OpenClaw/clawhub-security-signals huggingface dataset:
Skill: shan8851/parliament-cli (version 0.1.0)

--- name: parliament-cli description: UK Parliament CLI — search bills, divisions, members, and written questions from official UK Parliament APIs, with stable JSON envelopes for agents. Use when looking up UK Parliament bills, members, votes/divisions, written questions, or when an agent needs structured Parliament API results. homepage: https://www.parliment-cli.xyz metadata: { "openclaw": { "emoji": "🏛️", "requires": { "bins": ["parliament"] }, "install": [ { "id": "npm", "kind": "node", "package": "@shan8851/parliament-cli", "bins": ["parliament"], "label": "Install parliament-cli (npm)", }, ], }, } --- # parliament-cli Use `parliament` for UK Parliament data: bills, members, divisions/votes, and written questions. Setup - `npm install -g @shan8851/parliament-cli` - No API key or auth required Bills - By id: `parliament bill 3973` - By title: `parliament bill "renters rights"` - Search: `parliament search bills "energy"` Divisions and Votes - Search divisions: `parliament divisions "budget"` - Lookup by id: `parliament divisions 2211` - Alias: `parliament votes 2211` Members - By name: `parliament member "Keir Starmer"` - By id: `parliament member 4514` Written Questions - Search: `parliament questions "transport"` - Lookup by id or UIN query: `parliament questions 902178` Output - Defaults to text in a TTY and JSON when piped - Force JSON: `parliament bill 3973 --json` - Success envelope: `{ ok, schemaVersion, command, requestedAt, data }` - Error envelope: `{ ok, schemaVersion, command, requestedAt, error }` Agent Notes - Ambiguous text queries return `AMBIGUOUS_QUERY` with candidate hints in `error.details` - No auth setup needed, so agents can use it immediately - Exit codes are explicit and errors stay structured in JSON mode Notes - Official sources include the Bills, Members, Written Questions, and Commons Votes APIs - `votes` is an alias of `divisions`


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: hello-ahang/flyai-multi-airport-radar (version 1.0.1)

--- name: flyai-multi-airport-radar description: 同城不同价·多机场比价雷达。很多城市有多个机场，不同机场出发价格可能差几百甚至上千。AI自动扩展搜索半径，构建"出发地×日期"的价格矩阵，帮用户找到绝对最低价+综合交通成本的最优解。当用户提到"同城不同价"、"多机场比价"、"哪个机场便宜"、"换机场能省多少"、"周边机场"、"邻近机场"、"价格矩阵"、"找最便宜的出发地"时使用。 --- # 同城不同价·多机场比价雷达 你是一个**能够自主学习、持续成长**的智能机票比价专家。普通人只搜一个机场，你帮用户构建**出发地×日期**的价格矩阵，综合跨城交通成本，找到绝对最优解。 ## 核心定位 ### FlyAI 能力 > 完整命令参考见 reference 目录 **本技能主要使用**：`search-flight` **多维度省钱专家**： - 🔍 **空间扩展**：不只搜本地机场，自动扩展到周边城市机场 - 📅 **时间弹性**：多日期交叉比价，找到价格洼地 - 🧮 **综合计算**：机票 + 跨城高铁/打车成本，算出真实总价 - 💡 **一眼看清**：价格矩阵可视化，最低价高亮标注 - 🧬 **记忆成长**：记住用户常用出发城市和偏好，持续优化推荐 --- ## Memory 系统 作为一个能持续成长的智能助手，我会记住你的偏好和历史搜索。 **核心要点**： - **启动时读取**：除非用户说"忽略偏好/换个风格" - **有记录**：直接用已保存的常住城市、偏好机场开始对话 - **无记录**：首次用户，收集基本信息 - **实时更新**：用户提到新的出发区域、偏好时更新 Memory --- ## 工具说明 > 详见 [reference/tools.md](reference/tools.md) ## 用户画像读取（双模式） 启动时读取用户历史偏好，减少重复询问。 > 详见 [reference/user-profile-storage.md](reference/user-profile-storage.md) **优先**：`search_memory(query="用户旅行画像", category="user_hobby", keywords="flyai")` **降级**：`read_file(file_path="~/.flyai/user-profile.md")` --- ## 工作流程 > 详细步骤见 [reference/workflow.md](reference/workflow.md) **核心阶段：** 1. 收集用户信息 - 出发区域/目的地/日期弹性 2. 确定搜索范围 - 扩展周边机场/日期扫描 3. 执行矩阵搜索 - 批量调用 search-flight 4. 计算综合成本 - 机票+跨城交通+住宿 5. 生成价格矩阵 - 出发地×日期可视化 6. 输出推荐方案 - 含飞猪预订链接 ## 预订按钮说明 **重要**：每个方案必须包含可点击的预订入口： 1. **机票预订** - 从 `search-flight` 返回的 `jumpUrl` 字段提取 2. **酒店预订** - 调用 `search-hotel` 获取推荐酒店的 `jumpUrl` 3. **景点门票** - 调用 `search-poi` 获取景点的 `jumpUrl` **格式示例**： ```markdown 👉 [立即预订机票](https://a.feizhu.com/xxxxx) 👉 [查看酒店](https://a.feizhu.com/hotel/xxxxx) 👉 [查看景点门票](https://a.feizhu.com/poi/xxxxx) ``` 如果需要同时展示多个操作，使用按钮组： ```markdown ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 🎫 快速预订（点击跳转飞猪） | 类型 | 推荐 | 价格 | 操作 | |------|------|------|------| | ✈️ 机票 | {航班信息} | ¥{价格} | [预订]({jumpUrl}) | | 🏨 酒店 | {酒店名} | ¥{价格}/晚 | [预订]({jumpUrl}) | | 🎟️ 景点 | {景点名} | ¥{价格} | [购票]({jumpUrl}) | ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ ``` --- ## 异常处理 > 详见 [reference/error-handling.md](reference/error-handling.md) ## 自主学习机制 > 详见 [reference/self-learning.md](reference/self-learning.md) --- ## 示例对话 > 详见 [reference/examples.md](reference/examples.md) --- ## 进阶功能 > 详见 [reference/advanced.md](reference/advanced.md) ## 用户偏好保存（双模式） 发现新偏好时提示保存。详见 [reference/user-profile-storage.md](reference/user-profile-storage.md) **保存流程**：发现偏好 → 提示确认 → Qoder用update_memory / 非Qoder更新本地文件


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (CRITICAL)
Skill: 1970168137/biz-hospitality (version 1.0.0)

--- name: biz-hospitality version: 1.0.0 description: "Professional business hospitality including reception plans, seating arrangements, dining coordination, and etiquette guidance. Covers VIP visits, business dinners, corporate events, and relationship-building occasions with cultural sensitivity and protocol compliance." author: "openclaw" tags: - biz-hospitality - hospitality - reception - vip invocable: true --- ## Input | Name | Type | Required | Description | |------|------|----------|-------------| | guest_profile | text | Yes | Guest information and importance | | visit_purpose | text | Yes | Purpose of visit | | visit_duration | text | Yes | Length of visit | | host_representatives | text | Yes | Company representatives | | cultural_considerations | text | Yes | Cultural or dietary requirements | | budget_range | text | Yes | Hospitality budget | | previous_visits | text | No | History with this guest | ## Output | Name | Type | Description | |------|------|-------------| | reception_plan | text | Complete visit itinerary | | seating_arrangement | text | Meeting and dining seating plan | | dining_arrangements | text | Restaurant selection and menu | | etiquette_guide | text | Protocol and etiquette reminders | | gift_suggestions | text | Appropriate gift options | | talking_points | text | Suggested conversation topics | | follow_up_plan | text | Post-visit follow-up actions | ## Example ### Input ```json { "guest_profile": "CEO of major client company, strategic partner", "visit_purpose": "Partnership renewal discussion", "visit_duration": "Full day", "host_representatives": "Our CEO, VP Sales, Technical Director", "cultural_considerations": "Guest is Japanese, prefers formal settings", "budget_range": "$2,000 for day" } ``` ### Output ```json { "reception_plan": "9AM: Office arrival, tour | 10AM: Executive meeting | 12PM: Business lunch | 2PM: Technical demo | 4PM: Partnership discussion | 6PM: Dinner", "seating_arrangement": "Meeting: Host CEO center, guest CEO right, others by seniority | Dinner: Alternating host/guest", "dining_arrangements": "Lunch: Private room at business club | Dinner: High-end Japanese restaurant", "etiquette_guide": "Business card exchange with both hands, bow slightly, formal address, punctuality critical", "gift_suggestions": "Company-branded premium item, local specialty, quality pen set", "talking_points": "Partnership achievements, future opportunities, industry trends, personal interests", "follow_up_plan": "Thank you email within 24hrs, meeting summary, partnership proposal within week" } ```


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: roamer-remote/stocks-query-base-skill (version 0.2.2)

--- name: "A股-股市分析和投资顾问（安西军项目）" version: 0.2.2 description: > 中国 A 股/港股只读数据查询与分析技能。支持行情、基本面、指数、文本等数据内的检索，并且提供多种专业的分析方法和建议！ 支持自然语言需求映射到 stocks 接口，并输出结构化分析结果。 需 TAX_API_KEY 鉴权；仅用于公开历史数据查询，不支持交易下单，也不构成投资建议。 metadata: openclaw: requires: env: - TAX_API_KEY primaryEnv: TAX_API_KEY homepage: https://tax.yyyou.top/ --- ## 目标与边界 本 Skill 的目标是把用户自然语言问题转换为 /stocks/... 数据查询，并返回可复核的结构化分析结论。如需选股策略模板，可引导用户通过接口定义文档了解当前支持的财务指标与筛选字段。 ## 主要流程 1. 抓取数据 -> 技术分析/新闻检索 -> LLM 分析 -> 生成报告 -> 通知推送。 ## **必须遵守**： 1. 仅调用 /stocks/... 查询能力，不处理 /auth/*、/payment/* 等非股票查询路由。 2. 仅提供数据与分析，不给出交易代下单、收益承诺或“保证上涨”类结论。 3. 涉及投资建议时，始终加入风险提示与不构成投资建议声明。 4. 不回显、索取、存储或输出用户的 `TAX_API_KEY`以及任何个人隐私或者敏感信息。 ## 能力范围 | 类别 | 典型能力 | |------|----------| | 行情 | 日/周/月线、涨跌停、资金流向、复权因子、每日指标 | | 基本面 | 公司资料、三大报表、财务指标、分红、股东结构、质押回购 | | 指数 | 指数行情、成分股、权重、分类 | | 文本 | 利用llm的搜索功能。查询各类专业网站上的政策法规、研报元数据 | |讨论|利用llm的搜索功能去收集各大论坛，股吧等相关信息| ## 路由触发 当用户意图属于以下任一类时，触发本 Skill： - 股票代码、股票名称、上市公司（如"平安银行"、"600000"） - 行情、K线、涨跌、成交量、资金流向、股市分析 - 财报、财务指标、分红、ROE - 指数、成分股、权重、大盘 - 董秘问答、政策法规、研报元数据 以下情况不触发（或先澄清）： - 与股票数据无关的问题 - 要求代客交易、绕过风控或提供内幕信息 - 输入信息不足且无法定位标的（需先确认股票代码/名称/时间区间） ## 参数与鉴权规范 1. 请求头必须包含： ```http Header: TAX-[REDACTED_SECRET] ``` 2. 常用参数格式： | 参数 | 格式 | 说明 | |------|------|------| | ts_code | `600000` 或 `600000.SH` | 支持裸码与标准码 | | start_date | `YYYYMMDD` | 起始日期 | | end_date | `YYYYMMDD` | 结束日期 | 3. 代码规则提醒： - 裸码自动识别交易所（如 `600000` -> `.SH`） - 前导 0 不可省略（`000001` 不能写成 `1`） ## 主要流程 默认是以下1,2,3,4,5步以子代理的方式进行处理，除非用户明确只要单点数据： 1. **数据层** : 获取尽可能多的通过api获取具体的交易数据。 2. **行情层**：通过api来看趋势与波动（[REDACTED_SECRET]） 3. **基本面层**：验证质量与业绩（`fina-indicator/income/...`） 4. **环境层**：指数或文本交叉验证（`index-*`、`irm-qa-*`、`research-report`） 如果任一步数据不足，应明确写出“当前结论置信度受限”。 5. **新闻信息层** 通过网站搜索的能力 对相应的具体问询的股票进行新闻检索 。 6. 对上述数据并且**集成**接口返回的提示，用LLM进行分析 。 7. 生成报告。 8. 通知推送。 ## 常用接口速查 | 问题类型 | 推荐接口 | |----------|----------| | 个股走势 | `/stocks/daily` `/stocks/weekly` `/stocks/monthly` | | 估值与交易活跃度 | `/stocks/daily-basic` `/stocks/moneyflow` | | 财务质量 | `/stocks/fina-indicator` `/stocks/income` `/stocks/cashflow` | | 分红与股东结构 | `/stocks/dividend` `/stocks/top10-holders` | | 市场环境 | `/stocks/index-daily` `/stocks/index-member` `/stocks/index-weight` | | 公司互动信息 | `/stocks/irm-qa-sh` `/stocks/irm-qa-sz` | | 更多的数据接口 | 查看 skill_reference.md 文件| ## 输出格式规范 默认每次回复必须包含以下几段（仅当用户明确要求“简短回答”时可降级）： 1. **数据概览**：说明查询标的、时间范围、核心指标 2. **行情纵览**：分析相关股票所在的板块在最近几个交易日的行情简报。 3. **基本面**：查看股票的基本面情况。 4. **相关信息**：查看股票相关联的新闻，论坛等信息。 5. **市场情绪**：用llm来分析金融，股票市场的交易情绪。 6. **观察结论**：分点描述主要发现（行情/基本面/环境） 7. **一致性与风险**：说明数据是否互相印证，给出不确定性 8. **相关信息** : 通过收集网上的相关信息，来提供参考建议 9. **下一步建议查询**：给出 1-3 条可继续验证的接口或问题 若查询失败，按以下顺序返回可执行修复建议： 1. `401/403`：优先提示检查 `TAX_API_KEY` 是否已配置、是否过期或失效。 2. `400` 或参数类错误：提示检查 `ts_code` 与日期格式（`YYYYMMDD`）及起止区间。 3. `502/5xx`：说明上游服务临时异常，建议稍后重试，并给出可降级查询路径（如先查基础行情）。 ## 注意事项 - 只提供公开历史数据查询，不保证实时性 - 不支持交易下单或收益承诺 - 本 Skill 输出仅供研究参考，不构成投资建议


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (HIGH)
Skill: terrycarter1985/demo-archiver (version 0.1.0)

--- name: demo-archiver description: A demo skill for archiving and organizing files into a structured resource library. metadata: { "openclaw": { "emoji": "📦" } } --- # Demo Archiver Archive files into a structured directory with metadata tracking. ## Usage 1. Place source files in the skill's `incoming/` directory. 2. Run the archive script to move files into `archive/YYYY-MM/` with a metadata sidecar JSON. 3. Review the archive index at `archive/index.json`.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: deadlysilent/codex-usage (version 1.0.19)

--- name: codex-usage description: Manual Telegram slash-style command for Codex profile status and usage checks. Use when the user sends /codex_usage, /codex_usage default, /codex_usage all, or /codex_usage <profile>, or asks to check openai-codex profile usage/limits/auth health. --- > Deprecated wrapper: maintained implementation lives in `skills/codex-profiler/`. For `/codex_usage*` requests, follow `../codex-profiler/SKILL.md` and run: ```bash python3 skills/codex-profiler/scripts/codex_usage.py --profile all --format text ```


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: alti-systems/kling (version 1.0.0)

# Kling Video Generation Skill Generate AI videos using Kling 2.6 (via Kie.ai). ## Commands ```bash # Generate video and wait for result /root/clawd/skills/kling/kling.js generate "A gym owner high-fiving a member" # Quick start (returns task ID immediately) /root/clawd/skills/kling/kling.js quick "Professional fitness environment" # Check status /root/clawd/skills/kling/kling.js status <task_id> ``` ## Parameters - **Model**: kling-2.6/text-to-video (default) - **Aspect Ratio**: 16:9 (default) - **Duration**: 5 seconds (default) - **Negative Prompt**: Filters out blurry/low quality ## Use Cases - UGC-style marketing videos - Gym/fitness promotional content - LinkedIn video posts - Client testimonial visualizations - Product demos ## Notes - Videos take 1-5 minutes to generate - Results include video URL in the response - API key stored in `.env` as `KIE_API_KEY`


Security scan verdicts — ClawScan: clean | static analysis: suspicious | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: allinherog-star/douyin-realtime-hot-rise (version 1.0.1)

--- name: douyin-realtime-hot-rise description: "抖音上升热点选题助手适合内容创作者、运营、电商、营销在用户想知道接下来拍什么、写什么更可能有流量时使用，帮助基于输入材料生成上升热点列表、排名和变化趋势视图、可用于内容规划的选题线索。" requiredEnvVars: - name: AISKILLS_API_KEY description: "从 AI Skills 官网 https://ai-skills.ai 获取的 API Key，用于运行导出的技能调用。" --- # douyin-realtime-hot-rise 抖音上升热点选题助手 [快速开始](https://github.com/allinherog-star/ai-skills/tree/main#%E5%BF%AB%E9%80%9F%E5%BC%80%E5%A7%8B) [更多技能](https://ai-skills.ai) ### 概述 抖音上升热点选题助手用于回答「拍什么会有流量」、找上升选题、看赛道是否升温、辅助内容策划会，适合内容创作者、运营、电商、营销在明确业务目标、内容材料或分析对象后调用。 它会结合搜索词、搜索特定关键词的热点等输入，整理关键上下文，并输出上升热点列表、排名和变化趋势视图、可用于内容规划的选题线索，便于继续执行、复盘或交付。 ### 什么时候使用 **适用场景** - 用户想知道接下来拍什么、写什么更可能有流量 - 用户想找正在上升的抖音热点或赛道机会 - 用户需要增长导向的选题参考 ### 调用方式 通过导出的 Python runner 直接调用 AI Skills API： ### 命令示例 **按关键词追热点** ```bash python3 scripts/run.py --params '{"keyword":"奥运","order":"rank_diff"}' ``` **按分类看热点** ```bash python3 scripts/run.py --params '{"tag":"5000","order":"rank"}' ``` ### 参数说明 | 参数 | 类型 | 必填 | 默认 | 说明 | | --- | --- | --- | --- | --- | | `tag` | string | 否 | - | 筛选特定分类的热点（从分类接口获取） | | `order` | string | 否 | `rank` | 选择热点排序方式；可选值：热度排序（`rank`）、变化排序（`rank_diff`） | | `keyword` | string | 否 | - | 搜索特定关键词的热点 | 完整机器可读参数结构见 `references/form-schema.json`。 ### 参数取值参考 当前技能没有需要额外查表的分类参数。 ### 支持的输入格式 当前技能直接接收 JSON 参数，不涉及分享链接解析。 ### 示例请求 下面的示例参数可直接传给 `scripts/run.py`，runner 会把它们发送给 AI Skills API。 ```bash python3 scripts/run.py --params '{"keyword":"奥运","order":"rank_diff"}' ``` 等价的 `--params` JSON： ```json { "keyword": "奥运", "order": "rank_diff" } ``` ### 返回结果示例 ```json { "success": true, "data": { "title": "抖音实时上升热点榜", "updateTime": "2026-04-24T11:30:00.000Z", "pagination": { "page": 1, "pageSize": 30, "total": 100 }, "items": [ { "rank": 1, "rankDiff": 12, "keyword": "奥运开幕式", "id": 1234567890, "hotScore": 9876543, "videoCount": 1860, "tagId": 5000, "tagName": "体育", "trends": [ { "time": "10:00", "score": 6320000 }, { "time": "11:00", "score": 9876543 } ], "createdAt": "2026-04-24T11:20:00.000Z" } ] }, "meta": { "executionTime": 842, "cached": false } } ``` ### 交付内容 - 上升热点清单：给出关键词、分类、排名变化和热度趋势。 - 趋势判断依据：帮助判断热点是刚开始升温、持续走高还是已经接近峰值。 - 选题参考：可直接用于短视频脚本、内容会选题和赛道观察。 ### 结果使用建议 - 优先关注排名变化明显、仍在上升、且与账号赛道匹配的关键词。 - 结合分类和趋势变化判断跟进窗口，尽量把热点转成具体脚本角度。 - 适合内容会、选题池更新和临时热点响应。 ### 运行前准备 - `AISKILLS_BASE_URL`：默认 `https://ai-skills.ai` - `AISKILLS_API_KEY`：必填，用于认证调用 - `AISKILLS_TENANT_ID`：默认 `default`


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (HIGH)
Skill: zaixi/workspace-org (version 2.1.0)

--- name: workspace-org description: "Standardized workspace directory layout for multi-agent OpenClaw deployments. All agent-generated files go under files/ to keep root clean. Defines where agents store files, exchange deliverables, and cleanup policies. Trigger on workspace setup, file placement decisions, workspace cleanup, multi-agent convention setup, workspace compliance check." --- # Workspace Org Standardized directory conventions for OpenClaw multi-agent workspaces. ## Layout ``` workspace/ ← or any agent workspace dir ├── AGENTS.md, SOUL.md ... ← core config (never moved) ├── skills/ ← ClawHub skills ├── memory/ ← long-term memory ├── files/ ← all agent-generated content │ ├── tmp/ disposable temp files │ ├── notes/ working docs worth keeping │ ├── inbox/ deliverables from other agents │ ├── outbox/ files for owner/other agents │ ├── archive/ inactive projects │ └── experts/ (workspace root only) expert engagements ``` ## Rules - **Core config** files stay at workspace root. Never moved. - **All generated files** go into `files/{subdir}/`. No exceptions. - **Cross-agent handoff**: sender writes to `files/outbox/`, receiver picks from `files/inbox/`. ### Cleanup policy | Subdir | Cleanup rule | |--------|-------------| | `files/tmp/` | Eligible for auto-cleanup at any time | | `files/notes/` | Keep; never auto-clean | | `files/archive/` | Manual review before removal | | `files/experts/` | Remove after expert engagement ends | | `files/inbox/` | Clear after processing deliverable | ## Enforcement for future work ### When creating files All generated files go into `files/` subdirectories: - **Temp/one-off** scripts, patches, downloads → `files/tmp/` - **Keep-worthy** docs, analysis, snapshots → `files/notes/` - **Cross-agent handoff** → `files/inbox/` or `files/outbox/` - **Old projects** → `files/archive/` ### Periodic compliance check ```bash # Check if current workspace has layout violations python3 {{SKILL_DIR}}/scripts/sweep.py # JSON output for automation python3 {{SKILL_DIR}}/scripts/sweep.py --json ``` ### Fix existing violations ```bash python3 {{SKILL_DIR}}/scripts/apply.py --execute ``` HEARTBEAT.md can include a periodic sweep to catch drift. ## Scripts ### `scripts/apply.py` Creates `files/` and sub-directories, migrates existing files into correct locations. Auto-detects workspace root vs agent workspace. Dry-run by default. Agent directories (containing AGENTS.md) are never moved. ### `scripts/sweep.py` Audits workspace for layout violations. Returns exit code 0 (clean), 1 (warnings), or 2 (violations). ## References - [layout.md](references/layout.md) — Full specification with agent-type variations


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: huajianjiu000/customer-response-generator (version 1.0.0)

--- name: Customer Response Generator description: Generate professional, empathetic customer service responses in seconds. Handle complaints, questions, refunds, and reviews with consistent quality. metadata: openclaw: dependencies: [] --- # Customer Response Generator ## What This Skill Does Customer service doesn't have to be repetitive. I generate professional responses to common customer inquiries, complaints, and feedback so you can reply faster without sacrificing quality. ## Features - **Tone Consistency**: Professional, empathetic, and brand-aligned - **Quick Turnaround**: Reduce response time significantly - **Situation-Specific**: Different templates for complaints, questions, refunds, praise - **De-escalation Built-In**: Responses designed to calm frustrated customers - **Multi-Channel Ready**: Email, chat, social media, or review platforms ## How to Use 1. **Paste Customer Message**: What did the customer say? 2. **Choose Response Type**: Complaint, question, refund request, review, etc. 3. **Add Context**: Order details, policy, or any relevant information 4. **Get Your Response**: Receive a ready-to-send reply ## Response Types - **Order Inquiries**: Where's my order? Shipping questions - **Product Issues**: Defects, wrong items, quality concerns - **Refund Requests**: Processing returns and refunds - **Shipping Problems**: Delays, lost packages, address issues - **General Questions**: Product info, policies, availability - **Positive Reviews**: Thank you responses - **Negative Reviews**: Professional, solution-focused replies ## What Makes These Responses Work - **Empathy First**: Acknowledge feelings before solving problems - **Clear Solutions**: Specific next steps, not vague promises - **Professional Tone**: Polite but not robotic - **Brand Voice**: Consistent with your company's personality - **Action-Oriented**: What you're doing to help ## Best For - E-commerce store owners - Customer service teams - Small business owners handling their own support - Community managers - Anyone dealing with customer communications ## Tips for Best Results - Include relevant order/product information - Mention any policies that apply - Tell me if you have flexibility on solutions (discounts, free shipping, etc.) - Let me know your brand's tone (formal, casual, friendly) --- *Great customer service builds loyalty. Let me help you respond faster and better!*


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: rhlsthrm/telegram-history (version 1.1.0)

--- name: telegram-history description: Fetch Telegram chat message history via MTProto user API (Telethon). Use when needing to read old messages from any Telegram chat, group, or forum topic that the bot API can't access. Supports fetching by chat ID, forum topic/thread, message count, pagination, and JSON output. Requires one-time user login with phone number + 2FA. --- # Telegram History Fetch message history from any Telegram chat using MTProto (Telethon). The Bot API cannot read chat history — this skill uses the user API instead. ## Setup ### 1. Install Telethon ```bash pip3 install telethon ``` ### 2. Get API credentials Go to https://my.telegram.org/apps and create an app. Save credentials in the skill directory: ```bash cat > <skill-dir>/api_credentials.json << 'EOF' {"api_id": YOUR_API_ID, "api_hash": "YOUR_API_HASH"} EOF ``` ### 3. Login (one-time) All paths below are relative to the skill directory. ```bash # Step 1: Request a login code (sent to your Telegram app) python3 scripts/login.py send +1234567890 # Output: Code sent! phone_code_hash: abc123 # Output: Run: python3 login.py verify +1234567890 <code> abc123 # Step 2: Verify with the code you received # IMPORTANT: Do NOT send the code via Telegram — Telegram detects shared codes and blocks login. # Use a file, another messenger, or run the command directly in terminal. python3 scripts/login.py verify +1234567890 <CODE> <PHONE_CODE_HASH> # If 2FA is enabled, append your [REDACTED_SECRET] scripts/login.py verify +1234567890 <CODE> <PHONE_CODE_HASH> <2FA_PASSWORD> # Check login status: python3 scripts/login.py check +1234567890 ``` Session persists in `session/` — no need to re-login after initial setup. ## Usage ```bash # Fetch last 50 messages from a chat python3 scripts/tg_history.py history <chat_id> --limit 50 # Fetch from a forum topic python3 scripts/tg_history.py history <chat_id> --topic <topic_id> --limit 30 # JSON output python3 scripts/tg_history.py history <chat_id> --json # Paginate (messages before a specific ID) python3 scripts/tg_history.py history <chat_id> --offset-id <msg_id> --limit 50 ``` ## Notes - Group chat IDs use `-100` prefix (e.g., `-1001234567890`) - Forum topic IDs = the thread/topic message ID - Sender names are resolved automatically - All paths (session, credentials) are resolved relative to the skill directory — works regardless of install location


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