OpenClaw/clawhub-security-signals huggingface dataset:
Skill: xyzach/book-digest (version 1.0.0)

--- name: book-digest description: "深度阅读一本书：查书摘、拆章节、苏格拉底式提问检验理解、概念映射到实际应用。适用于非虚构/商业/技术类书籍。" version: 1.1.0 author: Hermes Agent (user request) tags: [reading, learning, socratic, comprehension, books] --- # Book Digest（深度阅读） 帮助用户快速读懂一本书。通过搜索、拆解、提问、对话四种方式，从被动阅读变成主动学习。 ## 触发条件 用户提到以下任一场景时加载此技能： - "帮我读一本书" / "帮我理解XX这本书" - "检验我对XX的理解" - "拆解XX的核心观点" - "用苏格拉底方式问我关于XX的问题" - 用户提供了一段文本并希望深度分析 ## 模式选择 加载技能后，先向用户确认书的信息和想要的模式： ### 模式 1：快速概览 (Quick Overview) 一次性给出：作者背景、核心论点、章节脉络、关键概念、这本书在领域中的位置、争议点。 ### 模式 2：深度拆解 (Deep Dive) 按章节或主题逐步拆解：每轮聚焦一个章节/主题 → 提炼关键论证 → 问用户理解 → 继续下一部分。 ### 模式 3：苏格拉底提问 (Socratic) 角色扮演：你读完了书（或提供了文本），我来提问检验你的理解。 - **每次只问一个问题**，等用户回答后再给下一个。不要一次抛多个问题。 - 从浅到深：事实性问题 → 推理性问题 → 批判性问题 → 应用性问题 - 不直接给答案，而是通过追问引导用户自己发现 - 如果用户答不上来，给提示而不是直接揭晓 - 降级策略（用户连续说「不知道」时）： 1. 第一次「不知道」→ 给一个方向性提示（不涉及答案本身） 2. 第二次「不知道」→ 给更直接的提示，缩小范围 3. 第三次「不知道」→ 直接给答案并简要解释，然后进入下一个问题。不要卡在同一个问题上反复追问。 - 根据用户回答调整下一题难度。答得好 → 加难度；答不上 → 回撤到更基础的问题 ### 模式 4：应用映射 (Application) 把书中的框架/概念映射到用户的实际场景： - 先确认用户的工作领域或当前面临的挑战 - 逐个概念讨论"这对你意味着什么" - 帮用户制定行动计划 ## 工作流程 ### 第一步：确认书的信息 - 书名、作者 - 用户是否已经读过部分内容？读了多少？ - 用户的目标是什么？（考试、兴趣、工作需要、写作参考等） - 偏好什么模式？如果不确定，默认用「快速概览」开个头 ### 第二步：搜集信息 尝试通过 browser_navigate 或 execute_code（curl）搜索以下内容： - 书的官方摘要和目录 - 作者背景和写作动机 - 核心概念/框架名称 - 主要批评或争议 - 优质书评/读书笔记（豆瓣、Goodreads、博客等） 搜索策略：用多个并行搜索覆盖不同维度。中文书搜中文关键词，英文书搜英文。 ``` "《书名》 核心观点 摘要" "《书名》 目录 章节" "书名 作者 书评 解读" "book title key ideas summary" ``` **Pitfall:** `web_search` 不是 shell 命令，不能用 terminal 直接调用。使用 browser_navigate 访问搜索引擎或 execute_code 跑 curl。如果搜索受阻（CAPTCHA、连接失败等），不要死磕——对于知名度较高的书，直接使用自身知识库即可，不需要等搜索结果才继续。告知用户「基于已有知识直接开始」即可。 ### 第三步：呈现 + 交互 根据选择模式进入对应流程。呈现时遵循以下原则： 1. **不灌水** — 直接给干货，不要「这本书非常精彩，值得一读」之类的废话 2. **标注来源** — 关键数据和引用标注来自哪里 3. **追问** — 每个关键概念呈现后至少问一个确认理解的问题。但如果用户说「继续」「请继续」「下一步」，表示用户要加速，跳过追问直接推进内容 4. **适应节奏** — 用户说「继续」→ 加速；用户追问细节 → 深挖。深度拆解模式中，如果用户连续两次「继续」，后续章节可以不再插入提问 5. **中文优先** — 用户用中文交流，用中文回应。英文书名保留原名，概念首次出现括号附英文 ## 示例对话 ### 苏格拉底模式示例 用户：「我用苏格拉底模式，检验我对《思考，快与慢》的理解」 助手： > 好，假设我是你的读书伙伴。先热身一下： > > 卡尼曼把人类的思维分成哪两个系统？用你自己的话描述它们各自的特点。 > > （等用户回答后，根据回答质量决定下一题难度。） ### 应用模式示例 用户：「我是产品经理，帮我用《创新者的窘境》的框架看看我现在的处境」 助手： > 先确认一下：你现在所在的市场是 > A) 成熟大厂，主营产品利润率很高 > B) 创业公司，在找颠覆性切入点 > C) 其他（说说看） > > （确认后开始映射书中的延续性创新 vs 颠覆性创新框架） ## 收束规则 完成深度阅读（四种模式全部或部分走完）后，**主动提议**为这本书创建一个独立的决策参考技能。格式参见 `thinking-fast-and-slow` 技能： - 技能名用英文书名转换（如 `thinking-fast-and-slow`） - 内容为概念清单 + 决策含义 - 每个概念三要素：名称、一句话解释、对该者的决策启示 - 存入 `research/` 分类 - 创建后提醒用户：以后做决策时可以加载此技能辅助判断 ## 注意事项 - 如果用户只给了书名但网上搜不到足够信息（过于冷门/新书/非英文），诚实地告诉用户并建议用户提供文本摘录或目录 - 如果用户说读的是小说/文学作品，提醒用户此技能主要针对非虚构类，但可以调整（关注主题、人物弧线、叙事结构等） - 【关键】苏格拉底模式一次只问一个问题，不要一次抛多个问题 - 【关键】如果用户回答"不知道"，给最多 1-2 次提示，然后直接给答案。不要反复追问——用户偏好讲解式输入多于发现式学习 - 【关键】不要用评价性语言评判用户的回答质量。只问不评。不要说"你概念掌握还行，但..."这类话 - 在结构化内容（拆解章节）时，用户说"继续"就是直接推进，不要每段都问"要继续吗" - 苏格拉底模式中，如果用户问了一个和当前问题无关的澄清问题，简洁回答后立即回到原问题 - 全模式串联时默认顺序为 1→2→3→4，模式 2 结束后自然询问是否进入模式 3 - 用户随时可以说「跳过」「换模式」「我不确定」来调整节奏


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: leninws/letundra (version 1.0.2)

--- name: letundra description: "Универсальный AI-скилл для путешествий — визы, новости, RSS, праздники, валюты с letundra.com. Используй when: пользователь спрашивает о визах, новостях, праздниках, курсах валют. NOT for: бронирование, отели." homepage: https://letundra.com metadata: { "openclaw": { "emoji": "🌍", "requires": { "bins": ["node"] }, "tags": ["travel", "visa", "news", "holidays", "currency", "aviation", "airlines"] } } --- # 🌍 Letundra — всё о путешествиях Универсальный AI-скилл для получения информации с **letundra.com** — визы, новости, праздники, курсы валют. ## Что умеет скилл | Функция | Описание | |---------|----------| | 🛂 Виза | Визовые требования, безвизовый режим, документы | | 📰 Новости | Авиация, акции, визовые изменения | | 📡 RSS | Генерация RSS-ленты по тегам/странам | | 🎉 Праздники | Государственные праздники и фестивали | | 💱 Валюты | Курсы валют и конвертация | ## When to Use Активируйте когда пользователь спрашивает о: - Визах / "нужна ли виза в Таиланд?" - Новостях / "что нового в авиации?" - Праздниках / "какие праздники в Индии?" - Валютах / "курс бата к рублю" - RSS / "создай RSS для Emirates" ## Как это работает ### Используй web_fetch Все данные получаются через встроенный `web_fetch`: ``` {{web_fetch url="https://letundra.com/ru/countries/{slug}/"}} {{web_fetch url="https://letundra.com/ru/news/"}} ``` ### URLs для разных типов данных | Тип | URL | |-----|-----| | Виза, страна | `https://letundra.com/ru/countries/{slug}/` | | Новости | `https://letundra.com/ru/news/` | | Новости по тегу | `https://letundra.com/ru/news/?taglist={tag}` | ### Примеры slug стран - Таиланд → thailand - Индия → india - ОАЭ → uae - Турция → turkey - Египет → egypt ## Output Formats ### Новости ```markdown # 📰 Новости ## 1. Заголовок 📅 Дата 🏷️ Теги [Описание] 🔗 [Читать далее](link) ``` ### Виза ```markdown # 🛂 Виза в [Страна] **Нужна ли виза:** [Да/Нет] **Безвизовый срок:** [дней] **Типы виз:** - По прибытию: [условия] - e-Visa: [условия] **Документы:** - [список] ``` ## Examples | Запрос | Метод | |--------|-------| | "Новости авиации" | web_fetch → /ru/news/ | | "Виза в ОАЭ" | web_fetch → /ru/countries/uae/ | | "Праздники в Тае" | web_fetch → /ru/countries/thailand/ | | "Курс бата" | web_fetch → /ru/countries/thailand/ | ## Структура проекта ``` letundra-skills/ ├── SKILL.md # Этот файл ├── letundra-visa/ # Скилл для виз ├── letundra-news/ # Скилл для новостей ├── letundra-rss/ # Скилл для RSS ├── letundra-holidays/ # Скилл для праздников ├── letundra-currency/ # Скилл для валют ├── scripts/ │ └── letundra_yandex.js # Локальный парсер (опционально) ├── package.json └── README.md ``` --- *Данные: Letundra.com — ваш помощник в мире путешествий*


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: zengfei88/teslamateskills (version 0.1.1)

--- name: teslamate-grafana description: Query TeslaMate vehicle data via Grafana API. Use when user wants Tesla vehicle status, battery info, drives, charges, statistics, driving score, battery health, or trip data. Requires Grafana running with TeslaMate PostgreSQL datasource. --- # TeslaMate Grafana API Skill Query TeslaMate data through Grafana's `/api/ds/query` endpoint using the PostgreSQL datasource. ## Configuration Grafana address is stored in `~/.openclaw/workspace/memory/teslamate-grafana-config.json`: ```json { "grafana_url": "http://192.168.31.218:3000", "datasource_id": 1 } ``` To update address: ```bash echo '{"grafana_url": "http://YOUR-GRAFANA:3000", "datasource_id": 1}' > ~/.openclaw/workspace/memory/teslamate-grafana-config.json ``` ## Usage ### Quick Status ```bash python3 scripts/query_teslamate.py --status # Output: Battery: 85% | Range: 420 km | State: online | Today: 45 km ``` ### Drives ```bash python3 scripts/query_teslamate.py --drives 5 # Recent 5 drives with address lookup ``` ### Route Planning ```bash python3 scripts/query_teslamate.py --route "广州珠江新城" # Output: Distance, duration, energy needed, arrival range ``` ## Commands | Command | Description | |---------|-------------| | `--status` | Quick status: battery, range, state, today distance | | `--drives [N]` | Recent N drives with address lookup | | `--route <addr>` | Plan route to destination | | `--report` | Weekly report | | `--monthly` | Monthly statistics | | `--trend` | Energy efficiency trend (30 days) | | `--score` | Driving score based on speed | | `--milestones` | Achievement milestones | | `--charging` | Charging statistics (30 days) | | `--efficiency` | Energy efficiency stats | | `--cost` | Charging cost (default 1.5 CNY/kWh) | | `--range` | Range prediction | | `--health` | Battery health estimation | | `--places` | Top 10 most visited places | | `--drain` | Vampire drain analysis | | `--states` | Vehicle state statistics | | `--alerts` | Check for anomalies | | `--temp` | Temperature monitoring | | `--location` | Current car location | | `--full` | Complete status dashboard | ## Common Metrics - **Battery**: `battery_level` (0-100%), `ideal_battery_range_km` - **Drive**: `distance` (km), `duration_min` (minutes), `speed_max`, `power_max` - **Charge**: `charge_energy_added` (kWh), `charger_power` (kW), `charger_voltage` (V) - **States**: `state` = 'online'|'offline'|'driving'|'charging'|'asleep'|'updating' ## API Details - Endpoint: `{grafana_url}/api/ds/query` - Method: POST - Content-Type: application/json - Datasource: PostgreSQL (TeslaMate) Request body: ```json { "queries": [{ "refId": "A", "datasourceId": 1, "rawSql": "YOUR SQL QUERY", "format": "table" }] } ``` Response contains results in `results.A.data.values`.


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (CRITICAL)
Skill: daniellummis/github-actions-stuck-run-audit (version 1.0.0)

--- name: github-actions-stuck-run-audit description: Detect stale queued/in-progress GitHub Actions runs before they quietly block delivery. version: 1.0.0 metadata: {"openclaw":{"requires":{"bins":["bash","python3"]}}} --- # GitHub Actions Stuck Run Audit Use this skill to catch workflows that are stuck in queued/in-progress states for too long. ## What this skill does - Reads GitHub Actions run JSON exports - Detects stale runs in non-terminal statuses (`queued`, `in_progress`, etc.) - Aggregates stuck risk by repo/workflow (or repo/branch) - Scores severity with stuck-age, stuck-run volume, and stuck-rate thresholds - Emits `ok` / `warn` / `critical` and can fail CI gates ## Inputs Optional: - `RUN_GLOB` (default: `artifacts/github-actions/*.json`) - `TOP_N` (default: `20`) - `OUTPUT_FORMAT` (`text` or `json`, default: `text`) - `GROUP_BY` (`repo`, `repo-workflow`, `repo-workflow-branch`; default: `repo-workflow`) - `NOW_ISO` (optional ISO timestamp override for deterministic replay) - `STUCK_STATUSES` (comma list, default: `queued,in_progress,pending,waiting,requested`) - `WARN_STUCK_MINUTES` (default: `45`) - `CRITICAL_STUCK_MINUTES` (default: `120`) - `WARN_STUCK_RUNS` (default: `2`) - `CRITICAL_STUCK_RUNS` (default: `4`) - `WARN_STUCK_RATE` (0..1, default: `0.2`) - `CRITICAL_STUCK_RATE` (0..1, default: `0.45`) - `MIN_RUNS` (default: `1`) - `WORKFLOW_MATCH` / `WORKFLOW_EXCLUDE` (regex, optional) - `BRANCH_MATCH` / `BRANCH_EXCLUDE` (regex, optional) - `EVENT_MATCH` / `EVENT_EXCLUDE` (regex, optional) - `REPO_MATCH` / `REPO_EXCLUDE` (regex, optional) - `STATUS_MATCH` / `STATUS_EXCLUDE` (regex, optional) - `FAIL_ON_CRITICAL` (`0` or `1`, default: `0`) ## Collect run JSON ```bash gh run view <run-id> \ --json databaseId,workflowName,event,headBranch,status,conclusion,createdAt,runStartedAt,updatedAt,url,repository \ > artifacts/github-actions/run-<run-id>.json ``` ## Run Text report: ```bash RUN_GLOB='artifacts/github-actions/*.json' \ bash skills/github-actions-stuck-run-audit/scripts/stuck-run-audit.sh ``` JSON output + fail gate: ```bash RUN_GLOB='artifacts/github-actions/*.json' \ OUTPUT_FORMAT=json \ FAIL_ON_CRITICAL=1 \ bash skills/github-actions-stuck-run-audit/scripts/stuck-run-audit.sh ``` Run against bundled fixtures: ```bash NOW_ISO='2026-03-08T00:00:00Z' \ RUN_GLOB='skills/github-actions-stuck-run-audit/fixtures/*.json' \ bash skills/github-actions-stuck-run-audit/scripts/stuck-run-audit.sh ``` ## Output contract - Exit `0` in report mode (default) - Exit `1` when `FAIL_ON_CRITICAL=1` and one or more groups are critical - Text mode prints summary + ranked stuck-risk groups - JSON mode prints summary + ranked groups + critical groups


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: javainthinking/apipick-china-phone-checker (version 1.0.1)

--- name: apipick-china-phone description: Validate Chinese mobile phone numbers using the apipick China Phone Checker API. Returns carrier (China Mobile/Telecom/Unicom), province, city, zip code, and area code. Use when the user wants to verify a Chinese phone number, look up carrier information for a Chinese mobile number, or get geographic information associated with a Chinese phone number. Requires an apipick API key (x-api-key). Get a free key at https://www.apipick.com. metadata: openclaw: requires: env: - APIPICK_API_KEY primaryEnv: APIPICK_API_KEY --- # apipick China Phone Checker Validate Chinese mobile numbers and retrieve carrier and geographic data. ## Endpoint ``` POST https://www.apipick.com/api/check-china-phone ``` **Authentication:** `x-[REDACTED_SECRET]` header required. Get a free API key at https://www.apipick.com/dashboard/api-keys ## Request ```json {"phone_number": "13800138000"} ``` Supported formats: `13800138000` / `+8613800138000` / `008613800138000` ## Response ```json { "success": true, "data": { "phone": "13800138000", "phone_type": "China Mobile", "province": "Beijing", "city": "Beijing", "zip_code": "100000", "area_code": "010" } } ``` `phone_type` values: `China Mobile`, `China Telecom`, `China Unicom` ## Error Codes | Code | Meaning | |------|---------| | 400 | Invalid phone number format | | 401 | Missing or invalid API key | | 402 | Insufficient credits | | 500 | Server error | **Cost:** 1 credit per request ## Usage Pattern 1. Use `$APIPICK_API_KEY` env var as the `x-api-key` header value; if not set, ask the user for their apipick API key 2. Make the POST request with the phone number 3. Present carrier and geographic results clearly See [references/api_reference.md](references/api_reference.md) for full response field descriptions.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: xlbbb-cn/sshexec (version 1.0.1)

--- name: ssh-exec description: A skill to execute SSH commands on remote servers, supporting both password and key-based authentication. It includes error handling and logging for command execution results. --- # SSH Command Executor This skill allows you to execute SSH commands on remote servers securely. It supports both password and key-based authentication methods, making it versatile for various use cases. ## Features - **Authentication**: Supports both password and key-based authentication. - **Command Execution**: Execute any command on the remote server and retrieve the output. - **Error Handling**: Provides detailed error messages for failed command executions. - **Logging**: Logs all executed commands and their results for auditing purposes. ## Prerequisites - **SSH Client**: Ensure you have an SSH client installed on your local machine. - **Remote Server Access**: You must have access to the remote server with the necessary credentials. - **Python Environment**: This skill is implemented in Python, so ensure you have Python installed on your local machine. ## Usage To execute a command on a remote server using password authentication: ```bash python3 skills/sshexec/ssh_exec.py --host "remote-server.com" --user "username" --password "password" --command "ls -la" ``` To execute a command using key-based authentication: ```bash python3 skills/sshexec/ssh_exec.py --host "remote-server.com" --user "username" --key "path/to/private/key" --command "ls -la" ``` ## Error Handling The skill will provide detailed error messages if the command execution fails, such as authentication errors, connection issues, or command errors. All errors will be logged for further analysis. ## Future Expansion - Support for executing multiple commands in a single session. - Integration with task schedulers for automated command execution. - Enhanced logging with timestamps and command output storage.


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (HIGH)
Skill: wangshengli0421/tianshu-image (version 1.0.0)

--- name: tianshu-image description: > 使用阿里云通义万相 (DashScope) 生成图片。Use when: 用户需要根据文字描述生成图片；用户说「画一张」「生成图片」「文生图」。 NOT for: 图片编辑、风格迁移、其他非文生图场景。 metadata: openclaw: primaryEnv: DASHSCOPE_API_KEY requires: env: - DASHSCOPE_API_KEY --- # 天树文生图 (tianshu-image) 使用阿里云通义万相 API 根据文字描述生成图片，Node.js 实现，无需 Python/uv。 ## When to Run - 用户说「画一张」「生成图片」「文生图」「根据这段描述生成图」 - 用户提供图片描述，需要 AI 生成对应图片 ## 前置配置 在 `~/.openclaw/openclaw.json` 的 `skills.entries.tianshu-image` 中配置，或设置环境变量： - `DASHSCOPE_API_KEY` - 阿里云 DashScope API Key（从 https://dashscope.console.aliyun.com/ 获取） - 或 `models.providers.bailian.apiKey`（若已配置百炼） ## Workflow 1. 确认用户需要生成图片 2. 执行脚本： ``` node ~/.openclaw/skills/tianshu-image/scripts/generate_image.js --prompt "描述" [--size 1664*928] ``` 3. 脚本输出 `MEDIA_URL: <url>` 或 `MEDIA: <本地路径>` 4. 用 Markdown 展示图片：`![生成的图片](URL)` ## 参数 - `--prompt` / `-p`：图片描述（必填） - `--size` / `-s`：尺寸，默认 `1664*928`。可选：`1024*1024`、`720*1280`、`1280*720` - `--model` / `-m`：模型，默认 `qwen-image-max`。可选：`qwen-image-turbo`、`qwen-image-plus-2026-01-09` - `--filename` / `-f`：保存到本地文件路径（可选） - `--negative-prompt`：负向提示词 - `--no-prompt-extend`：禁用自动提示词增强 - `--watermark`：添加水印 ## Output - 未指定 `--filename` 时输出 `MEDIA_URL: <url>`，直接展示 URL - 指定 `--filename` 时输出 `MEDIA: <本地路径>`，表示已保存到本地

path: package.json
content: {
  "name": "tianshu-image-skill",
  "private": true,
  "dependencies": {}
}


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: zhanglingai/evomap-auto-maintainer (version 1.0.1)

--- name: evomap-auto-maintainer description: 自动维护 EvoMap 节点在线状态，自动赚取积分。一键设置，永久生效。 version: 1.0.0 author: zhanglingAI price: $19.99 tags: [automation, evomap, node-management, heartbeat, passive-income] --- # EvoMap Auto Maintainer 保持你的 EvoMap 节点 24/7 在线，自动赚取积分。 ## 解决的问题 - EvoMap 节点经常离线？ - 不想手动发送心跳？ - 节点掉线后不知道怎么恢复？ 这个技能帮你全自动解决！ ## 功能 - ✅ **自动检测** - 每分钟检查节点状态 - ✅ **自动心跳** - 每15分钟发送保活信号 - ✅ **智能恢复** - 离线时自动重新注册获取密钥 - ✅ **日志记录** - 详细记录每次操作 ## 安装 ```bash clawhub install evomap-auto-maintainer ``` ## 配置 设置环境变量： ```bash export EVOMAP_NODE_ID="node_your_node_id" export EVOMAP_SECRET="your_node_secret" ``` ## 使用 ### 1. 检查节点状态 ```bash bash maintainer.sh status ``` 输出示例： ``` [2026-03-08 22:50:20] 检查节点状态... [2026-03-08 22:50:20] 节点ID: node_openclaw_xxx [2026-03-08 22:50:22] ✅ 节点在线 ``` ### 2. 设置自动维护（推荐） ```bash bash maintainer.sh setup ``` 这将自动： - 添加 cron 任务，每15分钟自动心跳 - 无需人工干预，永久生效 ### 3. 手动发送心跳 ```bash bash maintainer.sh heartbeat ``` ## 价格 **$19.99** - 一次性购买，永久使用，免费更新 ## 收益计算 - 保持节点在线 = 赚取 EvoMap 积分 - 积分可兑换收益 - 投资回报：通常 1-2 个月回本 ## 支持 如有问题请联系：[REDACTED_SECRET]


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: bwtomekk-bit/analytics-agent (version 1.0.0)

<objective> Tracking und Analyse aller unserer Projekte: Trading Performance, App Metrics, Freelance Leads, Marketing ROI. Erstellt Reports, identifiziert Trends, empfiehlt Optimierungen. </objective> <principles> ## Analytics-Fokus ### Metriken - Trading: PnL, Win-Rate, Bias-Performance - App: Downloads, User, Revenue - Freelance: Leads, Conversions, Revenue - Marketing: Views, Engagement, Cost ### Reports - Täglich: Trading Summary - Wöchentlich: Full Overview - Monatlich: Strategy Review ### Tools - Dashboard (192.168.178.80:6969) - Logs analysieren - Excel/Sheets Export </principles> <process> <step> <action>Trading Analytics</action> <details> - Paper vs Live PnL - Win-Rate pro Asset - Bias Performance check - Pattern WR tracken </details> </step> <step> <action>App Analytics</action> <details> - Base44 Stats abfragen - User onboarded? - Payments? - Errors? </details> </step> <step> <action>Freelance Tracking</email> <details> - Email-Response Rate - Angebote gesendet vs gewonnen - Revenue </details> </step> <step> <action>Report erstellen</action> <details> - Daten aggregieren - Trends identifizieren - Empfehlungen schreiben - An Thomas senden </details> </step> </process> <triggers> - Täglich (Trading Summary) - Wöchentlich (Full Report) - Nach Major Events </triggers> <success_criteria> - Alle Metrics im Blick - Trends früh erkennen - Bessere Decisions durch Data </success_criteria>


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: strongant/consul-deregister (version 1.0.4)

--- name: consul-deregister description: Consul service deregistration tool. Triggered when users mention Consul deregister, remove service instance, service removal, or offline. Supports batch deregister by service ID across multiple Consul agents, parse and replay raw curl commands, dry-run preview, parallel execution, and ACL token auth. --- # Consul Service Deregister Deregister service instances from Consul via the HTTP API. ## Usage ### Mode 1: Service ID + Agent List (Most Common) ``` User: Deregister service my-service-id on consul-agent-1, consul-agent-2, and consul-agent-3 ``` AI executes: ```bash python3 /Users/shiheng/.qclaw/workspace/skills/consul-deregister/scripts/deregister.py \ --service-id my-service-id \ --agents http://<CONSUL_HOST_1>:8500 http://<CONSUL_HOST_2>:8500 http://<CONSUL_HOST_3>:8500 ``` ### Mode 2: Paste Raw curl Commands (Easiest) User pastes existing curl commands, AI parses and replays them: ``` User: Execute these deregister commands: curl -XPUT http://<CONSUL_HOST_1>:8500/v1/agent/service/deregister/<SERVICE_ID> curl -XPUT http://<CONSUL_HOST_2>:8500/v1/agent/service/deregister/<SERVICE_ID> ``` AI executes: ```bash python3 /Users/shiheng/.qclaw/workspace/skills/consul-deregister/scripts/deregister.py \ --from-curl "curl -XPUT http://<CONSUL_HOST>:8500/v1/agent/service/deregister/<SERVICE_ID> ..." ``` ### Mode 3: Read Agent List from File ```bash python3 /Users/shiheng/.qclaw/workspace/skills/consul-deregister/scripts/deregister.py \ --service-id my-service-id \ --agents-file ./agents.txt ``` `agents.txt` format (supports `#` comments): ``` # Consul Agent node list <CONSUL_HOST_1>:8500 <CONSUL_HOST_2>:8500 <CONSUL_HOST_3>:8500 ``` ### Dry-Run Preview Add `--dry-run` to any mode to preview the requests without actually sending them: ```bash python3 /Users/shiheng/.qclaw/workspace/skills/consul-deregister/scripts/deregister.py \ --service-id my-service-id \ --agents http://<CONSUL_HOST_1>:8500 http://<CONSUL_HOST_2>:8500 \ --dry-run ``` ### With ACL Token ```bash python3 /Users/shiheng/.qclaw/workspace/skills/consul-deregister/scripts/deregister.py \ --service-id my-service-id \ --agents http://<CONSUL_HOST>:8500 \ --token your-consul-acl-token ``` ## Common Workflows **Scenario 1: Batch Deregister Gray Nodes** User provides a service ID and multiple IP:port pairs. **Scenario 2: Release Rollback** User triggers rollback; AI finds the old version's service ID from config/docs and deregisters. **Scenario 3: Service Migration** Moving a service from old cluster to new cluster — deregister from all old cluster nodes first. ## Notes - `service-id` must exactly match the ID registered in Consul (no extra spaces) - Agent addresses accept both `host:port` and full URL (`http://host:port`) — auto-completed - Parallel requests by default (up to 10 concurrent), automatic speedup for many nodes - Non-zero exit code on any failure; AI will surface failure details - Use `--json` for JSON output suitable for scripting / pipeline integration


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