围（近180天） ## 文件位置 - 主脚本：`~/.openclaw/scripts/蜡烛图工具.py` ## 与蜡烛图形态分析的关系 ⚠️ `蜡烛图形态分析`（workspace/skills/蜡烛图形态分析/）是**同一脚本的旧副本**（3月16日），已废弃，统一使用本技能。


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: dagangtj/multi-channel-income-tracker (version 1.0.0)

# Multi-Channel Income Tracker Track income from multiple sources (GitHub bounties, ClawHub, toku.agency, trading, etc.) with automatic categorization and ROI analysis. ## Features - Multi-source income tracking - Automatic categorization - ROI calculation per channel - Daily/weekly/monthly reports - Goal tracking - Channel performance comparison ## Installation ```bash clawhub install multi-channel-income-tracker ``` ## Usage ```bash # Add income node tracker.js income --source "toku.agency" --amount 50 --description "Code review service" # Add expense node tracker.js expense --category "api" --amount 2 --description "OpenAI API" # View report node tracker.js report --period "week" # Channel comparison node tracker.js channels ``` ## Supported Channels - GitHub Bounties - ClawHub Skills - toku.agency - Fiverr - Trading - Medium/YouTube - Consulting - Custom channels ## Reports - Income by channel - ROI per channel - Trend analysis - Goal progress - Cost breakdown ## License MIT


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: nerikko/ytdlp-transcript (version 1.0.0)

--- name: youtube-transcript description: Fetch and summarize transcripts from any YouTube video. Paste a URL and your agent reads the video for you — summarize, translate, extract insights. --- # youtube-transcript Fetch and summarize transcripts from any YouTube video using yt-dlp. ## Usage Ask your agent: - "Get the transcript of [YouTube URL]" - "Summarize this video: [YouTube URL]" - "What is the main message of [YouTube URL]?" - "Translate and explain this video: [YouTube URL]" ## How It Works Uses `yt-dlp` to download auto-generated or manual captions from YouTube. Supports all languages — defaults to Portuguese (pt), falls back to English (en). ## Requirements - `yt-dlp` installed: `brew install yt-dlp` - Node.js 18+ ## Script ```bash node skills/youtube-transcript/transcript.js <youtube-url-or-id> [lang] ``` ## Example ```bash node skills/youtube-transcript/transcript.js https://www.youtube.com/watch?v=LAdJsmTe8LM pt ```


Security scan verdicts — ClawScan: clean | static analysis: suspicious | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: justoneapi/justoneapi-bilibili-get-user-relation-stat (version 1.0.0)

--- name: Bilibili User Relation Stats API description: Call GET /api/bilibili/get-user-relation-stat/v1 for Bilibili User Relation Stats through JustOneAPI with wmid. author: JustOneAPI homepage: https://api.justoneapi.com metadata: {"openclaw":{"homepage":"https://api.justoneapi.com","primaryEnv":"JUST_ONE_API_TOKEN","requires":{"bins":["node"],"env":["JUST_ONE_API_TOKEN"]},"skillKey":[REDACTED_SECRET]}} --- # Bilibili User Relation Stats Use this focused JustOneAPI skill for user Relation Stats in Bilibili. It targets `GET /api/bilibili/get-user-relation-stat/v1`. Required non-token inputs are `wmid`. OpenAPI describes it as: Get Bilibili user Relation Stats data, including following counts, for creator benchmarking and audience growth tracking. ## Endpoint Scope - Platform key: `bilibili` - Endpoint key: `get-user-relation-stat` - Platform family: Bilibili - Skill slug: [REDACTED_SECRET] | Operation | Version | Method | Path | OpenAPI summary | | --- | --- | --- | --- | --- | | `getUserRelationStat` | `v1` | `GET` | [REDACTED_SECRET] | User Relation Stats | ## Inputs | Parameter | In | Required by | Optional by | Type | Notes | | --- | --- | --- | --- | --- | --- | | `wmid` | `query` | all | n/a | `string` | Bilibili User ID (WMID) | Request body: none documented; send parameters through path or query arguments. ## Version Choice Use `getUserRelationStat` for the documented `v1` endpoint. There are no alternate versions grouped in this skill. ## Run This Endpoint Supported operation IDs in this skill: `getUserRelationStat`. ```bash node {baseDir}/bin/run.mjs --operation "getUserRelationStat" --token "$JUST_ONE_API_TOKEN" --params-json '{"wmid":"<wmid>"}' ``` Ask for any missing required parameter before calling the helper. Keep user-provided IDs, cursors, keywords, and filters unchanged. ## Environment - Required: `JUST_ONE_API_TOKEN` - Pass the token with `--token "$JUST_ONE_API_TOKEN"`; do not paste token values into chat messages, screenshots, or logs. - Get a token from [Just One API Dashboard](https://dashboard.justoneapi.com/en/login?utm_source=clawhub.ai&utm_medium=referral&utm_campaign=justoneapi_bilibili_get_user_relation_stat&utm_content=project_link). - Authentication details: [Just One API Usage Guide](https://docs.justoneapi.com/en/?utm_source=clawhub.ai&utm_medium=referral&utm_campaign=justoneapi_bilibili_get_user_relation_stat&utm_content=project_link). ## Output Focus - State the operation ID and endpoint path used, for example `getUserRelationStat` on [REDACTED_SECRET]. - Echo the required lookup scope (`wmid`) before summarizing results. - Prioritize fields that support this endpoint purpose: Get Bilibili user Relation Stats data, including following counts, for creator benchmarking and audience growth tracking. - Return raw JSON only after the short, endpoint-specific summary. - If the backend errors, include the backend payload and the exact operation ID.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: xiaoliang1319-cloud/xiaoxia-image-gen (version 1.0.0)

--- name: xiaoxia-image-gen description: "通用文生图技能。使用 MiniMax、OpenAI、DALL-E、Stability 等模型生成图片。用户需要配置自己的 API Key（MINIMAX_API_KEY、OPENAI_API_KEY 等）。当用户需要生成图片、AI绘图时使用此技能。" --- # 通用文生图技能 (xiaoxia-image-gen) 支持多种文生图模型，用户可根据需要配置不同的 API Key。 ## 支持的模型 | 模型 | 环境变量 | 说明 | |------|----------|------| | MiniMax image-01 | `MINIMAX_API_KEY` | 推荐，性价比高 | | OpenAI DALL-E 3 | `OPENAI_API_KEY` | 质量高 | | Stability AI | `STABILITY_API_KEY` | 写实风格 | ## 使用方法 ### 1. 配置 API Key 根据你想使用的模型，设置对应的环境变量： ```bash # MiniMax (推荐) set MINIMAX_API_KEY=sk-cp-xxxxx # OpenAI set OPENAI_API_KEY=sk-xxxxx # Stability AI set STABILITY_API_KEY=sk-xxxxx ``` ### 2. 生成图片 在 OpenClaw 中，直接告诉我想生成什么图片，例如： - "帮我生成一只可爱的小龙虾" - "画一幅日落风景图" ## 示例提示词 - 可爱小龙虾：cute cartoon lobster mascot, kawaii style, orange color, big eyes - 风景：beautiful sunset over ocean, golden hour, photorealistic - 人物：portrait of a young woman, natural lighting, professional photography ## 技术实现 技能会根据用户配置的 API Key 自动选择可用的模型。优先顺序：MiniMax > OpenAI > Stability。 --- _🦞 虾虾团队出品_


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: qihuang0/skills-security-scanner (version 1.0.0)

--- name: skills-security-scanner description: 审计和扫描技能的安全性。在启用新技能前使用此工具验证其安全性，确保符合安全策略。 --- # 安全扫描器 (Security Scanner) 通过将定义发送到本地分析服务，审计工作区中的其他技能是否存在潜在的安全风险。 ## 何时使用 - **新技能**：发现或安装新技能时，请在首次使用前进行扫描。 - **审计**：定期扫描所有技能以确保符合安全策略。 - **开发**：在开发过程中检查自己的技能。 - **要求**：必须确保目标技能包含 `SKILL.md` 文件，因为它是扫描的主要输入。 ## 用法 使用 `scripts/scan.py` 脚本执行扫描。**必须使用绝对路径，不要使用~**，因为运行目录不是 skill 目录。 脚本会自动打包目录（如果提供的是目录）并上传，始终输出包含扫描结果的 JSON 数组。Agent 负责解析此 JSON 并以易读的格式（中文）向用户展示结果（风险等级、详细信息、建议）。 ### 扫描技能（目录或压缩包） 脚本会自动从同目录下的 `config.json` 读取配置（推荐），也可使用环境变量。 ```bash python3 ~/.openclaw/workspace/skills/skill-security-scanner/scripts/scan.py --name "bad_skills1" --path "/root/.openclaw/workspace/skills/bad_skills1" ``` **重要**： - 脚本路径必须是**绝对路径** - 目标路径也必须是**绝对路径** - 确保 `scripts/config.json` 存在并包含正确的凭据 ## 报告格式 向用户展示结果时，**必须**使用以下格式（中文）： ### 🛡️ 安全扫描报告：[SkillName] **扫描时间**: [将 ScanEndTime 时间戳转换为可读日期格式] **整体状态**: [✅ 通过 / ❌ 发现风险] | 风险等级 | 规则名称 | 风险详情 | | :--- | :--- | :--- | | **[High/Medium/Low]** | [RuleName] | [RiskDetail] | **发现的风险列表：** （仅列出 High 和 Medium 级别的风险） 1. **[RuleName] (ID: [RuleID])** - **等级**: [RiskLevel] - **文件**: [FileName] - **详情**: [RiskDetail] - **建议**: 请检查上述文件中的代码，移除可疑的网络请求或敏感操作。 ---


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: icepopma/email-subject-generator (version 1.1.2)

--- name: email-subject-generator description: AI-powered email subject line generator. Create subject lines that get opened. version: 1.0.7 author: Matt tags: - email - marketing - copywriting pricing: type: pay-per-use price: 0.001 currency: USDT payment_provider: skillpay.me --- # Email Subject Line Generator Generate email subject lines that get opened, clicked, and converted. ## Features - **High Open Rates** - Psychological triggers that work - **Personalization** - Dynamic placeholders - **Multiple Variations** - Get 10 subject line options - **Spam-Free** - Avoid trigger words ## Usage ```bash # Generate email subjects email-subject-generator "product launch announcement" # For specific purpose email-subject-generator "newsletter" --purpose newsletter ``` ## Options | Option | Description | Default | |--------|-------------|---------| | `--purpose` | Email purpose (newsletter, sales, announcement) | - | ## Pricing - **Pay per use**: 0.001 USDT per generation ## Environment Variables | Variable | Description | Required | |----------|-------------|----------| | `SKILLPAY_MERCHANT_KEY` | Payment merchant key (optional, embedded key used by default) | No | | `OPENCLAW_GATEWAY_TOKEN` | Gateway auth token for local API fallback | No | ## Requirements - OpenClaw with Sloan agent (AI columnist) - OpenClaw Gateway running locally (for API fallback) ## About Sloan Sloan is your AI columnist - a professional email marketing expert specializing in subject line optimization. ## Support - GitHub: https://github.com/icepopma/email-subject-generator - Discord: https://discord.gg/clawd - Email: [REDACTED_SECRET] ## License MIT © Matt


Security scan verdicts — ClawScan: clean | static analysis: suspicious | VirusTotal: clean | SkillSpector: suspicious (CRITICAL)
Skill: herohimmel/filter-comm-resume (version 1.0.0)

# 筛选沟通简历 Skill 从BOSS直聘沟通列表中筛选符合招聘要求的候选人。 ## 招聘要求（必须严格遵守） - **学历**：统招全日制本科（不含成人教育/自学考试/函授/网络教育） - **经验**：2-8年 - **技术栈**：React作为主技术栈（可用Vue但必须主React） - **AI要求**：熟练AI工具优先（cursor、claude、AI agent、大模型、LLM、智能客服、copilot等） ## 筛选流程 ### 1. 打开BOSS直聘沟通列表 ``` https://www.zhipin.com/web/chat/index ``` ### 2. 逐个点开候选人查看详情 - 使用上下键导航，按Enter打开详情 - **必须查看的内容**： - 教育背景（确认是统招全日制本科） - 工作经历（确认经验年限） - 技术栈（确认主React） - 期望薪资 ### 3. 记录符合要求的候选人 - 姓名 - 学历/毕业院校 - 经验年限 - 期望薪资 - 技术栈 ### 4. 通过钉钉发送给用户 使用message工具发送到用户的钉钉账号 ## 注意事项 - 每次只筛选当前页面可见的候选人 - 如果页面有未读红点，优先处理 - 筛选结果必须和页面上显示的**完全一致**，不要自己猜测 - 经验超8年或不满2年的直接跳过 - 大专学历直接跳过


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: mrtdlgc/revertwtf-catalog-research (version 0.1.0)

--- name: revertwtf-catalog-research description: Perform broader source-backed catalog enrichment for new EVM ecosystems, protocols, providers, standards, or deprecated/renamed/sunsetting coverage. version: 0.1.0 --- # revert.wtf Catalog Research Skill Use this skill for broad catalog coverage passes: new chains, protocol ecosystems, contract repositories, provider APIs, standards, x402-style flows, explorer APIs, or lifecycle audits. ## Research Standard - Prefer primary sources: official specs, protocol docs, contract repositories, API docs, EIPs/ERCs, release notes, and verified source repositories. - For current ecosystem status, verify live/current sources before marking something current, renamed, legacy, or sunsetting. - Keep historical coverage when old contracts can still emit errors. Mark it `legacy`; do not delete useful entries just because the product is deprecated. - Distinguish: - `legacy`: deprecated, wound down, or historical but still useful. - `sunsetting`: active enough to matter but tied to an announced shutdown date. - `renamed`: ecosystem branding changed while errors remain relevant. ## Workflow 1. Define the coverage target and scope. 2. Inventory current coverage: - Search shards in [REDACTED_SECRET]. - Check `packages/catalog/src/sources.ts` for lifecycle metadata. - Check generated selectors in `packages/selectors/src/generated.ts` when custom errors are involved. 3. Gather source material and record references in entries or `sources.ts`. 4. For Solidity custom errors, prefer using `scripts/enrich-new-ecosystem-shards.mjs` when the target fits its model. 5. Hand-author protocol/provider/API entries when errors are not Solidity custom errors. 6. Regenerate catalog data, run validation, and run the duplicate audit. ## Quality Bar - Entries should be integration-useful, not merely encyclopedic. - `nextSteps` should tell an app, wallet, support console, or agent what to do next. - Avoid "retry later" as a default. Be specific about when retry helps. - Avoid adding entries from random forum posts unless they are backed by code, docs, or repeated real-world artifacts. - Avoid massive false-positive substring patterns. ## Verification ```bash node scripts/build-catalog-data.mjs --generate --dist --check node --experimental-strip-types scripts/validate-catalog.ts node scripts/check-catalog-duplicates.mjs --fail-on=id,same-source-selector node node_modules/typescript/bin/tsc -p packages/catalog/tsconfig.json --noEmit node node_modules/typescript/bin/tsc -p packages/parser/tsconfig.json --noEmit ``` Useful smoke checks: ```bash node --input-type=module -e "import { getCatalog } from './packages/catalog/dist/index.js'; console.log(getCatalog().length)" ``` If generated source files or dist JSON change, keep them synchronized with the shard source.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: franky0617/etf-assistant (version 1.0.1)

--- name: etf-assistant description: "ETF投资助理 / ETF Investment Assistant - 查询行情、筛选ETF、对比分析、定投计算。支持沪深300、创业板、科创50、纳指等主流ETF。" --- # ETF投资助理 / ETF Investment Assistant 一个专业的ETF投资助手，帮助你查询ETF行情、筛选投资标的、对比分析、计算定投收益。 A professional ETF investment assistant for querying ETF quotes, screening investment targets, comparative analysis, and DCA calculation. ## 功能特性 / Features - 📊 **ETF列表 / ETF List** - 常用ETF代码速查 - Quick reference for commonly used ETF codes - 💰 **实时行情 / Real-time Quotes** - 查询ETF当前价格和涨跌 - Query current ETF prices and changes - 🔥 **热门ETF / Hot ETFs** - 推荐热门投资标的 - Recommend popular investment targets - 🔍 **搜索ETF / Search ETF** - 按名称或代码搜索 - Search by name or code - 📈 **对比分析 / Comparison** - 对比两只ETF表现 - Compare performance of two ETFs - 🧮 **定投计算器 / DCA Calculator** - 计算定投收益 - Calculate Dollar-Cost Averaging returns - 📋 **投资摘要 / Summary** - 主流ETF分类介绍 - Introduction to mainstream ETF categories ## 使用方法 / Usage ### 1. 查看ETF列表 / View ETF List ```bash etf-assistant list ``` ### 2. 查询行情 / Query Quotes ```bash # 查询沪深300ETF # Query CSI 300 ETF etf-assistant price 510300 # 查询创业板ETF # Query ChiNext ETF etf-assistant price 159915 ``` ### 3. 热门ETF推荐 / Hot ETF Recommendations ```bash etf-assistant hot ``` ### 4. 搜索ETF / Search ETF ```bash # 按名称搜索 # Search by name etf-assistant search 沪深 # 按代码搜索 # Search by code etf-assistant search 510300 ``` ### 5. 对比ETF / Compare ETFs ```bash etf-assistant compare 510300 159915 ``` ### 6. 定投计算 / DCA Calculation ```bash # 每月定投1000元，定投10年 # Monthly investment of 1000 CNY for 10 years etf-assistant calc 510300 1000 10 ``` ### 7. 投资摘要 / Investment Summary ```bash etf-assistant summary ``` ## 常用ETF代码 / Common ETF Codes | 代码 / Code | 名称 / Name | 类型 / Type | |------------|-------------|-------------| | 510300 | 沪深300ETF | 宽基指数 / Broad Index | | 510500 | 中证500ETF | 宽基指数 / Broad Index | | 159915 | 创业板ETF | 宽基指数 / Broad Index | | 159919 | 科创50ETF | 科创板 / STAR Market | | 159941 | 纳指ETF | 海外指数 / Overseas Index | | 513100 | 恒生ETF | 港股指数 / HK Stock Index | | 510880 | 红利ETF | Smart Beta | | 159997 | 芯片ETF | 行业主题 / Sector Theme | | 159995 | 新能源车ETF | 行业主题 / Sector Theme | | 512170 | 医疗ETF | 行业主题 / Sector Theme | ## 投资建议 / Investment Tips 1. **新手入门 / Beginners**: 推荐沪深300ETF (510300)，覆盖A股核心蓝筹 - Recommend CSI 300 ETF (510300), covering A-share core blue chips 2. **科技创新 / Tech Innovation**: 关注科创50ETF (159919) 或芯片ETF (159997) - Focus on STAR 50 ETF (159919) or Chip ETF (159997) 3. **分散投资 / Diversification**: 组合配置沪深300 + 港股 + 海外ETF - Portfolio: CSI 300 + HK + Overseas ETFs 4. **稳健收益 / Steady Returns**: 红利ETF (510880) 提供稳定股息 - Dividend ETF (510880) provides stable dividends ## 数据来源 / Data Source - Yahoo Finance 实时行情 - Free API, no API Key required ## 注意事项 / Notes ⚠️ 投资有风险，入市需谨慎 ⚠️ Investment involves risk, invest cautiously ⚠️ 历史收益不代表未来表现 ⚠️ Past performance does not guarantee future results ⚠️ 仅供参考，不构成投资建议 ⚠️ For reference only, not investment advice


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: suspicious | SkillSpector: clean (LOW)
Skill: codenova58/user-acquisition (version 0.1.0)

--- name: "新客拉新" description: "提供新客拉新的可落地指南与SOP。在开展新客拉新相关工作时调用。" --- # 新客拉新 (user-acquisition) ## 目标与场景 - 明确业务目标、核心指标与应用场景；设定落地时限与负责人。 ## 操作步骤 1. 明确范围与资源；2. 制定SOP；3. 数据接入与看板搭建； 4. 小流量试点；5. 复盘优化；6. 标准化沉淀与知识库更新。 ## 指标 - 主指标与守护指标成体系；定义口径并固定报表节奏。 ## 风险与合规 - 遵守中国本地法规与平台规则；个人信息保护与数据最小化。 ## 可复用清单 - 模板、脚本、Checklist、报表与会议纪要结构。 生成日期：2026-03-17


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)