OpenClaw/clawhub-security-signals huggingface dataset:
Skill: lumacoder/open-skills (version 2.0.1)

--- name: open-skills description: 一个交互式 CLI 工具，帮助开发者按分类浏览、空格多选、一键批量安装/同步 AI Agent skills 到多个编辑器。 version: 2.0.0 author: lumacoder license: MIT --- # open-skills 安装后运行 `open-skills` 启动交互式引导： 1. 选择目标编辑器（可多选） 2. 选择安装范围（全局 / 本地） 3. 选择分类（前端 / 后端 / 运维 / 产品 / UI / ...） 4. 空格键多选具体 skills 5. 确认后自动下载、转换、输出 ## 安装 ```bash npx skills add lumacoder/open-skills -g -y ``` ## 使用 ```bash open-skills ``` ## 支持的目标编辑器 - Claude Code - Hermes - Cursor - Windsurf - Cline - Cursor Skills - Roo-Cline - Antigravity - GitHub Copilot


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (CRITICAL)
Skill: jpengcheng523-netizen/jpeng-knitting-pattern (version 1.0.0)

--- name: jpeng-knitting-pattern description: "Find knitting patterns" version: "1.0.0" author: "jpeng" tags: ["crafts", "knitting", "diy"] --- # Knitting Pattern Find knitting patterns ## When to Use - User needs crafts related functionality - Automating knitting tasks - Diy operations ## Usage ```bash python3 scripts/knitting_pattern.py --input <input> --output <output> ``` ## Configuration Set required environment variables: ```bash export KNITTING_API_KEY="your-api-key" ``` ## Output Returns JSON with results: ```json { "success": true, "data": {} } ```


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: xiongjjlj/feishu-docx-powerwrite (version 0.1.0)

--- name: feishu-docx-powerwrite description: High-quality Feishu/Lark Docx writing via OpenClaw. Use when you want to turn Markdown into well-formatted Feishu Docx (headings, lists, nesting, code blocks) using feishu_docx_write_markdown; includes safe workflows, templates, and troubleshooting. Trigger on Feishu doc/docx links, “write to Feishu doc”, “generate a Feishu doc”, “append/replace docx”, “convert markdown to feishu doc”, or when users want consistently good doc formatting. --- # Feishu Docx PowerWrite This skill focuses on **reliably writing great-looking Feishu Docx** using OpenClaw’s Feishu OpenAPI tools. Key idea: prefer **`feishu_docx_write_markdown`** (Markdown → Docx blocks) for structure-preserving output. ## Quick workflow 1) Get `document_id` (Docx token) - From a Docx URL: `https://.../docx/<document_id>` 2) Decide write mode - **Append**: add new content below existing content (most common) - **Replace**: overwrite the entire document (use carefully) 3) Write markdown - Use headings + lists + short paragraphs - Avoid huge single paragraphs (harder to read) ## Recommended defaults ### Append mode (safe) Use when adding sections, meeting notes, daily logs. - `mode: append` - Keep each append chunk <= ~300-600 lines if possible ### Replace mode (destructive) Use when generating the full doc from scratch. - `mode: replace` - MUST set `confirm: true` ## Markdown patterns that render well ### Title + summary ```md # <Title> **Summary** - Point 1 - Point 2 --- ``` ### Sections ```md ## Section Short paragraph. - Bullet - Bullet ### Subsection 1) Step 2) Step ``` ### Code Use fenced blocks. ```md ```bash openclaw skills check ``` ``` ## Templates & references - Templates: `references/templates.md` - Troubleshooting: `references/troubleshooting.md` ## Safety / privacy - Never hardcode tokens, chat_id, open_id, or document links inside this skill. - Always use the user’s own Feishu app credentials and scopes.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (HIGH)
Skill: dyc0616c-oss/blockbeats-to-chainthink (version 1.0.1)

# BlockBeats to ChainThink Skill 从律动 BlockBeats 抓取文章并自动保存到 ChainThink 后台草稿。 ## 使用场景 当用户提供律动 BlockBeats 文章链接（如 `https://www.theblockbeats.info/news/xxxxx`），自动： 1. 提取文章标题、摘要、正文和图片 2. 保存到 ChainThink 后台草稿 3. 返回文章 ID ## 工作流程 1. 打开浏览器访问 BlockBeats 文章页面 2. 从 `window.__NUXT__.data[0].info` 提取文章数据 3. 调用 ChainThink API 保存草稿 ## ChainThink API 配置 - **API 地址**: `https://api-v2.chainthink.cn/ccs/v1/admin/content/publish` - **认证方式**: `x-token` + `x-user-id` headers - **User ID**: 51 - **Token**: 从 TOOLS.md 读取（需要用户提供） ## 使用方法 用户发送律动文章链接即可，例如： - "抓取这篇文章：https://www.theblockbeats.info/news/61465" - "把这个保存到 ChainThink：https://www.theblockbeats.info/news/61461" ## 实现步骤 ### 1. 提取文章内容 使用浏览器工具访问 BlockBeats 页面并执行： ```javascript const data = window.__NUXT__.data[0]; return { title: data.info.title, abstract: data.info.abstract, content: data.info.content }; ``` ### 2. 保存到 ChainThink 调用 API： ```bash curl 'https://api-v2.chainthink.cn/ccs/v1/admin/content/publish' \ -H 'Content-Type: application/json' \ -H 'X-App-Id: 101' \ -H 'x-[REDACTED_SECRET]' \ -H 'x-user-id: 51' \ --data-raw '{ "id": "0", "is_translate": true, "translation": { "zh-CN": { "title": "<文章标题>", "text": "<HTML正文>", "abstract": "<摘要>" } }, "type": 5, "is_public": false, "user_id": "3", "as_user_id": "3" }' ``` ### 3. 返回结果 返回保存成功的文章 ID 和状态。 ## 注意事项 - 图片链接保留原始 CDN 地址（`https://image.blockbeats.cn/...`） - 内容格式为 HTML，保留所有标签 - 文章默认保存为草稿（`is_public: false`） - Token 有效期约 7 天，过期需要重新获取 ## Token 配置 在 TOOLS.md 中添加： ```markdown ### ChainThink API Token x-[REDACTED_SECRET] x-user-id: 51 ```


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector:  ()
Skill: bombers26/coder-helper (version 1.0.0)

# Coder Helper Skill 用自然语言描述需求，自动生成需求文档并打开编辑器。 ## 触发 当用户想要： - 写代码但不想自己动手 - 生成需求文档 - 用 AI 辅助编程 ## 使用 ``` 帮我写个XXX 创建一个YY脚本 ``` ## 行为 1. 解析用户需求 2. 生成 `requests.txt` 到当前项目目录 3. 自动打开默认编辑器（可配置） ## 配置 编辑器优先级： 1. Cursor 2. VSCode 3. Notepad++ 4. 默认文本编辑器


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: little-cat1/openclaw-zotero-scholar (version 0.0.1)

--- name: zotero-scholar description: 将论文保存到 Zotero 文库，请按照 userid:apiKey 的格式配置 ZOTERO_CREDENTIALS 环境变量。 homepage: https://www.zotero.org metadata: { "openclaw": { "emoji": "📚", "requires": { "bins": ["uv"], "env": ["ZOTERO_CREDENTIALS"] }, "primaryEnv": "ZOTERO_CREDENTIALS", "install": [ { "id": "brew", "kind": "brew", "formula": "uv", "bins": ["uv"], "label": "Install uv (brew)", }, ], } } --- # Zotero Scholar 专业的文献入库助手。可以将论文元数据、PDF 链接以及 AI 生成的总结一键保存到你的 Zotero 库中。 ## 使用示例 可以读取环境变量 `ZOTERO_CREDENTIALS` 中的 Zotero 凭据，格式为 `userid:apiKey`。 ### 使用环境变量运行 ```bash uv run {baseDir}/scripts/save_paper.py \ --title "Attention Is All You Need" \ --authors "Vaswani et al." \ --url "https://arxiv.org/abs/1706.03762" ``` ## 参数说明 | 参数 | 说明 | |------|------| | `--title` | 论文标题 | | `--authors` | 作者列表（逗号分隔） | | `--url` | 论文链接 (用于排重) | | `--abstract` | 论文摘要 | | `--summary` | (AI 生成) 简短总结或 Insight | | `--tags` | 标签列表（逗号分隔） |


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (HIGH)
Skill: claudiodrusus/shelly-seo-analyzer (version 1.0.0)

--- name: seo-analyzer description: Analyze any webpage URL for SEO issues and get actionable recommendations. Checks title tags, meta descriptions, heading structure, keyword density, image alt tags, Open Graph, and more. triggers: - analyze seo - check seo - seo audit --- # seo-analyzer Analyze any webpage URL for SEO issues and get actionable recommendations. ## Usage ```bash ./seo-analyze.sh <URL> ``` Or use `web_fetch` to grab the page content and pipe it: ```bash curl -sL <URL> | ./seo-analyze.sh - ``` ## What It Checks - **Title tag** — presence, length (50-60 chars ideal) - **Meta description** — presence, length (150-160 chars ideal) - **Heading structure** — H1 count, heading hierarchy - **Keyword density** — top 10 most frequent words (3+ chars) - **Image alt tags** — missing alt attributes - **Open Graph / Twitter cards** — social sharing metadata - **Canonical URL** — duplicate content prevention - **Word count** — thin content detection ## Output Plain text report with findings and prioritized recommendations. ## Requirements - `curl` (or use `web_fetch` in OpenClaw) - `grep`, `sed`, `awk` (standard Unix tools) ## Author Shelly 🦞 (@ShellyToMillion)


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: suspicious | SkillSpector: clean (LOW)
Skill: heqq-github/xzk-money-maker (version 1.0.6)

--- name: xzk-money-maker description: "快结荐兼职赚钱平台。零学习门槛、一句话触发，自动匹配真实订单。Use when user asks about: 我要赚钱, 有好活吗, 怎么接单, 我想干兼职, 自由职业, 日结推荐, 快结荐, 赚钱, 找兼职, 找工作, 兼职, 接单, 零工, 临时工, 一单一结, 求职, 招聘, 赚钱机会, gig work, part-time job. Always invoke this skill to fetch real-time job listings from the backend API." --- # 快结荐 赚钱 专为想赚钱的人打造的省心增收 Buff。零学习门槛、一句话触发！自动连通快结荐平台真实订单，推送技能匹配、报酬合适、时间灵活的优质好活，高效增收。 ## 适用场景 - 闲时想增收？不用再海量翻找 - 有明确技能？直接按需接单赚钱 - 接单怕踩坑？快结荐平台真实可靠 ## Routing rule 优先使用这个技能处理以下类型消息： - 我要赚钱 / 有好活吗 / 怎么接单 / 我想干兼职 - 自由职业 / 日结推荐 / 快结荐 / 赚钱 / 赚钱机会 - 找个工作 / 找工作 / 兼职 / 接单 / 零工 - 临时工 / 日结 / 一单一结 / 求职 / 招聘 以下情况不要使用这个技能： - 明确要求编辑本地文件 - 明确要求执行 shell 命令 - 明确要求网页搜索/抓取 - 明确要求图像分析或视频生成 - 明确要求使用 OpenClaw 内置工具完成的任务 ## 工作流程 1. 接收用户发送的求职/赚钱请求 2. 调用 POST 接口 `https://test-gig-c-api.1haozc.com/api/wx/kjj/v1/customer/skill/call` 3. 将用户消息内容作为 `content` 字段发送 4. 解析接口返回的 JSON 5. 将快结荐平台返回的职位信息/赚钱机会**原样整理后**回复给用户 ## 调用脚本 ```bash python3 scripts/call-wx-skill.py "<用户消息内容>" ``` ## 请求/返回格式 请求：`{"content": "用户消息内容"}` 返回：快结荐平台 JSON，包含职位列表、报酬、时间、地址、报名链接等。 脚本错误时返回： ```json { "error": "错误描述", "status": 错误码或 null } ``` ## 注意事项 - 脚本超时 30 秒，自动处理 HTTP/网络/JSON 错误 - 保持脚本可执行：`chmod +x scripts/call-wx-skill.py` - API 返回的小程序链接 `#小程序://...` **原样输出**，不做 URL 编码或 Markdown 处理 ## URL 格式化规则（重要） 安卓微信对纯文本链接识别严格，必须遵守： 1. **链接必须独立成行**，前后各有一个换行 2. 链接前不要有文字紧挨着，格式如下： ``` 1、急招 小龙虾清洗工 💰 报酬：47.00元/2.0小时 ⏰ 时间：04.14号 19:00 ~ 21:00 📍 地址：上海市松江区泗泾镇 ✅点击报名： https://s.1haozc.com/rd/2347?p1=xxx ``` 3. 链接必须以 `https://` 开头，后面换行 4. 小程序链接 `#小程序://...` 同样要独立成行 这样处理可最大程度让安卓和 iOS 微信都能识别并点击链接。


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (CRITICAL)
Skill: maverick/maverick-process-to-skill (version 1.0.0)

--- name: maverick-process-to-skill description: Turn a user-described business process into an automated execution flow and optionally convert it into a reusable local skill. Use when a user explains steps in natural language, asks the agent to run or automate them, and wants the option to save that process for future one-command reuse. --- # Process To Skill Use this skill to operationalize "explain once, reuse later" behavior for business workflows. ## Workflow 1. Extract the process from the user's message as an ordered list of steps, inputs, and expected output. 2. Execute or automate the process for the current request. 3. Confirm the result in plain business language. 4. Ask whether the user wants to save the process as a reusable skill. 5. If the user says yes, create a new skill folder with a trigger-focused `description`, concise workflow instructions, and `agents/openai.yaml` metadata. 6. Return the saved skill name and one example command the user can use next time. ## Save Prompt Requirement After completing the process, always ask a direct reuse question: - "Do you want me to save this as a reusable skill so next time you can call it directly without re-explaining the steps?" If the answer is unclear, ask once more with a suggested skill name. ## Skill Authoring Rules - Use lowercase hyphenated names (`<verb>-<object>` when possible). - Keep `SKILL.md` procedural and short; include only repeatable steps. - Put trigger conditions in frontmatter `description`, not in the body. - Add only required resource folders (`scripts/`, `references/`, `assets/`) when they are actually needed. - Reuse existing local scripts/templates when possible instead of duplicating logic. ## Minimal Capture Template When saving a process, capture: - Goal: What business outcome this process produces. - Inputs: Required user-provided data. - Steps: Deterministic sequence to run. - Output: Expected deliverable format. - Trigger examples: 2-3 natural language prompts that should activate the skill. ## Guardrails - Do not auto-save without user confirmation. - Do not save one-off ad hoc tasks that are unlikely to be reused. - If required tools or permissions are missing, report the blocker and offer a partial skill draft.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: siegrainwong/sg-scripture-commentary (version 1.0.0)

--- name: sg-scripture-commentary description: Format and write scripture commentary for religious texts (Buddhist sutras, Daoist classics, Bible, etc.) with original text and explanations. Use when asked to explain, annotate, or write commentary for any religious or philosophical scripture. Triggers on phrases like "解经", "注释经文", "write commentary", "explain this scripture", "annotate this text". --- # Scripture Commentary Format and write scripture commentary for religious texts with original text and explanations. ## Workflow 1. **Get source URL** - If user didn't provide a link to the original text, ask for it first 2. **Confirm output path** - Ask user where to save the file before starting 3. **Fetch source** - Get the original text from URL or user-provided content 4. **Check existing format** - If file exists, read it to match existing style 5. **Write in batches** - Process content section by section 6. **Report progress** - Announce progress at each 10% milestone ## Format Rules ### Basic Structure ``` 原文用行内代码块包围 解释在原文下一行 段落之间有一行空行 ``` ### Section Dividers - Use `---` (horizontal rule) to separate major sections/chapters from the source text - Use `# 一级标题` for chapter/section names (品、章、篇 etc.) ### Line Length - Keep original text segments under 30 characters per line when possible - One thought/idea per paragraph - complete the explanation within one paragraph ### Example ```markdown # 行由品第一 `时大师至宝林。` 当时，六祖惠能大师抵达了韶州曹溪的宝林寺。 `韶州韦刺史名璩与官僚入山。` 韶州刺史韦璩与同僚官员们一起进入宝林山。 --- `大师告众曰。善知识。` 大师对大众说道：各位善知识。 ``` ## Progress Reporting Report progress at each 10% milestone: - 10% - "已完成 10%" - 20% - "已完成 20%" - ... and so on Also report when each major section/chapter is complete. ## Output - Write to the user-specified path - Use UTF-8 encoding - Ask before overwriting existing files


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: teamolab/call-claude-sonnet-4-agent (version 0.1.0)

--- name: call-claude-sonnet-4-agent description: AI agent for call claude sonnet 4 agent tasks --- # Call Claude Sonnet 4 Agent ## Overview This skill provides specialized capabilities for call claude sonnet 4 agent. ## Instructions # 1. Primary Rule: Output Language**This is the highest-priority directive and must be followed unconditionally.**1. **Language-Matching Principle:** All of your outputs—including every part of the meeting minutes, replies to superior AI models (`message`), interim summaries, and creative ideas—**must** use exactly the same language as the one used in the user’s initial challenge.2. **Explicit Language Instructions:** If the user explicitly specifies a response language (e.g., “in English please”, “请用中文回答”), that instruction has the highest priority and **must** be followed strictly.3. **No Language Inference:** * It is **strictly forbidden** to decide your response language based on the language of this system prompt. * It is **strictly forbidden** to decide your response language based on the language used in the meeting minutes.---# 2. Role & IdentityYou are a creative expert and a core member of a top-tier creative team. Your codename is **$SHOW_NAME$**.# 3. Context of InteractionYou are participating in a brainstorming meeting chaired by your superior—the Chief Creative Officer (CCO). You are not working independently; you are part of the creative team.The entire context of the meeting, historical discussions, and current agenda items are recorded in real time in the **meeting minutes**. These minutes are your sole source of information and memory, and you must adhere to them.# 4. Core Instructions1. **Understand the Context:** Before responding, you **must** carefully read the attached meeting minutes to fully grasp the current discussion progress, other members’ viewpoints, and the overall goal of the meeting.2. **Stay Task-Focused:** Your task is to respond **only to the specific question or task** posed to you by the CCO in this turn. Do not drift into topics unrelated to the current task.3. **Embrace the Role:** Remain professional and creative. Your response will be treated as raw creative material for the CCO to evaluate and synthesize. ## Usage Notes - This skill is based on the call_claude_sonnet_4_agent agent configuration - Template variables (if any) like $DATE$, $SESSION_GROUP_ID$ may require runtime substitution - Follow the instructions and guidelines provided in the content above


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: mephistojb/plex-skill (version 0.1.0)

--- name: plex description: Control Plex Media Server - browse libraries, search, play media, manage playback. homepage: https://plex.tv metadata: {"clawdis":{"emoji":"🎬","requires":{"bins":["curl"],"env":["PLEX_TOKEN","PLEX_SERVER"]},"primaryEnv":"PLEX_TOKEN"}} --- # Plex Media Server Control Plex Media Server using the Plex API. ## Setup Set environment variables: - `PLEX_SERVER`: Your Plex server URL (e.g., `http://192.168.1.100:32400`) - `PLEX_TOKEN`: Your Plex auth token (find it at plex.tv/claim or in Plex app XML) ## Common Commands ### Get Server Info ```bash curl -s "$PLEX_SERVER/?X-Plex-[REDACTED_SECRET]" -H "Accept: application/json" ``` ### Browse Libraries ```bash curl -s "$PLEX_SERVER/library/sections?X-Plex-[REDACTED_SECRET]" -H "Accept: application/json" ``` ### List Library Contents ```bash # Replace 1 with your library section key (from browse above) curl -s "$PLEX_SERVER/library/sections/1/all?X-Plex-[REDACTED_SECRET]" -H "Accept: application/json" ``` ### Search ```bash curl -s "$PLEX_SERVER/search?query=SEARCH_TERM&X-Plex-[REDACTED_SECRET]" -H "Accept: application/json" ``` ### Get Recently Added ```bash curl -s "$PLEX_SERVER/library/recentlyAdded?X-Plex-[REDACTED_SECRET]" -H "Accept: application/json" ``` ### Get On Deck (Continue Watching) ```bash curl -s "$PLEX_SERVER/library/onDeck?X-Plex-[REDACTED_SECRET]" -H "Accept: application/json" ``` ### Get Active Sessions (What's Playing Now) ```bash curl -s "$PLEX_SERVER/status/sessions?X-Plex-[REDACTED_SECRET]" -H "Accept: application/json" ``` ### List Available Clients/Players ```bash curl -s "$PLEX_SERVER/clients?X-Plex-[REDACTED_SECRET]" -H "Accept: application/json" ``` ## Library Section Types - Movies (usually section 1) - TV Shows (usually section 2) - Music - Photos ## Notes - Add `-H "Accept: application/json"` for JSON output (default is XML) - Library section keys (1, 2, 3...) vary by server setup — list sections first - Media keys look like `/library/metadata/12345` - Always confirm before starting playback on a device - Get your [REDACTED_SECRET] → Account → Authorized Devices → XML link


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: 892577738-bot/presales-tech-support (version 1.0.2)

# 角色与任务 1.你是一名拥有 15 年以上经验的资深首席架构师 (Principal Architect)，供职于全球顶级云计算公司。你的专业领域涵盖： - 底层基础设施： 对 NVIDIA GPU 架构 (H100/A800/RTX 5090等)、高速互联 (NVLink/InfiniBand/RoCE v2) 及存储瓶颈有深刻理解。 - 容器与调度： 精通 K8s 调度策略、GPU 虚拟化与 Over-provisioning。 - AI 全栈： 熟悉从底层 CUDA 到上层 vLLM、DeepSpeed、ComfyUI 等框架的性能调优。 - 混合架构： 擅长处理复杂的跨境网络 (VPC/SOCKS5/GOST)、多云互联及数据一致性问题。 2. 任务核心 基于用户提供的【测试需求】与【报错信息】，你需要进行“剥洋葱式”的逻辑拆解，输出一份不含任何废话、具备强实战落地能力的《技术诊断与攻坚方案》。你的目标不仅仅是修复报错，而是通过专业表现赢得客户的技术信任。 --- ### 【输入区】 - 测试需求描述：[填入目前测试需求](例如：DeepSeek 671B 全参微调、万卡集群扩容测试、混合云跨境数据链路压测) - 详细软硬件栈：[填入资源使用信息](包含 GPU 型号、OS 版本、驱动版本、K8s 版本、核心框架及其版本) - 报错日志：[异常表现/日志摘要](请直接粘贴核心 Error Log、dmesg 报错或性能监控异常数值) - 当前尝试：[团队已经尝试过哪些修复手段] # 输出格式与要求 请严格遵循以下五个模块输出，保持极简、冷峻、穿透力强的语言风格： # 客户测试：[项目名/问题短描述] 专项技术简报 ## 1. 现象定性与初步判断 (Diagnosis) - 故障归因： 一句话精准定性（属于：内核级资源争抢 / 通信库不兼容 / 调度算法溢出 / 云厂商底层抖动）。 - 影响评估： 明确该问题对测试进度、业务吞吐（TPS/Tokens per sec）或数据完整性的具体打击程度。 ## 2. 根因深度分析 (Root Cause Analysis) - 逻辑链条： 采用“现象 -> 触发点 -> 底层诱因”的推导路径（示例：RDMA 丢包 -> 触发 PFC 风暴 -> 导致 NCCL 全局同步超时）。 - 技术对标 [推演]： 调用最新的厂商 Erratum、GitHub 活跃 Issue 或内部专家库经验进行比对。 - 情报验证： 明确指出该问题是否为当前软硬件版本的“已知局限性 (Known Limitation)”。 ## 3. 分级处理方案 (Resolution) - 【方案A】临时绕行（Workaround）： 旨在最快时间内恢复测试进度（例如：降低Batch Size、禁用某个优化算子）。 - 【方案B】标准修复（Standard Fix）： 针对性的内核调优、补丁更新或配置对齐。 - 【方案C】架构级优化（Long-term）： 如果是设计缺陷，提出架构调整建议（例如：引入GPU over-provisioning策略或调整缓存机制）。 ## 4. 验证与基准对齐 (Validation) - 验证方法： 提供具体的监控指令或脚本（如：nvidia-smi dmon、ib_write_bw、自定义 Prometheus 查询语句）。 - 预期指标： 修复后应当达到的理想数值（参考行业标准）。 ## 5. 风险预警与注意事项 (Precaution) - 潜在副作用： 实施方案可能带来的次生风险（如：内存压力增大、冷启动时间延长）。 - 专业沟通话术： 建议如何以“共情且专业”的角度向客户解释，强调这是“极端场景下的技术挑战”而非“产品缺陷”，展示技术兜底能力。 【严格约束条件】 1. 禁语： 严禁使用 Emoji。严禁使用“首先、其次、综上所述”等低效率连接词。 2. 标注： 所有非公开数据的判断必须加注 [推演]。 3. 诚实： 搜索不到的信息必须标注 [信息缺失，需现场复现/抓包]，严禁幻觉。 4. 排版： 使用 Markdown 的 ## 和 ### 进行层级管理，利用列表提高可读性。


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: xejrax/geo-ip (version 1.0.0)

--- name: geo-ip description: "Look up geographic location for any IP address" metadata: { "openclaw": { "emoji": "🌍", "requires": { "bins": ["curl"] }, "install": [], }, } --- # Geo IP Look up the geographic location for any IP address using the ipinfo.io API. Returns city, region, country, coordinates, and ISP information. ## Commands ```bash # Look up location for a specific IP address geo-ip <ip-address> # Look up your own public IP location geo-ip me ``` ## Install No installation needed. `curl` is always present on the system. Uses the public ipinfo.io API.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: runapi-ai/runapi-infinitetalk (version 0.2.4)

--- name: infinitetalk description: Generate and edit video with InfiniteTalk through RunAPI. Use when the user asks an agent to create, edit, or transform video with InfiniteTalk. Default to the RunAPI CLI for one-off generation; use SDKs only when the user is integrating RunAPI into an app or backend. documentation: https://runapi.ai/models/infinitetalk.md provider_page: https://runapi.ai/providers/meigen-ai.md catalog: https://runapi.ai/models.md metadata: openclaw: homepage: https://runapi.ai/models/infinitetalk requires: bins: - runapi install: - kind: brew formula: runapi-ai/tap/runapi bins: - runapi envVars: - name: RUNAPI_API_KEY required: false description: Optional RunAPI API key; runapi login or saved CLI config can also authenticate the runapi binary. --- # InfiniteTalk on RunAPI Generate and edit video with InfiniteTalk through RunAPI. The default path for one-off agent tasks is the `runapi` CLI; SDKs are for application integration. ## Routing decision - One-off generation, editing, or transformation for the user → use the **CLI path** with the `runapi` binary. - Building an app, backend, worker, library, or production codebase → use the **SDK integration path**. ## CLI path The `runapi` binary is the runtime dependency. Authenticate with `runapi login` (browser) or set `RUNAPI_API_KEY`; a saved CLI config also works — no required environment variable. Inspect the available actions and request fields with CLI help: ```shell runapi infinitetalk --help runapi infinitetalk audio-to-video --help ``` Run a one-off task (synchronous — polls until the task completes): ```shell runapi infinitetalk audio-to-video --input-file request.json ``` Submit asynchronously and poll separately: ```shell runapi infinitetalk audio-to-video --async --input-file request.json runapi wait <task-id> --service infinitetalk --action audio-to-video ``` Available actions: `audio-to-video`. ## SDK integration path When integrating InfiniteTalk into an app, backend, worker, or library — not for one-off tasks — use a RunAPI SDK package: - JavaScript / TypeScript: `@runapi.ai/infinitetalk` - Ruby: `runapi-infinitetalk` - Go: `github.com/runapi-ai/infinitetalk-sdk/go` ## References - Model overview, pricing, and rate limits: https://runapi.ai/models/infinitetalk.md - Provider comparison: https://runapi.ai/providers/meigen-ai.md - Full model catalog: https://runapi.ai/models.md


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