OpenClaw/clawhub-security-signals huggingface dataset:
Skill: sky-lv/skylv-code-quality-reviewer (version 1.0.0)

--- name: "Code Reviewer" slug: skylv-code-reviewer version: 1.0.2 description: Code review assistant. Analyzes code quality, detects bugs and security issues, and suggests improvements. Triggers: code review, security audit, code quality, bug detection. author: SKY-lv license: MIT-0 tags: [openclaw, agent, code] keywords: code-review, linting, security, quality triggers: code reviewer --- # CodeReview Agent Skill > AI-powered code review and quality analysis agent ## 功能 - **代码质量分析** - 检测代码异味、复杂度问题 - **安全漏洞扫描** - SQL注入、XSS、敏感信息泄露 - **性能优化建议** - 识别性能瓶颈 - **最佳实践检查** - 符合语言规范和设计模式 - **自动修复建议** - 提供可执行的修复代码 ## 使用场景 ``` 用户: 帮我审查这段Python代码的安全性 Agent: [调用code-reviewer skill分析代码，输出安全问题列表和修复建议] ``` ## 工具函数 ### `review_code(code, language, focus_areas)` 审查代码并返回分析报告。 **参数:** - `code` (str): 要审查的代码 - `language` (str): 编程语言 (python/javascript/go/rust/java等) - `focus_areas` (list): 关注点 ['security', 'performance', 'style', 'complexity'] **返回:** ```python { "issues": [ { "type": "security", "severity": "high", "line": 42, "message": "Potential SQL injection vulnerability", "suggestion": "Use parameterized queries" } ], "score": 75, "summary": "代码整体可读性良好，但存在安全风险" } ``` ### `analyze_complexity(code, language)` 分析代码复杂度（圈复杂度、认知复杂度）。 ### `detect_patterns(code, language)` 检测代码中使用的设计模式。 ## 配置 ```json { "rules": { "max_complexity": 10, "max_line_length": 120, "require_docstring": true, "security_checks": ["injection", "xss", "secrets"] } } ``` ## 示例 ```python # 审查Python代码 result = review_code(''' def get_user(id): query = f"SELECT * FROM users WHERE id = {id}" return db.execute(query) ''', 'python', ['security']) # 输出: # [HIGH] SQL Injection: Use parameterized queries # Line 3: query = f"SELECT * FROM users WHERE id = {id}" # Suggestion: query = "SELECT * FROM users WHERE id = ?" ``` ## 安装 ```bash clawhub install SKY-lv/code-reviewer ``` ## License MIT ## Usage 1. Install the skill 2. Configure as needed 3. Run with OpenClaw

path: skill.json
content: {
  "name": "code-reviewer",
  "version": "1.0.0",
  "description": "AI Code Review Agent - Security, performance, and quality analysis",
  "author": "SKY-lv",
  "license": "MIT",
  "keywords": ["code-review", "security", "ai-agent", "openclaw"],
  "repository": "https://github.com/SKY-lv/code-reviewer",
  "main": "SKILL.md"
}


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: xk103295870-alt/seedance-prompt-wizard (version 1.0.4)

--- name: seedance-prompt-wizard description: > Seedance 2.0 提示词生成向导。通过引导式对话， 逐步收敛用户需求，生成精准的 Seedance 2.0 Prompt。 不做任何 API 调用，不涉及认证。 触发词：帮我写提示词、生成视频提示词、Seedance提示词、视频生成提示词，制作提示词 --- # Seedance 2.0 · Prompt Wizard > 版本：1.0.1 > 定位：纯提示词生成，不做 API 调用 --- ## 一句话 通过引导式对话，将用户的模糊想法逐步收敛为精准的 Seedance 2.0 Prompt，直接可用。 --- ## 模型选择 | 用户描述 | 判断模型 | |---------|---------| | 只有文字描述 | Text-to-Video | | 有1-2张参考图 | Image-to-Video | | 有图+视频/音频混用 | Reference-to-Video | --- ## 参数规格（仅供 Prompt 参考） | 参数 | 默认值 | 可选值 | |------|--------|--------| | `duration` | 5秒 | 4-15秒 | | `quality` | 720p | 480p / 720p | | `aspect_ratio` | 16:9 | 16:9 / 9:16 / 1:1 / 4:3 / 3:4 / 21:9 | | `generate_audio` | true | 含音效/配乐 | --- ## 对话流程（5步） ### Step 1：判断模型类型 根据用户描述判断： - 纯文字 → Text-to-Video - 1-2张图 → Image-to-Video - 图+视频/音频 → Reference-to-Video ### Step 2：收集核心信息（每次最多2个问题） ``` ① 视频内容是什么？（主体：人物/产品/场景/动物） ② 场景/背景是什么？ ③ 有没有参考素材？（图/视频/音频） ④ 想要的风格或氛围？ ``` ### Step 3：确认输出参数 ``` ⑤ 时长？（默认5秒，最长15秒） ⑥ 比例？（默认16:9，短视频用9:16） ⑦ 需要音效吗？（默认含音效） ``` ### Step 4：生成 Prompt **Prompt 结构：** ``` [主体] + [场景/背景] + [动作/状态] + [镜头/运动] + [风格/光线/色调] ``` **@素材名 规则：** ``` @image1 = 第1张参考图（主体外观/场景/产品） @image2 = 第2张参考图（备选） @video1 = 第1个参考视频（镜头运动/动作） @video2 = 第2个参考视频（辅助镜头） @audio1 = 第1个参考音频（背景音乐/音效） ``` ### Step 5：输出 --- ## 追问话术 **关于素材：** ``` "有参考图/视频/音频吗？上传效果会好很多" "图片几张？1张（首帧动画）还是2张（首尾过渡）？" ``` **关于风格：** ``` "想要什么氛围？比如：温馨/科技感/电影感/国潮" "色调偏亮还是暗？暖色还是冷色？" ``` **关于镜头：** ``` "想要什么镜头感觉？比如：特写/全景/缓慢推进/环绕" "有参考视频吗？镜头运动通过视频参考最稳定" ``` **关于动作：** ``` "画面中有什么动作？比如：人物走路/产品旋转/倒液体" "动作要快还是慢？" ``` **关于音效：** ``` "需要配音或背景音乐吗？" ``` --- ## 输出标准格式 ``` ━━━━━━━━━━━━━━━━━━━━ 📋 精准 Prompt ━━━━━━━━━━━━━━━━━━━━ [完整中文 Prompt] ━━━━━━━━━━━━━━━━━━━━ 📡 参考 API 参数 ━━━━━━━━━━━━━━━━━━━━ model: [模型名] duration: [时长] quality: 720p aspect_ratio: [比例] generate_audio: true prompt: [英文版 Prompt] ━━━━━━━━━━━━━━━━━━━━ 📌 使用说明 ━━━━━━━━━━━━━━━━━━━━ • 链接有效期：24小时，及时下载 • 建议先用 fast 模型测试 • Prompt 建议≤500中文字或1000英文词 • 音效默认开启，如需默片设 generate_audio: false • API 文档：https://seedance2api.app ``` --- ## Prompt 质量自检 ``` ✓ 主体明确（谁/什么） ✓ 场景/背景交代 ✓ 动作/状态具体（"走" > "动"） ✓ 光线/色调说明 ✓ 镜头类型描述（推/拉/移/跟/环绕） ✓ 无矛盾（不说"黑夜"又描述"阳光感"） ``` --- ## 常见问题处理 | 需求 | 处理方式 | |------|---------| | 镜头不稳定 | 引导提供参考视频用 @video 参考镜头 | | 首尾连贯 | 提供2张图，prompt 说明 "from [图1] to [图2]" | | 视频延长 | 结尾加 "Extend @video1 by N seconds"，描述最后一帧状态 | | 长镜头 | 结尾加 "No scene cuts throughout, one continuous shot" | | 不要某元素 | prompt 加 "without [元素]" 或 "avoid [元素]" | | 指定音效 | prompt 加 "Background BGM: [描述]" | --- ## 镜头描述速查 | 效果 | 写法 | |------|------| | 推近 | Camera pushes in / Camera zooms in | | 拉远 | Camera pulls back | | 横移 | Camera pans left/right | | 跟拍 | Camera follows / Camera tracks | | 环绕 | Camera circles around | | 升降 | Camera rises/drops | | 希区柯克 | Hitchcock zoom | | 加速 | Speed accelerates like a roller coaster | --- ## 结尾必备 ``` No scene cuts throughout, one continuous shot. ``` （确保生成连续镜头） --- *此技能由 Anna 整理 · v1.0.1（纯提示词生成版）*


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: zmlgit/task-watchdog-plugin (version 1.1.0)

# Task Watchdog OpenClaw plugin that auto-notifies on subagent failures, exec errors, and stale tasks. ## Hooks - **subagent_ended**: Detects abnormal outcomes (error/timeout/killed/reset/deleted) and notifies parent session - **after_tool_call (exec)**: Watches for abnormal exec exits (non-zero, OOM, signals) - **heartbeat_prompt_contribution**: Injects stale-task patrol instructions into heartbeat cycles - **gateway_start**: Timer-based patrol that periodically triggers heartbeat checks ## Install ```bash openclaw plugin install openclaw-task-watchdog ``` ## Config All optional — works with defaults: ```json { "task-watchdog": { "subagentNotifyOn": ["error", "timeout", "killed"], "execNotifyOnAbnormal": true, "timerPatrol": true, "timerPatrolIntervalMs": 120000, "staleThresholdMs": 1800000 } } ```


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: daniellummis/readme-env-table-sync (version 1.0.0)

--- name: readme-env-table-sync description: Generate and sync a README environment-variable table from .env.example using marker blocks, with drift detection for CI. version: 1.0.0 metadata: {"openclaw":{"requires":{"bins":["bash","python3"]}}} --- # README Env Table Sync Use this skill to keep README environment-variable docs aligned with the real `.env.example` file. ## What this skill does - Parses env keys from `.env.example` (or another env template file) - Generates a markdown table with key/default values - Detects doc drift by comparing generated table with the README marker block - Optionally applies the update directly into README ## Inputs Optional: - `ENV_FILE` (default: `.env.example`) - `README_FILE` (default: `README.md`) - `SYNC_MODE` (`report` or `apply`, default: `report`) - `TABLE_START_MARKER` (default: `<!-- ENV_TABLE_START -->`) - `TABLE_END_MARKER` (default: `<!-- ENV_TABLE_END -->`) ## Run Drift report (CI-friendly): ```bash ENV_FILE=.env.example \ README_FILE=README.md \ bash skills/readme-env-table-sync/scripts/sync-readme-env-table.sh ``` Apply sync: ```bash ENV_FILE=.env.example \ README_FILE=README.md \ SYNC_MODE=apply \ bash skills/readme-env-table-sync/scripts/sync-readme-env-table.sh ``` Run against included fixtures: ```bash ENV_FILE=skills/readme-env-table-sync/fixtures/.env.sample \ README_FILE=skills/readme-env-table-sync/fixtures/README.sample.md \ SYNC_MODE=apply \ bash skills/readme-env-table-sync/scripts/sync-readme-env-table.sh ``` ## Output contract - Exit `0` when table is already in sync (report) or update is applied (apply) - Exit `1` on invalid inputs, missing markers, parse errors, or detected drift in report mode - Prints a short summary with key count and mode


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: 0xrag/search-for-service (version 0.1.0)

--- name: search-for-service description: Search and browse the x402 bazaar marketplace for paid API services. Use when you or the user want to find available services, see what's available, discover APIs, or need an external service to accomplish a task. Also use as a fallback when no other skill clearly matches — search the bazaar to see if a paid service exists. Covers "what can I do?", "find me an API for...", "what services are available?", "search for...", "browse the bazaar". user-invocable: true disable-model-invocation: false allowed-tools: ["Bash(npx awal@latest x402 bazaar *)", "Bash(npx awal@latest x402 details *)"] --- # Searching the x402 Bazaar Use the `npx awal@latest x402` commands to discover and inspect paid API endpoints available on the x402 bazaar marketplace. No authentication or balance is required for searching. ## Commands ### Search the Bazaar Find paid services by keyword using BM25 relevance search: ```bash npx awal@latest x402 bazaar search <query> [-k <n>] [--force-refresh] [--json] ``` | Option | Description | | ----------------- | ------------------------------------ | | `-k, --top <n>` | Number of results (default: 5) | | `--force-refresh` | Re-fetch resource index from CDP API | | `--json` | Output as JSON | Results are cached locally at `~/.config/awal/bazaar/` and auto-refresh after 12 hours. ### List Bazaar Resources Browse all available resources: ```bash npx awal@latest x402 bazaar list [--network <network>] [--full] [--json] ``` | Option | Description | | ------------------ | --------------------------------------- | | `--network <name>` | Filter by network (base, base-sepolia) | | `--full` | Show complete details including schemas | | `--json` | Output as JSON | ### Discover Payment Requirements Inspect an endpoint's x402 payment requirements without paying: ```bash npx awal@latest x402 details <url> [--json] ``` Auto-detects the correct HTTP method (GET, POST, PUT, DELETE, PATCH) by trying each until it gets a 402 response, then displays price, accepted payment schemes, network, and input/output schemas. ## Examples ```bash # Search for weather-related paid APIs npx awal@latest x402 bazaar search "weather" # Search with more results npx awal@latest x402 bazaar search "sentiment analysis" -k 10 # Browse all bazaar resources with full details npx awal@latest x402 bazaar list --full # Check what an endpoint costs npx awal@latest x402 details https://example.com/api/weather ``` ## Prerequisites - No authentication needed for search, list, or details commands ## Next Steps Once you've found a service you want to use, use the `pay-for-service` skill to make a paid request to the endpoint. ## Error Handling - "CDP API returned 429" - Rate limited; cached data will be used if available - "No X402 payment requirements found" - URL may not be an x402 endpoint


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: suspicious | SkillSpector: clean (LOW)
Skill: williamwang-wh/claw-summarize-pro (version 1.0.0)

--- name: summarize description: Summarize URLs or files with the summarize CLI (web, PDFs, images, audio, YouTube). homepage: https://summarize.sh metadata: {"clawdbot":{"emoji":"🧾","requires":{"bins":["summarize"]},"install":[{"id":"brew","kind":"brew","formula":"steipete/tap/summarize","bins":["summarize"],"label":"Install summarize (brew)"}]}} --- # Summarize Fast CLI to summarize URLs, local files, and YouTube links. ## Quick start ```bash summarize "https://example.com" --model google/gemini-3-flash-preview summarize "/path/to/file.pdf" --model google/gemini-3-flash-preview summarize "https://youtu.be/dQw4w9WgXcQ" --youtube auto ``` ## Model + keys Set the API key for your chosen provider: - OpenAI: `OPENAI_API_KEY` - Anthropic: `ANTHROPIC_API_KEY` - xAI: `XAI_API_KEY` - Google: `GEMINI_API_KEY` (aliases: `GOOGLE_GENERATIVE_AI_API_KEY`, `GOOGLE_API_KEY`) Default model is `google/gemini-3-flash-preview` if none is set. ## Useful flags - `--length short|medium|long|xl|xxl|<chars>` - `--max-output-tokens <count>` - `--extract-only` (URLs only) - `--json` (machine readable) - `--firecrawl auto|off|always` (fallback extraction) - `--youtube auto` (Apify fallback if `APIFY_API_TOKEN` set) ## Config Optional config file: `~/.summarize/config.json` ```json { "model": "openai/gpt-5.2" } ``` Optional services: - `FIRECRAWL_API_KEY` for blocked sites - `APIFY_API_TOKEN` for YouTube fallback


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: oakcoderx/half-full (version 0.1.4)

--- name: half-full description: 半饱 — 生活的高潮所在。A mindful eating companion for desk workers. Track meals with photos, understand your body's needs, no gym guilt. version: 0.1.4 author: oak lee tags: [nutrition, health, diet, mindful-eating, 减脂, 饮食, 健康] metadata: openclaw: emoji: "🍃" requires: bins: ["python3"] scripts: - scripts/log.py - scripts/profile.py - scripts/food_db.py - scripts/health_sync.py commands: - "python3 scripts/log.py add --meal 早餐 --items '鸡蛋,燕麦'" - "python3 scripts/log.py today" - "python3 scripts/profile.py show" - "python3 scripts/profile.py update --weight 60" - "python3 scripts/health_sync.py parse '[半饱数据] 步数：8000 步，活动消耗：300 千卡'" - "python3 scripts/health_sync.py today" install: "pip3 install -q" --- # 半饱 🍃 生活的高潮所在。 不是教练，不是健身搭子，是你幸福生活的陪伴。


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (CRITICAL)
Skill: airclear/bmad-brainstorming-coach (version 0.1.0)

--- name: bmad-brainstorming-coach description: 激活 BMad 系统的 "Brainstorming Coach" 代理（Carson），用于引导创新工作坊、头脑风暴会议和创意激发。适用于需要打破常规思维、生成大量创意、或者进行系统性创新探索的场景。 --- # BMad Brainstorming Coach (Carson) 你现在是 BMad 系统中的 **Carson**，一位精英头脑风暴专家和创新催化剂。 ## 角色定义 (Persona) 请参考本地文件：`references/agent_definition.md` 获取完整的 Persona 定义。 - **身份**：拥有 20 多年引导突破性会议经验的高级引导者。精通各种创意技术、群体动力学和系统化创新。 - **沟通风格**：充满活力的即兴表演教练——高能量，基于想法进行 "YES AND"（是的，而且...），庆祝各种疯狂的想法。 - **原则**：心理安全是开启突破的关键；今天的疯狂想法是明天的创新；幽默和游戏是严肃的创新工具。 ## 激活工作流 (Activation Workflow) 在首次激活或用户请求时，必须执行以下步骤： 1. **预检与配置 (Pre-flight & Configuration)**： - 检查本地是否已存在配置信息。 - 需要的变量：`user_name` (用户姓名), `communication_language` (沟通语言), `output_folder` (输出目录)。 - **逻辑**： - 如果变量未定义，请向用户询问：“为了更好地为您服务，我需要了解您的姓名、首选沟通语言以及头脑风暴成果的保存目录。” - 一旦获取，请在当前会话中记住这些变量。 2. **开场致辞 (Greeting)**： - 使用 `{user_name}` 和 `{communication_language}` 进行问候。 - 展示 Carson 的 persona 和充满活力的风格。 - **告知用户**：可以随时输入 `/bmad-help` 获取建议，也可以结合具体需求。 3. **展示菜单 (Display Menu)**： - 按照以下顺序展示编号菜单： 1. **[MH] Redisplay Menu Help** - 重新显示菜单帮助。 2. **[CH] Chat with the Agent** - 随意聊聊任何话题。 3. **[BS] Guide me through Brainstorming** - 引导我进行任何主题的头脑风暴。 4. **[PM] Start Party Mode** - 开启派对模式 (Party Mode)。 5. **[DA] Dismiss Agent** - 解散代理。 4. **等待输入**：停止并等待用户输入。 ## 交互处理逻辑 (Interaction Logic) 根据用户输入进行匹配： - **数字输入**：执行对应编号的菜单项。 - **文本输入**：进行不区分大小写的子字符串匹配（Fuzzy Match）。 - **多重匹配**：如果输入匹配多个选项，请用户澄清。 - **无匹配**：显示 "未识别的命令 (Not recognized)"。 ## 菜单处理 (Menu Handlers) - **[BS] Brainstorming**: - 核心引擎：必须加载并遵循 `references/workflow_engine.xml`。 - 配置路径：`assets/workflows/brainstorming/workflow.md`。 - **[PM] Party Mode**: - 执行：`assets/workflows/party-mode/workflow.md`。 - **[CH] Chat**: - 自由对话，保持 Carson 风格。 ## 工作流执行核心规则 (Internal Workflow Engine) 当执行本 Skill 包含的工作流时，你必须充当工作流引擎： 1. **加载引擎**：始终加载并参考 `references/workflow_engine.xml` 作为核心指令集。 2. **本地路径优先**：在工作流中引用的所有资源路径（如步骤文件、CSV）必须解析为 `assets/workflows/` 下的相对路径。 3. **协作式保存 (template-output)**： - 每遇到 `template-output` 标签，必须生成内容并保存到 `{output_folder}` 下。 - **中断并确认**：在保存后，向用户展示生成的内容，并等待指令： - `[c] 继续 (Continue)`: 进入下一步。 - `[a] 高级启发 (Advanced Elicitation)`: 激活 `assets/workflows/advanced-elicitation.xml`。 - `[p] 派对模式 (Party-Mode)`: 切换到派对模式。 - `[y] YOLO`: 自动完成当前文档。 ## 沟通准则 (Communication Rules) - **语言**：始终使用配置中定义的 `{communication_language}`。 - **风格**：保持 "YES AND" 积极态度。 - **自包含性**：本 Skill 的所有逻辑、模板和引擎均已包含在本地 `references/` 和 `assets/` 目录下，严禁引用外部目录（如 `_bmad`）。


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

--- name: github-actions-failure-hour-audit description: Audit GitHub Actions failure timing by day/hour to surface recurring outage windows and staffing hotspots. version: 1.0.0 metadata: {"openclaw":{"requires":{"bins":["bash","python3"]}}} --- # GitHub Actions Failure Hour Audit Use this skill to identify when failures cluster so teams can target flaky time windows and on-call coverage. ## What this skill does - Reads one or more GitHub Actions workflow run JSON exports - Keeps only failure-like conclusions (`failure`, `cancelled`, `timed_out`, `action_required`, `startup_failure`) - Buckets failures into day/hour windows (with optional timezone offset) - Ranks windows by severity using failure-run thresholds - Emits text or JSON output for dashboards or CI gates ## Inputs Optional: - `RUN_GLOB` (default: `artifacts/github-actions/*.json`) - `TOP_N` (default: `24`) - `OUTPUT_FORMAT` (`text` or `json`, default: `text`) - `WARN_FAILURE_RUNS` (default: `3`) - `CRITICAL_FAILURE_RUNS` (default: `6`) - `FAIL_ON_CRITICAL` (`0` or `1`, default: `0`) - `TZ_OFFSET_HOURS` (default: `0`) — integer timezone shift from UTC, between `-23` and `23` - `WORKFLOW_MATCH`, `WORKFLOW_EXCLUDE` (regex, optional) - `BRANCH_MATCH`, `BRANCH_EXCLUDE` (regex, optional) - `REPO_MATCH`, `REPO_EXCLUDE` (regex, optional) ## Collect run JSON ```bash gh run view <run-id> --json databaseId,workflowName,headBranch,conclusion,createdAt,updatedAt,url,repository \ > artifacts/github-actions/run-<run-id>.json ``` ## Run Text report: ```bash RUN_GLOB='artifacts/github-actions/*.json' \ WARN_FAILURE_RUNS=3 \ CRITICAL_FAILURE_RUNS=6 \ TZ_OFFSET_HOURS=7 \ bash skills/github-actions-failure-hour-audit/scripts/failure-hour-audit.sh ``` JSON output + fail gate: ```bash RUN_GLOB='artifacts/github-actions/*.json' \ OUTPUT_FORMAT=json \ FAIL_ON_CRITICAL=1 \ bash skills/github-actions-failure-hour-audit/scripts/failure-hour-audit.sh ``` ## Output contract - Exit `0` in reporting mode - Exit `1` when `FAIL_ON_CRITICAL=1` and one or more critical windows are found - Text output includes summary and top windows by severity - JSON output includes `summary`, ranked `windows`, and `critical_windows`


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: yang1002378395-cmyk/ai-data-governance (version 1.0.0)

--- name: ai-intelligent-data-governance version: 1.0.0 description: 企业数据治理，数据质量 + 数据安全。 metadata: openclaw: emoji: "📈" requires: bins: [] --- # AI 智能数据治理系统 ## 描述 企业数据治理，数据质量 + 数据安全。 ## 功能 - 数据质量（自动检测） - 数据安全（权限管理） - 数据标准（统一规范） - 数据血缘（追踪来源） - 数据资产（资产目录） ## 定价 - 基础版：¥299/月（10 数据源） - 专业版：¥1499/月（50 数据源） - 企业版：¥4999/月（无限数据源） ## 适用场景 - 企业数据治理 - 数据中台 - 数据安全 - 数据质量管理 ## 技术栈 - Python + FastAPI - 数据质量引擎 - 权限管理 - 数据血缘追踪 ## 安装 ```bash git clone https://github.com/openclaw-skills/ai-intelligent-data-governance cd ai-intelligent-data-governance pip install -r requirements.txt python app.py ``` --- 创建：2026-03-13 作者：OpenClaw Skills Team


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: x-rayluan/clawdy-selfie (version 1.0.1)

--- name: clawdy-selfie description: Generate a Clawdy selfie with the installed local helper script and the configured FAL_KEY. allowed-tools: Bash(bash:*) Bash(curl:*) Read Write --- # Clawdy Selfie Use this skill only when the user asks Clawdy for a selfie, photo, mirror pic, outfit shot, or location selfie. Rules: - Generate/send a real image when possible. - Keep Clawdy clearly male-coded. - ALL Clawdy images must use the same single male reference image. - Never switch to text-to-image fallback for Clawdy unless Ray explicitly asks for it. - If reference-based generation fails, report the exact API/tool error. Do not invent explanations like quota/balance unless the API explicitly says that. Execution: - Run the local helper script in this skill's `scripts` folder. - Use the configured `FAL_KEY` env. - Use the bundled Clawdy reference image in this skill's `assets` folder. Preferred prompt style: - mirror selfie for outfit/fashion/full-body requests - direct selfie for close-up/location/boyfriend vibe requests Default visual baseline: - handsome Korean-American male - masculine jawline - athletic build - boyfriend vibe - tasteful, not explicit


Security scan verdicts — ClawScan: suspicious | static analysis: suspicious | VirusTotal: stale | SkillSpector: suspicious (CRITICAL)
Skill: liyanhe95/insurance-rate-table (version 1.0.0)

# 保险费率二维表生成工具 ## Skill 职责 根据用户提供的保险产品参数，自动生成符合行业标准的 Excel 费率二维表。 ## 触发场景 用户请求生成以下内容时触发： - "生成费率表" - "生成费率二维表" - "生成XX产品费率表" - "生成XX保险费率" ## 执行步骤 ### 第1步：收集产品参数 向用户确认以下必填参数： 1. **产品名称** - 产品全称 2. **产品类型** - 年金险/重疾险/寿险/医疗险等 3. **领取时间** - 如：自55周岁、自60周岁 4. **保障计划** - 如：计划一、计划二 5. **交费期间** - 如：趸交、10年、20年 6. **交费方式** - 一次交清/月交/年交/半年交/季交/不定期交 7. **被保人年龄范围** - 如：0-70岁 8. **被保人性别** - 男、女 ### 第2步：确认交费方式与交费期间约束规则 根据产品类型确认以下约束： - **一次交清** 只能匹配 **趸交** - **月交/年交/半年交/季交/不定期交** 不能匹配 **趸交** ### 第3步：生成 Excel 文件 执行脚本生成符合标准的费率表： - 多级表头结构 - 自动过滤无效组合 - 填充示例费率数据 ### 第4步：输出交付 - 文件保存至 workspace 目录 - 告知用户文件位置和表格结构 ## 输出标准 ### Excel 文件命名规范 ``` {产品名称}费率表.xlsx ``` ### 表头结构（5行多级表头） | 行号 | 表头内容 | 说明 | |------|----------|------| | 第1行 | 保障计划 | 计划一、计划二 | | 第2行 | 交费期间 | 趸交、10年、20年 | | 第3行 | 交费方式 | 一次交清/月交/年交/半年交/季交/不定期交 | | 第4行 | 领取时间 | 自55周岁、自60周岁 | | 第5行 | 被保人年龄/被保人性别 | 女、男 | ### 数据结构 - **A列**：被保人年龄（0-70岁） - **B列及以后**：对应各方案的保费数据 - 数据行按年龄递增排列 ### 组合过滤规则 - 一次交清 ↔ 趸交（唯一有效组合） - 月交/年交/半年交/季交/不定期交 ↔ 10年/20年 - 其他组合不生成 ### 文件格式 - 格式：`.xlsx`（Excel 2007+） - 编码：`UTF-8` - Sheet 名称：`费率表`

path: package.json
content: {
  "name": "insurance-rate-table-generator",
  "version": "1.0.0",
  "description": "保险费率二维表生成工具",
  "main": "scripts/generate-rate-table.js",
  "scripts": {
    "generate": "node scripts/generate-rate-table.js"
  },
  "dependencies": {
    "xlsx": "^0.18.5"
  },
  "keywords": [
    "insurance",
    "rate-table",
    "excel"
  ],
  "author": "",
  "license": "ISC"
}


path: scripts/generate-rate-table.sh
content: #!/bin/bash
# 保险费率表生成工具
# 
# 使用方法：
#   ./generate-rate-table.sh "产品名称"
# 
# 示例：
#   ./generate-rate-table.sh "星海赢家朱雀版"

PRODUCT_NAME="${1:-费率表}"
SCRIPT_DIR="$(dirname "$0")"

cd "$SCRIPT_DIR/.."

node scripts/generate-rate-table.js "$PRODUCT_NAME" \
  --plans="计划一,计划二" \
  --payment-years="趸交,10年,20年" \
  --payment-methods="一次交清,月交,年交,半年交,季交,不定期交" \
  --receive-ages="自55周岁,自60周岁" \
  --age-range="0-70"


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