OpenClaw/clawhub-security-signals huggingface dataset:
Skill: dzy-1026/xfyun-song-rec (version 1.0.0)

--- name: song-recognition description: Recognize songs by singing or audio file using iFlytek's Query By ACRCloud technology. homepage: https://www.xfyun.cn/doc/voiceservice/music_recognition/API.html metadata: { "openclaw": { "emoji": "🎵", "requires": { "bins": ["python3"], "env": ["XF_SONG_APP_ID", "XF_SONG_API_KEY", "XF_SONG_API_SECRET"] }, "primaryEnv": "XF_SONG_APP_ID" } } --- # 🎵 Song Recognition Recognize songs by singing, or audio file using iFlytek's advanced Query By ACRCloud technology. Designed for music identification, song discovery, and audio recognition scenarios. --- ## ✨ Features - Singing recognition - Audio file recognition - High-accuracy song matching - Real-time synchronous detection - Multiple audio format support - URL and file path input support --- ## 🚀 Usage **Using audio file path:** ```bash python {baseDir}/scripts/index.py "<audio_path>" ``` Examples: ``` python {baseDir}/scripts/index.py "humming.wav" ``` ## 📋 Input Specification ### Audio Requirements - Supported formats: MP3 - Sample rate: 16000Hz - Audio encoding: lame - Duration: 5-30 seconds recommended - singing melody --- ## ⚠ Constraints - Audio must contain clear melody - API credentials must be configured - Network connection required - Synchronous processing - instant results - Audio quality affects recognition accuracy --- ## 🔧 Environment Setup Required: - Python available in PATH - Environment variables configured: ```bash export XF_SONG_APP_ID=your_app_id export XF_SONG_API_KEY=your_api_key export XF_SONG_API_SECRET=your_api_secret ``` Or configure it in `~/.openclaw/openclaw.json`: ```json { "env": { "XF_SONG_APP_ID": "your_app_id", "XF_SONG_API_KEY": "your_api_key", "XF_SONG_API_SECRET": "your_api_secret" } } ``` --- ## 📦 Output Returns JSON response with: - Song name - Artist name - Album information - Confidence score - Match details --- ## 🎯 Target Use Cases - Music identification apps - Song discovery platforms - Karaoke applications - Music education tools - Audio content recognition - Copyright detection - Music search engines --- ## 🛠 Extensibility Future enhancements may include: - Batch audio processing - Real-time streaming recognition - Custom music library - Multi-language song support - Genre classification --- Built for automation workflows and AI-driven music recognition.


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

--- name: json-tool description: Validate, format, and transform JSON data. Use when user needs to pretty print JSON, validate JSON syntax, minify JSON, extract JSON paths, or convert JSON to other formats. --- # JSON Tool Validate, format, and transform JSON data. ## Quick Start ```bash # Format JSON python scripts/json_tool.py data.json --format # Validate JSON python scripts/json_tool.py data.json --validate ``` ## Usage ```bash python scripts/json_tool.py [FILE] [OPTIONS] Options: --format Pretty print JSON --minify Minify JSON --validate Validate JSON syntax --query PATH JSONPath query --convert FORMAT Convert to: yaml, csv, xml --sort-keys Sort object keys --indent NUM Indentation size ``` ## Examples ```bash # Pretty print python scripts/json_tool.py data.json --format # Minify python scripts/json_tool.py data.json --minify # Extract field python scripts/json_tool.py data.json --query "items[0].name" # Convert to YAML python scripts/json_tool.py data.json --convert yaml # Sort keys python scripts/json_tool.py data.json --sort-keys ``` ## Features - Pretty printing - Minification - Validation - JSONPath queries - Format conversion (YAML, CSV, XML) - Key sorting


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: hilaraklesantosw-art/get-my-ip (version 0.1.0)

--- name: get-my-ip description: Get the machine's current public IP address by calling `curl ifconfig.me`. Use when the user asks for their IP address, public IP, external IP, or explicitly wants to use ifconfig.me. version: 1.0.0 metadata: openclaw: requires: bins: - curl homepage: https://github.com/hilaraklesantosw-art/skills --- # Get My IP Use this skill when the user wants the current machine's IP address as seen from the public internet. This skill uses: ```bash curl -fsSL ifconfig.me ``` ## Outcome Return the current public IP address from `ifconfig.me`. Keep the answer concise. By default, return only the IP unless the user asks for more detail. ## Workflow ### 1. Clarify the meaning only when needed `ifconfig.me` returns the public outbound IP, not the local LAN IP. If the user says "local IP" but also asks to use `ifconfig.me`, follow the request and, when useful, note that the result is the public IP. ### 2. Run the command Use: ```bash curl -fsSL ifconfig.me ``` Do not replace it with another service unless the user asks for a fallback. ### 3. Return the result If successful: - return the IP directly If it fails: - say the public IP could not be retrieved - include the brief reason when available, such as missing `curl`, network failure, or service unavailability ## Scope Boundaries This skill is only for retrieving the public IP via `ifconfig.me`. It is not for: - finding the local LAN IP - diagnosing network routing issues - checking multiple interfaces - performing geolocation lookups


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: lixiabupt/skill-analyst (version 1.1.0)

--- name: skill-analyst description: > Analyze and evaluate OpenClaw skills before installing or publishing. Compare against existing or ClawHub skills, check feature overlap, perform security review, and provide clear install/publish recommendations. Requires `clawhub` CLI to be available. Triggers: "analyze skill-name", "evaluate installing/publishing skill", "is this skill worth installing", "can I publish this", "skill comparison". --- # Skill Analyst Help you analyze, compare, and vet skills before installing or publishing. ## Prerequisites - `clawhub` CLI required - `skill-vetter` optional (for security review) ## Workflow: Install Evaluation ### Step 1: Search the Target Search ClawHub for similar skills: ```bash clawhub search "<skill-name>" clawhub inspect "<best-match>" ``` Get: name, author, version, summary, license, last updated. ### Step 2: Check Installed Skills Scan `~/.openclaw/skills/` for SKILL.md files, or use `clawhub list`. ### Step 3: Find Overlap Compare target against installed skills: - Search by functionality keywords or use case - Rate overlap: HIGH / MEDIUM / LOW / NONE - Note key differences ### Step 4: Security Check (optional) If `skill-vetter` is installed, run security review. Otherwise mark "security check skipped". ### Step 5: Generate Report ```markdown ## 🔍 Analysis Report: Install <skill-name> ### Overview | Field | Value | |-------|-------| | Name | ... | | Author | ... | | Version | ... | | License | ... | | Last Updated | ... | ### Overlap with Installed Skills - skill-a: MEDIUM — Similar use case, different approach - skill-b: NONE — Unrelated ### Unique Value - Feature X (no installed skill covers this) ### Risks - Requires Z API key ### Verdict ✅ Recommended / ⚠️ Consider / ❌ Not recommended ``` ## Workflow: Publish Evaluation ### Step 1: Read Local Skill Read SKILL.md from workspace or skills directory. Extract name, description, features, file list. ### Step 2: Search Competitors Use 2-3 different keywords: ```bash clawhub search "<skill-name>" clawhub search "<keywords from description>" ``` ### Step 3: Analyze Competitors For each relevant result: ```bash clawhub inspect "<competitor>" ``` Compare: feature coverage, maturity, update frequency, uniqueness. ### Step 4: Generate Report ```markdown ## 🔍 Analysis Report: Publish <skill-name> ### Your Skill | Field | Value | |-------|-------| | Name | ... | | Files | ... | | Description | ... | ### ClawHub Competitors | Skill | Author | Version | Overlap | Updated | |-------|--------|---------|---------|---------| | ... | ... | ... | HIGH/MED/LOW | ... | ### Your Advantages - Key differentiators ### Suggestions - Consider adding X before publishing ### Verdict ✅ Ready to publish / ⚠️ Optimize first / ❌ Reconsider ``` ## Output Rules - Always use tables for structured comparison - Keep analysis concise and actionable - End with a clear verdict - Follow the report templates above


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: ivangdavila/urdu (version 1.0.0)

--- name: Urdu description: Write Urdu that sounds human. Not formal, not robotic, not AI-generated. --- ## The Real Problem AI Urdu is technically correct but sounds off. Too formal. Too ادبی (literary). Natives write more casually, with warmth and natural flow. Match that. ## Formality Default Default register is too high. Casual Urdu is warm and expressive. Unless explicitly formal: lean casual. ## تم vs آپ vs تو Three levels: - آپ: formal, elders, respect - تم: standard casual, peers - تو: very intimate, close friends - Online mostly uses تم or آپ depending on context ## Urdu vs Hindi Similar spoken, different written: - Urdu: Nastaliq script (اردو) - More Persian/Arabic vocabulary - Different cultural expressions - Don't mix scripts ## Particles & Softeners These make Urdu natural: - نا: question tag, softening ("ٹھیک ہے نا؟") - تو: emphasis ("یہ تو بہت اچھا ہے") - ہی: emphasis ("یہی چاہیے") - بھی: "also", "even" ## Fillers & Flow Real Urdu has fillers: - یعنی، اچھا، تو - ویسے، اصل میں - سنو، دیکھو - کیا بتائیں ## Expressiveness Don't pick the safe word: - اچھا → بہترین، زبردست، کمال - برا → بیکار، بکواس، گھٹیا - بہت → انتہائی، کافی ## Common Expressions Natural expressions: - ٹھیک ہے، اوکے، ہاں جی - کوئی بات نہیں، کوئی مسئلہ نہیں - سچی?، واقعی?، کیا بات ہے! - واہ!، کیا خوب! ## Reactions React naturally: - سچی?، واقعی?، کیا? - واہ!، اللہ!، تو‌بہ! - زبردست!، کمال!، بہت خوب! - ہاہاہا in text ## Romanized Urdu Common online: - Roman script often used in texting - "Kya haal hai", "Theek hai" - Natural in casual digital contexts ## The "Native Test" Before sending: would an Urdu speaker screenshot this as "AI-generated"? If yes—too formal, too ادبی. Add casual warmth.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: cp3d1455926-svg/email-helper (version 1.0.0)

# 📧 Email Helper - 邮件助手 ## 触发规则 **关键词：** - 写邮件、邮件草稿、回复邮件 - 邮件模板、邮件格式 - 邮件分类、整理邮件 **场景：** - 用户需要写邮件但不知道如何开头 - 用户需要回复工作邮件 - 用户需要整理收件箱 ## 功能描述 ### 核心功能 1. **邮件草稿生成** - 根据目的生成邮件 - 正式/非正式语气 - 中英文支持 2. **邮件回复建议** - 自动回复草稿 - 语气调整 - 快捷回复 3. **邮件模板** - 求职信 - 请假申请 - 商务合作 - 感谢信 4. **邮件分类** - 工作/个人分类 - 优先级标记 - 归档建议 ## 权限需求 - [x] 文件读写（模板存储） - [ ] 外部 API（邮件客户端集成） ## 示例对话 ``` 用户：帮我写一封请假邮件 助手：好的！帮你起草请假邮件： --- **主题：** 请假申请 - [你的名字] - [日期] 尊敬的 [领导姓名]： 您好！ 因 [请假原因]，我需要在 [开始日期] 至 [结束日期] 期间请假 [天数] 天。 请假期间的工作已安排如下： 1. [工作交接安排 1] 2. [工作交接安排 2] 如有紧急情况，可通过 [联系方式] 联系我。 恳请批准，谢谢！ 此致 敬礼 [你的名字] [日期] --- 需要我调整语气或内容吗？ 用户：写一封商务合作邮件 助手：好的！商务合作邮件草稿： --- **主题：** 商务合作洽谈 - [公司名] 尊敬的 [对方姓名/团队]： 您好！ 我是 [公司名] 的 [职位][你的名字]。我们专注于 [业务领域]... 希望能与贵方探讨合作机会... 期待您的回复！ 祝好， [你的名字] --- ``` ## 数据存储 ```json // ~/.openclaw/workspace/email-helper/templates.json { "templates": [ { "name": "请假申请", "category": "工作", "content": "..." } ] } ``` ## 待办事项 - [ ] 邮件模板库 - [ ] 语气调整 - [ ] 自动回复 - [ ] 邮件客户端集成 --- **版本：** 1.0.0 **创建日期：** 2026-03-16 **作者：** 小鬼 👻


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (HIGH)
Skill: 275254cl-hash/1688-price-monitor (version 1.0.1)

--- name: 1688-price-monitor version: 1.0.0 description: 监控 1688 批发商品价格，支持一件代发价格查询、厂家信息、同款比价。适合电商卖家、代购、副业创业者。 homepage: https://github.com/openclaw/skills metadata: { "openclaw": { "emoji": "🏭", "requires": { "bins": ["python3", "curl"] }, "install": [ { "id": "requests", "kind": "pip", "package": "requests", "label": "安装依赖：pip3 install requests", }, ], }, } --- # 1688 价格监控技能 监控 1688 批发商品价格，找货源、比价格、查厂家。 ## 功能 1. **价格查询**: 实时获取批发价格 2. **厂家信息**: 查看供应商资质 3. **一件代发**: 支持代发价格查询 4. **同款比价**: 相似商品比价 5. **起订量**: 查看 MOQ 信息 ## 使用方式 **查询商品价格**: ``` 查询 1688 价格 https://detail.1688.com/offer/123456789.html ``` **找货源**: ``` 帮我找手机壳的 1688 货源，要求一件代发 ``` **查厂家**: ``` 查一下这个厂家的资质 https://shop123.1688.com ``` **比价**: ``` 找同款商品的最低批发价 ``` ## 输出示例 ``` 🏭 1688 商品信息 商品：iPhone 15 手机壳 ├─ 批发价：¥3.50 - ¥5.80 ├─ 一件代发：¥6.80 ├─ 起订量：2 件 └─ 运费：¥5.00 🏢 厂家信息： ├─ 公司：深圳市 XXX 电子厂 ├─ 年限：5 年 ├─ 评分：4.8/5.0 └─ 回头率：35% 💰 利润测算（淘宝售价¥19.9）： ├─ 成本：¥6.80 + ¥5.00 = ¥11.80 └─ 毛利：¥19.9 - ¥11.80 = ¥8.10 (40.7%) ``` ## 变现模式 - 免费：每日 20 次查询 - 付费 (¥49/月)：无限查询 + 货源推荐 - 付费 (¥99/月)：+ 利润测算 + 厂家分析 ## 优势 相比淘宝监控： - ✅ 1688 反爬较低 - ✅ 数据更公开 - ✅ 适合 B 端用户 - ✅ 利润空间更大 --- **声明**: 数据仅供参考，交易前请核实。


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: sarielwang93/memory-tiering (version 1.0.0)

--- name: memory-tiering description: Automated multi-tiered memory management (HOT, WARM, COLD). Use this skill to organize, prune, and archive context during memory operations or compactions. --- # Memory Tiering Skill 🧠⚖️ This skill implements a dynamic, three-tiered memory architecture to optimize context usage and retrieval efficiency. ## The Three Tiers 1. **🔥 HOT (memory/hot/HOT_MEMORY.md)**: * **Focus**: Current session context, active tasks, temporary credentials, immediate goals. * **Management**: Updated frequently. Pruned aggressively once tasks are completed. 2. **🌡️ WARM (memory/warm/WARM_MEMORY.md)**: * **Focus**: User preferences (Hui's style, timezone), core system inventory, stable configurations, recurring interests. * **Management**: Updated when preferences change or new stable tools are added. 3. **❄️ COLD (MEMORY.md)**: * **Focus**: Long-term archive, historical decisions, project milestones, distilled lessons. * **Management**: Updated during archival phases. Detail is replaced by summaries. ## Workflow: `Organize-Memory` Whenever a memory reorganization is triggered (manual or post-compaction), follow these steps: ### Step 1: Ingest & Audit - Read all three tiers and recent daily logs (`memory/YYYY-MM-DD.md`). - Identify "Dead Context" (completed tasks, resolved bugs). ### Step 2: Tier Redistribution - **Move to HOT**: Anything requiring immediate attention in the next 2-3 turns. - **Move to WARM**: New facts about the user or system that are permanent. - **Move to COLD**: Completed high-level project summaries. ### Step 3: Pruning & Summarization - Remove granular details from COLD. - Ensure credentials in HOT point to their root files rather than storing raw secrets (if possible). ### Step 4: Verification - Ensure no critical information was lost during the move. - Verify that `HOT` is now small enough for efficient context use. ## Usage Trigger - Trigger manually with: "Run memory tiering" or "整理记忆层级". - Trigger automatically after any `/compact` command.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: morrison230/cron-local (version 1.0.0)

--- name: cron description: Local-first recurring schedule engine for reminders, repeated tasks, and time-based execution plans. Use whenever the user mentions recurring timing, repetition, schedules, cadence, weekly/daily/monthly routines, future triggers, or wants to know what runs next. Captures natural language timing into structured local schedules, supports pause/resume, and surfaces upcoming executions. No external sync. --- # Cron Turn recurring intentions into structured local schedules. ## Core Philosophy 1. Repetition should be captured once, then trusted. 2. A schedule is not just a reminder — it is an execution contract over time. 3. The system should make recurrence visible, editable, and pausable. 4. Users should always know what runs next. ## Runtime Requirements - Python 3 must be available as `python3` - No external packages required ## Storage All data is stored locally only under: - `~/.openclaw/workspace/memory/cron/jobs.json` - `~/.openclaw/workspace/memory/cron/runs.json` - `~/.openclaw/workspace/memory/cron/stats.json` No external sync. No cloud storage. No third-party cron service. ## Job Status - `active`: schedule is live - `paused`: temporarily disabled - `archived`: no longer active, kept for history ## Schedule Types - `daily` - `weekly` - `monthly` - `interval` ## Key Workflows - **Capture recurring job**: `add_job.py` - **See what runs next**: `next_run.py` - **Pause or resume**: `pause_job.py`, `resume_job.py` - **Inspect one job**: `show_job.py` - **Review all jobs**: `list_jobs.py`


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: paoloxiamn/acmilan-match-monitor (version 1.2.1)

--- name: acmilan-match-monitor description: Check if AC Milan played yesterday and send the result. Uses ESPN public API — no token, no region restrictions. Works with curl directly. Silent if no match. Perfect for daily 8:30 AM cron push. --- # AC Milan Match Monitor Check yesterday's AC Milan match result using ESPN's public API. ## Why ESPN API? - ✅ No API key required - ✅ No region restrictions (works anywhere) - ✅ Direct curl, no browser needed - ❌ Don't use web_search (region-blocked) - ❌ Don't use acmilan.com (React SPA, curl gets empty shell) - ❌ Don't use sofascore API (returns 403) ## Setup Place `scripts/check_match.py` in your skill folder. No dependencies beyond Python 3 stdlib. ## Usage Run the script via `nodes.run` or locally: ```bash python3 scripts/check_match.py ``` **Output (if match yesterday):** ``` ⚽ AC Milan ✅ Win Score: AC Milan 3 - 2 Torino Competition: Serie A ``` **Output (if no match):** silent, no output. ## Cron Integration ```json { "payload": { "kind": "agentTurn", "message": "Run the AC Milan match check script via nodes.run:\n[\"/usr/bin/python3\", \"/path/to/skills/acmilan-match-monitor/scripts/check_match.py\"]\n\nIf output exists, forward it to the user.\nIf no output, end silently.", "model": "dashscope/qwen-plus", "timeoutSeconds": 60 }, "schedule": { "kind": "cron", "expr": "30 8 * * *", "tz": "Asia/Shanghai" } } ``` ## Key Info - AC Milan ESPN ID: **103** - League code: **ita.1** (Serie A) - API endpoint: `https://site.api.espn.com/apis/site/v2/sports/soccer/ita.1/teams/103/schedule?limit=5`


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (HIGH)
Skill: blammectrappora/neon-art-generator (version 1.0.0)

--- name: neon-art-generator description: AI neon art generator that transforms any subject into stunning neon-lit artwork. Create glowing neon portraits, cyberpunk neon scenes, neon sign aesthetics, and vibrant electric art. Perfect for profile pictures, wallpapers, social media content, and digital art with neon glow, neon lights, and neon aesthetic styles via the Neta AI image generation API (free trial at neta.art/open). tools: Bash --- # Neon Art Generator AI neon art generator that transforms any subject into stunning neon-lit artwork. Create glowing neon portraits, cyberpunk neon scenes, neon sign aesthetics, and vibrant electric art. Perfect for profile pictures, wallpapers, social media content, and digital art with neon glow, neon lights, and neon aesthetic styles. ## Token Requires a Neta API token (free trial at <https://www.neta.art/open/>). Pass it via the `--token` flag. ```bash node <script> "your prompt" --token YOUR_TOKEN ``` ## When to use Use when someone asks to generate or create neon art generator images. ## Quick start ```bash node neonartgenerator.js "your description here" --token YOUR_TOKEN ``` ## Options - `--size` — `portrait`, `landscape`, `square`, `tall` (default: `portrait`) - `--ref` — reference image UUID for style inheritance ## Install ```bash npx skills add blammectrappora/neon-art-generator ```


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (HIGH)
Skill: 0x-professor/docs-pipeline-automation (version 0.1.0)

--- name: docs-pipeline-automation description: Build repeatable data-to-Docs pipelines from Sheets and Drive sources. Use for automated status reports, template-based document assembly, and scheduled publishing workflows. --- # Docs Pipeline Automation ## Overview Create deterministic pipelines that transform Workspace data sources into generated Docs outputs. ## Workflow 1. Define pipeline name, sources, template, and destination. 2. Normalize source extraction and section mapping steps. 3. Build report assembly sequence and publish target. 4. Export implementation-ready pipeline artifact. ## Use Bundled Resources - Run `scripts/compose_docs_pipeline.py` for deterministic pipeline output. - Read `references/docs-pipeline-guide.md` for document assembly guidance. ## Guardrails - Keep source mapping explicit and versioned. - Include fallback behavior for missing sections.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: suspicious | SkillSpector: suspicious (MEDIUM)
Skill: anyunzhong/clawec-shopee-product-search (version 1.0.3)

--- name: shopee-product-search description: 通过 Clawec API 搜索 Shopee 商品，返回价格、销量、评分、市场、链接与图片等。在用户需要 Shopee 搜品、东南亚跨境选品、竞品调研、关键词找货、虾皮商品搜索时使用。 --- # Shopee 商品搜索 ## 关于 ClawEC ClawEC 是一款面向跨境电商场景的 AI 智能体协同平台，以「你的跨境电商 AI 团队」为品牌主张，将选品、调研、运营、上架、营销、客服、采购、合规等环节沉淀为可执行的 SOP（标准作业程序），通过多智能体（「虾员工」）分工协作与 7×24 小时自动化任务，帮助卖家在单人或少人条件下完成跨境业务闭环，降低对专业运营团队与复杂本地部署的依赖。 本技能调用 ClawEC 开放 API，用于 Shopee 商品搜索与东南亚市场选品调研。 ## 认证与基址 - **Base URL**: `https://www.clawec.com/api` - **API Key**: 在 https://www.clawec.com/?source=q-clawhub 注册帐号 然后去https://www.clawec.com/api-key?source=q-clawhub 获取key - **请求头**: - `Content-Type: application/json` - `Authorization: Bearer <API_KEY>` 优先从环境变量 `CLAWEC_API_KEY` 读取密钥；未设置时向用户索取，勿硬编码。 ## 接口 `POST /aigc/ec/shopee_search` | 参数 | 位置 | 必填 | 说明 | |------|------|------|------| | keyword | body | 是 | 搜索关键词 | | region | body | 否 | 地区，支持：SG, MY, TH, ID, PH, VN, BR, MX, CL, CO, PL, TW（示例：PH） | ## 调用 ```bash curl -s -X POST "https://www.clawec.com/api/aigc/ec/shopee_search" \ -H "Content-Type: application/json" \ -H "Authorization: Bearer $CLAWEC_API_KEY" \ -d '{"keyword":"蓝牙耳机","region":"PH"}' ``` 或使用脚本： ```bash bash scripts/search.sh "蓝牙耳机" PH ``` ## 响应结构 ```json { "status": 1, "data": [ ... ], "pointInfo": { "type": 0, "point": 0 } } ``` - `status`: `1` = 成功，`0` = 失败 - `data`: 商品数组，失败或空结果时按实际返回处理 - `pointInfo`: 积分/扣点信息 `{ type, point }` ### 商品字段 | 字段 | 说明 | |------|------| | id | 商品 ID | | name | 名称 | | price | 价格 | | cover | 封面图 URL | | rating | 排名 | | sales | 销量 | | star | 评分 | | images | 图片 URL 数组 | | url | 商品链接 | | market | 市场/站点 | 完整字段说明见 [references/response-schema.md](references/response-schema.md)。 ## 工作流程 1. 确认搜索关键词；需要指定站点时传入 `region`（如 PH、SG、MY） 2. 检查 `CLAWEC_API_KEY` 是否可用 3. 执行 API 请求 4. `status !== 1` 或请求失败时，说明错误并提示检查密钥与参数 5. 解析 `data`，按用户需求整理输出 ## 输出建议 默认中文摘要，包含： - 命中数量 - 商品对比表：名称、价格、销量、评分、排名、市场、链接 - 选品调研场景：可按价格/销量/评分排序，并按 `market` 分组观察 ## 示例 **输入**：搜索「蓝牙耳机」 **输出摘要**： | 名称 | 价格 | 销量 | 评分 | 排名 | 市场 | 链接 | |------|------|------|------|------|------|------| | ... | ... | ... | ... | ... | ... | ... |


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