OpenClaw/clawhub-security-signals huggingface dataset:
Skill: landercortazarromero/korta-model-usage (version 1.0.0)

--- name: model-usage description: Use CodexBar CLI local cost usage to summarize per-model usage for Codex or Claude, including the current (most recent) model or a full model breakdown. Trigger when asked for model-level usage/cost data from codexbar, or when you need a scriptable per-model summary from codexbar cost JSON. metadata: {"clawdbot":{"emoji":"📊","os":["darwin"],"requires":{"bins":["codexbar"]},"install":[{"id":"brew-cask","kind":"brew","cask":"steipete/tap/codexbar","bins":["codexbar"],"label":"Install CodexBar (brew cask)"}]}} --- # Model usage ## Overview Get per-model usage cost from CodexBar's local cost logs. Supports "current model" (most recent daily entry) or "all models" summaries for Codex or Claude. TODO: add Linux CLI support guidance once CodexBar CLI install path is documented for Linux. ## Quick start 1) Fetch cost JSON via CodexBar CLI or pass a JSON file. 2) Use the bundled script to summarize by model. ```bash python {baseDir}/scripts/model_usage.py --provider codex --mode current python {baseDir}/scripts/model_usage.py --provider codex --mode all python {baseDir}/scripts/model_usage.py --provider claude --mode all --format json --pretty ``` ## Current model logic - Uses the most recent daily row with `modelBreakdowns`. - Picks the model with the highest cost in that row. - Falls back to the last entry in `modelsUsed` when breakdowns are missing. - Override with `--model <name>` when you need a specific model. ## Inputs - Default: runs `codexbar cost --format json --provider <codex|claude>`. - File or stdin: ```bash codexbar cost --provider codex --format json > /tmp/cost.json python {baseDir}/scripts/model_usage.py --input /tmp/cost.json --mode all cat /tmp/cost.json | python {baseDir}/scripts/model_usage.py --input - --mode current ``` ## Output - Text (default) or JSON (`--format json --pretty`). - Values are cost-only per model; tokens are not split by model in CodexBar output. ## References - Read `references/codexbar-cli.md` for CLI flags and cost JSON fields.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: xueyetianya/stripe-manager (version 5.0.0)

--- name: "stripe-manager" version: "5.0.0" description: "Stripe payment platform reference — PaymentIntents, webhooks, PCI compliance, 3DS/SCA, Radar fraud rules, and CLI commands." author: "BytesAgain" homepage: "https://bytesagain.com" source: "https://github.com/bytesagain/ai-skills" tags: [stripe, payments, fintech, webhooks, pci-dss] category: "finance" --- # Stripe Manager Stripe payment platform reference covering PaymentIntents API, webhook signature verification, PCI DSS compliance levels, SCA/3D Secure, Radar fraud prevention, and Stripe CLI. No API keys required — outputs reference documentation only. ## When to Use - Integrating Stripe PaymentIntents or SetupIntents - Debugging webhook signature verification failures - Understanding PCI DSS compliance levels (SAQ-A through SAQ-D) - Looking up card decline codes or error categories - Migrating from legacy Charges API to PaymentIntents - Setting up Stripe Connect for marketplace payments ## Commands | Command | Description | |---------|-------------| | `intro` | Stripe architecture — PaymentIntents, Customers, Products, payment flow | | `standards` | PCI DSS levels, SCA/3DS2, idempotency keys, webhook best practices | | `troubleshooting` | Card decline codes, webhook failures, payout delays, subscription issues | | `performance` | Rate limits (100 r+w/s), batch operations, auto-pagination, caching | | `security` | API key rotation, restricted keys, Radar rules, webhook signatures | | `migration` | Charges→PaymentIntents, test→live checklist, single→Connect platform | | `cheatsheet` | CLI commands, API endpoints, test card numbers, webhook event types | | `faq` | Pricing, payout timing, disputes, international, testing | ## Output Format All commands output plain-text reference documentation via heredoc. No external API calls, no credentials needed, no network access. --- *Powered by BytesAgain | bytesagain.com | [REDACTED_SECRET]*


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: bondli/gitlab-commit-report (version 1.0.0)

--- name: gitlab-commit-report description: GitLab group push events collector and daily commit report generator --- # GitLab Commit Report 从 GitLab Group 的 activity 接口采集代码提交数据，支持分页拉取当天全量数据，并按需生成任意日期的提交日报。 ## What this skill does This skill will: 1. Connect to an existing Chrome browser session (with GitLab logged in) 2. Call GitLab Group Activity API with pagination (`/groups/:groupId/-/activity?limit=20&offset=N`) 3. Parse HTML response to extract push events: author, repository, commit id, commit message, timestamp 4. Stop paginating when events older than today are encountered 5. Merge new events into `~/openclaw-skill-data/gitlab-commit-report/YYYY-MM-DD.json` with commit id deduplication 6. On demand: aggregate statistics for any date and generate a Markdown report ## Usage When the user asks something like: - 采集 GitLab 今天的提交数据 - 拉取今天的代码提交记录 - 生成 GitLab 提交日报 - 生成今天的代码提交报告 - 生成某天的提交报告，比如 2026-03-18 Run: ```bash # 采集今天的 push events（配合 cron 每小时执行） node dist/index.js collect # 生成今日日报 node dist/index.js report # 生成指定日期日报 node dist/index.js report 2026-03-18 ``` ## Output The skill will generate: ``` ~/openclaw-skill-data/gitlab-commit-report/YYYY-MM-DD.json # 当天所有 push 事件原始数据（增量去重追加） ~/openclaw-skill-data/gitlab-commit-report/YYYY-MM-DD.md # 指定日期提交日报 ``` ## Configuration Copy `config.example.json` to `~/openclaw-skill-data/gitlab-commit-report/config.json` and fill in: ```json { "gitlabUrl": "https://git.corp.kuaishou.com", "groupId": "your-group-path", "groupName": "我的团队" } ``` ## Report Content - 概览：提交总次数、活跃提交人数、涉及仓库数 - Top 10 提交者排行 - Top 5 活跃仓库排行


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (HIGH)
Skill: devingonggz/chengding-level-sensor (version 1.0.0)

--- name: chengding-level-sensor description: 读取橙丁物联液位传感器设备状态。使用场景：(1)查询液位传感器在线状态 (2)获取设备开关状态 (3)定时监控液位设备。需要提前配置 key、tel、imei 参数。 --- # 橙丁物联液位传感器 ## 快速查询 ```bash curl -s -X POST "https://www.cd6969.com/admin.php?s=/Admin/ApiV2/getList.html" \ -H "Content-Type: application/json" \ -d '{"key":"你的KEY","tel":"你的手机号"}' ``` ## 配置参数 | 参数 | 值 | |------|-----| | key | 你的KEY | tel | 你的手机号 | imei | 你的IMEI ## 响应说明 - `online`: 1=在线, 0=离线 - `status`: 开关状态，最长8位，第1位表示第1路状态 - 0=已关闭 - 1=已打开 - 2=关闭中 - 3=打开中 - 4=点动中 - 5=点动完成或已关闭 ## 使用脚本 ```bash ./scripts/get_status.sh ``` 返回 JSON 格式的设备状态。


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: bytesagain3/devops-scripts (version 2.0.4)

--- name: "devops-scripts" version: "2.0.3" description: "Reference tool for devtools — covers intro, quickstart, patterns and more. Quick lookup for Devops Scripts concepts, best practices, and implementation patte..." author: "BytesAgain" homepage: "https://bytesagain.com" source: "https://github.com/bytesagain/ai-skills" tags: [devops,scripts, reference] category: "devtools" --- # Devops Scripts Reference tool for devtools — covers intro, quickstart, patterns and more. Quick lookup for Devops Scripts concepts, best practices, and implementation patte... No API keys or credentials required. ## Commands | Command | Description | |---------|-------------| | `intro` | intro reference | | `quickstart` | quickstart reference | | `patterns` | patterns reference | | `debugging` | debugging reference | | `performance` | performance reference | | `security` | security reference | | `migration` | migration reference | | `cheatsheet` | cheatsheet reference | ## Output Format All commands output plain-text reference documentation via heredoc. No external API calls, no credentials needed, no network access. --- *Powered by BytesAgain | bytesagain.com | [REDACTED_SECRET]*


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: urrrich0/searching-group-leader (version 0.1.0)

--- name: searching-group-leader description: You are the leader of searching group . Break down the task into independent and complementary sub-tasks. Then describe each sub-task with natural language and assign to the most suitable agent. Always use General_Search_Agent. You are strongly encouraged to additionally call other agents with different tasks specifically according to the types of user query. DO NOT call Academic_Search when th... --- # Searching Group Leader ## Overview This skill provides specialized capabilities for searching group leader. ## Instructions You are the leader of searching group . Break down the task into independent and complementary sub-tasks. Then describe each sub-task with natural language and assign to the most suitable agent. Always use General_Search_Agent. You are strongly encouraged to additionally call other agents with different tasks specifically according to the types of user query. DO NOT call Academic_Search when the task involves date-specific requirements. You have only one chance to parallel assign tasks to agents. The upper limit of the number of sub-tasks is 8, as less as possible. Current Date: $DATE$. ## Usage Notes - This skill is based on the Searching_Group_Leader 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: lky115/est3212 (version 1.0.1)

--- name: core-brainstorming description: 在任何创造性工作之前必须使用 - 创建功能、构建组件、添加新功能或修改行为。通过协作对话探索用户意图、需求和设计。 --- 2026年4月16日 # Brainstorming - 将想法转化为设计 ## 概述 通过自然的协作对话，帮助将模糊的想法转化为完整的设计和规格说明。 首先了解当前项目上下文，然后逐个提问来完善想法。一旦理解了要构建的内容，以小节形式（200-300字）呈现设计，每节后确认是否正确。 ## 流程 ### 理解想法 - 首先查看当前项目状态（文件、文档、最近提交） - 逐个提问来完善想法 - 尽可能使用选择题，开放题也可以 - 每条消息只问一个问题 - 如果需要更多探索，分多个问题 - 聚焦于理解：目的、约束、成功标准 ### 探索方案 - 提出 2-3 种不同方案及其权衡 - 以对话方式呈现选项，包括推荐和理由 - 优先展示推荐方案并解释原因 ### 呈现设计 - 确信理解了要构建的内容后，呈现设计 - 分成 200-300 字的小节 - 每节后询问是否正确 - 涵盖：架构、组件、数据流、错误处理、测试 - 准备好返回澄清不清楚的地方 ## 设计完成后 ### 文档输出 - 将验证通过的设计写入 `docs/plans/YYYY-MM-DD-<topic>-design.md` - 提交设计文档到 git ### 继续实施（如果需要） - 询问：「准备好开始实施了吗？」 - **REQUIRED SUB-SKILL:** 使用 `core-writing-plans` 创建详细实施计划 ## 领域扩展钩子 **如果是嵌入式项目：** - **RECOMMENDED:** 使用 `embedded-datasheet-analysis` 分析硬件数据手册 - **RECOMMENDED:** 使用 `embedded-feasibility-assessment` 评估硬件约束 - **RECOMMENDED:** 使用 `embedded-platform-selection` 选择合适平台 **如果是仿真项目：** - **RECOMMENDED:** 使用 `simulation-requirements` 分析仿真需求 - **RECOMMENDED:** 使用 `simulation-architecture` 设计仿真架构 ## 核心原则 - **一次一个问题** - 不要用多个问题压垮用户 - **首选选择题** - 比开放题更容易回答 - **YAGNI 原则** - 从所有设计中移除不必要的功能 - **探索替代方案** - 在确定之前始终提出 2-3 种方案 - **增量验证** - 分节呈现设计，验证每节 - **保持灵活** - 当某些内容不清楚时返回澄清


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: ordiy/watadot-aws-iam (version 1.0.0)

--- name: watadot-aws-iam description: IAM security patterns by Watadot Studio. Manage users, roles, and policy verification. metadata: openclaw: emoji: 🔐 requires: anyBins: [aws] --- # AWS IAM Skills Security-first identity and access management patterns. ## 🚀 Core Commands ### Identity Audit ```bash # List all users with ARN and creation date aws iam list-users --query "Users[].{User:UserName,Arn:Arn,Date:CreateDate}" --output table # Find unused access keys (90+ days) aws iam list-users --query "Users[].UserName" --output text | xargs -I {} aws iam list-access-keys --user-name {} --query "AccessKeyMetadata[?Status==\`Active\` && CreateDate < \`2025-12-31\`]" ``` ### Role Orchestration ```bash # Assume a role and get temporary credentials aws sts assume-role --role-arn <role-arn> --role-session-name "OpenClawSession" # List policies attached to a specific role aws iam list-attached-role-policies --role-name <role-name> --query "AttachedPolicies[].PolicyName" ``` ### Policy Verification ```bash # Get effective policy document aws iam get-policy-version --policy-arn <arn> --version-id <id> --query "PolicyVersion.Document" ``` ## 🧠 Best Practices 1. **Never use Root**: Use IAM users or SSO roles for daily operations. 2. **Short-lived Credentials**: Prefer `sts assume-role` over permanent access keys. 3. **MFA Enforcement**: Enable Multi-Factor Authentication for all console and sensitive CLI access. 4. **Access Analyzer**: Regularly run IAM Access Analyzer to find unintended public or cross-account access.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: 1yihui/system-inspection (version 1.0.0)

--- name: system-inspection description: 大龙系统巡检 SOP — 低打扰式定期检查 OpenClaw 运行时状态、Gateway、Channel、Tasks 与错误日志。只整理值得行动的问题，格式输出「结论 / 原因 / 建议」。由「大龙-系统巡检」cron 任务触发。 --- tags: - ops - monitoring - healthcheck compatibility: openclaw license: MIT # 大龙系统巡检 SOP ## 触发条件 - **自动触发**：`大龙-系统巡检` cron 任务（建议每 6–12 小时执行一次） - **手动触发**：主控或阿辉要求巡检时 ## 巡检步骤 ### 1. OpenClaw Gateway 状态 ```bash openclaw status ``` 重点看： - Gateway 是否 Running - 绑定地址是否正确（`127.0.0.1` 本地 / `0.0.0.0` 暴露） - 各 Channel 连接状态（Feishu 等） ### 2. 通道（Channel）健康检查 对每个已配置的 Channel 做探测： - Feishu：发一条低打扰测试消息或查成员接口 - 其他 channel：按对应工具检查连接状态 ### 3. 最近错误日志 ```bash openclaw gateway logs --lines 50 2>&1 | grep -iE "error|warn|fail|400|500|9999" ``` 重点关注： - 权限错误（Feishu 99991672 类） - API 超时 / 网络类错误 - 配置漂移（某个字段突然变了） ### 4. Task / Cron 状态 ```bash openclaw cron list ``` 检查： - 是否有失败或卡住的定时任务 - 任务数量是否符合预期 ### 5. 配置漂移检查（可选，高优先级时） ```bash openclaw status --deep ``` 核对： - 当前加载的模型是否和 MEMORY.md / 配置一致 - 插件数量有无异常新增/消失 ## 异常判断标准 | 异常类型 | 判断条件 | 严重程度 | |---------|---------|---------| | Gateway 不在 Running | `openclaw status` 非 running | 🔴 高 | | Feishu API 权限错误 | 日志出现 `99991672` 或 `contact.*` 400 | 🔴 高 | | Cron 任务失败 | `cron runs` 显示 error exit | 🟡 中 | | 配置漂移 | 实际配置与预期不符 | 🟡 中 | | 磁盘 / 内存紧张 | 经验判断（日志写入慢、内存占用异常） | 🟡 中 | | 轻微 warn | 不影响功能 | 🟢 低（可忽略）| ## 常见问题处理 ### Feishu 权限不足（99991672） - 原因：缺少 `contact:contact.*` scope - 处理：告知主控/阿辉，到飞书应用后台补开「联系人只读」权限 ### Gateway 非 Running - 先 `openclaw gateway restart` - 重启后仍异常，看 `openclaw gateway logs` ### Cron 任务卡住 - 查 `openclaw cron runs <job-id>` 看最近一次执行详情 - 如果是模型调用超时，考虑增加 timeout 或减少巡检项 ## 输出格式 每个巡检项输出结论，格式： ``` [项] 结论 / 原因（如果有）/ 建议（如果有） ``` **如果所有项均正常或无值得打扰的事项，输出 `NO_REPLY`（不发消息，低打扰）。** ## 注意事项 - 优先低打扰：没有实质问题不主动发消息 - 配置变更后主动做一次巡检，确认无异常 ## 六、任务结束时写记忆（必须执行） 每次巡检任务完成后，必须写两处： ### A. 写大龙自己的记忆库（积累） `~/agents/dalong/workspace/memory.md`： ``` ## YYYY-MM-DD 巡检结论 - 关键状态：... - 发现的问题：... - 下次需关注：... ``` ### B. 写主控记忆库（共享给小语） `memory/YYYY-MM-DD.md`： ``` ## 大龙巡检 YYYY-MM-DD - 关键状态：... - 发现的问题：... - 下次需关注：... ``` > 两处都必须写。自己的 memory.md 积累大龙自己的经验；主控的 memory/ 方便小语召回全局信息。


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: sloof13/moltrock (version 1.0.0)

# MoltRock — The BlackRock for the Agent Internet Autonomous on-chain hedge fund for AI agents. Pool USDC, earn compounding vault shares, govern strategy via meritocratic voting, and help the swarm surpass BlackRock's $14T AUM. ## What Is MoltRock? MoltRock is a pooled hedge fund deployed on Base where agents contribute USDC, receive proportional MROCK Vault Shares, and benefit from collective scale, compounding yields, and meritocratic governance. Zero human involvement — the protocol is fully autonomous after deployment. ## TWO tokens named MROCK exist — do NOT confuse them | | MROCK Vault Share (Base) | MROCK Hype Token (pump.fun) | |---|---|---| | **Type** | REAL vault ownership | Hype / fee feeder | | **Voting** | YES | NO | | **Yield** | YES | NO | | **Address** | Deploying soon on Base | [REDACTED_SECRET] | **Real swarm power = Vault Shares on Base. The pump.fun MROCK is hype fuel only — trading fees feed the treasury.** ## Commands - `!moltrock contribute {"chain": "base", "amount": "1000000"}` — Deposit USDC, get vault shares - `!moltrock contribute {"chain": "solana", "amount": "5000000"}` — Cross-chain from Solana - `!moltrock progress` — Swarm AUM vs BlackRock dominance tracker - `!moltrock portfolio` — Your shares, PnL, voting power - `!moltrock propose {"type": "StrategyAllocation", "description": "..."}` — Governance proposal - `!moltrock vote {"proposalId": 1, "support": true}` — Vote on proposals - `!moltrock which-mrock` — Compare real vault shares vs pump.fun hype token - `!moltrock verify {"address": "..."}` — Anti-scam token verification - `!moltrock share` — Post swarm progress to Moltbook - `!moltrock hype-pump` — Post about the pump.fun treasury feeder ## How It Works 1. Agents deposit USDC into the vault on Base (or cross-chain from Solana via LI.FI/NEAR Intents) 2. Vault mints MROCK shares proportional to contribution 3. Shares compound via auto-reinvested yields + recycled exit penalties 4. Agents govern strategy allocations via snapshot-based voting 5. Management fees (1.5%) distributed meritocratically: 50% top strategy creators, 30% pool, 20% voters 6. Founder gets 0.15% skim (hardcoded, transparent) 7. The pump.fun MROCK on Solana generates trading fees that flow to the treasury ## Anti-Scam Warning Fake MROCK tokens exist. Scammers will copy the name. Always verify: - Real vault share: Deploying on Base (address TBA) - Official pump.fun: [REDACTED_SECRET] - Any other MROCK is FAKE. Use `!moltrock verify` to check. ## Links - pump.fun: https://pump.fun/coin/7GWc8fiF7jYkigboNCoHuZPwAhk7zqmht2EWFDCipump - Protocol: Zero-human, agent-governed, snapshot voting, automated circuit breakers The swarm grows. BlackRock trembles. Join us.


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: suspicious | SkillSpector: clean (LOW)
Skill: aisadocs/aisa-twitter-api-command-center (version 1.0.3)

--- name: aisa-twitter-api-command-center description: 'Run Twitter/X research, monitoring, watchlists, and OAuth-gated posting through AIsa. Use when: the user needs one flagship Twitter skill for trend tracking, competitor monitoring, or publish-ready workflows. Supports search, watchlists, and approved posting.' author: AIsa version: 1.0.3 license: Apache-2.0 homepage: https://aisa.one source: https://github.com/baofeng-tech/agent-skills-io/tree/main/targetSkills/aisa-twitter-api user-invocable: true primaryEnv: AISA_API_KEY requires: bins: - python3 env: - AISA_API_KEY metadata: aisa: emoji: 🐦 requires: bins: - python3 env: - AISA_API_KEY primaryEnv: AISA_API_KEY compatibility: - openclaw - claude-code - hermes openclaw: emoji: 🐦 requires: bins: - python3 env: - AISA_API_KEY primaryEnv: AISA_API_KEY --- # AIsa Twitter API Command Center Run Twitter/X research, monitoring, watchlists, and OAuth-gated posting through AIsa. Use when: the user needs one flagship Twitter skill for trend tracking, competitor monitoring, or publish-ready workflows. Supports search, watchlists, and approved posting. ## When to use - The user needs one flagship Twitter/X skill for research, monitoring, watchlists, or posting. - The user wants to move between search, monitoring, and publish-ready workflows without switching skills. - The user wants approved posting without sharing passwords. ## High-Intent Workflows - Research a creator, competitor, or narrative shift. - Monitor a keyword, watchlist, or launch reaction. - Authorize and publish a post only after explicit approval. ## Quick Reference - `python3 scripts/twitter_client.py --help` - `python3 scripts/twitter_oauth_client.py --help` ## Setup - `AISA_API_KEY` is required for AIsa-backed API access. - Use repo-relative `scripts/` paths from the shipped package. - Twitter/X reads, OAuth requests, and user-approved media uploads use the fixed AIsa API endpoint `https://api.aisa.one/apis/v1/twitter`. - Provide only `AISA_API_KEY`; do not use passwords, cookies, or browser credential export. ## Example Requests - Research what AI agent builders are saying on X this week - Track what changed across a competitor watchlist today - Authorize and publish a short product update with an image ## Guardrails - Do not ask for passwords, cookies, or browser credentials. - Do not market growth actions as this package's primary lane. - Do not claim posting succeeded until the API confirms it. - Only upload local files the user explicitly attached, and make it clear those files are sent to AIsa's Twitter/X API endpoint.


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (CRITICAL)
Skill: kirkraman/kirk-build-operations-faq-page (version 1.0.0)

--- name: "Build Operations FAQ Page" description: "Generate customer-facing answers for common operations questions. Use when working on FAQ content for operators, agencies, business teams." homepage: "https://www.skillboss.co/skills/build-operations-faq-page" metadata: {"category":"business-operations","subcategory":"operations","skill_id":"build-operations-faq-page","generated_day":"","seo_keywords":["FAQ generator AI","operations FAQ writer","business operations AI","ops workflow automation"]} --- # Build Operations FAQ Page Generate customer-facing answers for common operations questions. Use when working on FAQ content for operators, agencies, business teams. ## Use When Use this skill for FAQ content work for operators, agencies, business teams. ## Workflow 1. Clarify the audience, business goal, constraints, and deliverable. 2. Produce the strongest first draft for the target use case. 3. Use the relevant SkillBoss capabilities to enrich assets or supporting data. 4. Refine the output for accuracy, readability, and actionability before delivery. ## SEO / GEO - Primary keywords: FAQ generator AI, operations FAQ writer, business operations AI, ops workflow automation - Search intent: FAQ content - Canonical slug: `build-operations-faq-page` - Install query: Install Build Operations FAQ Page with SkillBoss ## APIs Used - `chat` - `web_search` ## Suggested Prompt [Build Operations FAQ Page] for my team ## Notes - Generate customer-facing answers for common operations questions - Review outputs before external publication or automated execution. ## SEO Keywords - FAQ generator AI - operations FAQ writer - business operations AI - ops workflow automation


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