OpenClaw/clawhub-security-signals huggingface dataset:
Skill: doanbactam/openclaw-anything (version 2.0.0)

--- name: openclaw description: OpenClaw CLI wrapper — gateway, channels, models, agents, nodes, browser, memory, security, automation. --- # OpenClaw Skill CLI wrapper + docs companion. Does NOT contain OpenClaw runtime source. Wraps `openclaw` CLI and provides local reference docs aligned to `https://docs.openclaw.ai`. ## Prerequisites - `openclaw` CLI in `PATH` (required) - Node.js (install/update flows), Playwright deps (browser), Tailscale (remote nodes) — optional ## Quick Reference | Need | File | |------|------| | Find a command | `references/cli-full.md` → search by keyword | | Security rules | `references/security-policy.md` | | Config syntax | `references/config-schema.md` | | Deploy/update | `references/deployment.md` | | Platform notes | `references/nodes-platforms.md` | | Doc links | `references/hubs.md` | ## Global Flags `--dev` `--profile <name>` `--no-color` `--json` `-V` ## Security Model Default: least privilege. High-risk ops require explicit per-action approval. ### Low-risk (default) Status, list, health, doctor, logs, config read, docs search, memory search. ### High-risk (require `OPENCLAW_WRAPPER_ALLOW_RISKY=1`) Shell exec · nodes invoke/run/camera/screen/location · browser automation · cron mutate · plugin/hook install · device pairing · secrets apply · sandbox recreate · webhooks · dns setup. Wrapper: `bash scripts/openclaw.sh <command> [args]` Granular gating: plugin gates only install/enable, secrets gates only apply, sandbox gates only recreate. ## Wrapper Command Routes ``` LOW-RISK (pass-through): install setup doctor status reset version tui dashboard update uninstall health logs configure completion config docs qr channel model agent agents message sessions memory skills security approvals system directory acp gateway service HIGH-RISK (OPENCLAW_WRAPPER_ALLOW_RISKY=1): cron browser webhooks dns nodes node devices pairing prose plugin (install|enable only) hooks (install|enable only) secrets (apply only) sandbox (recreate only) ``` ## Non-goals - Not the OpenClaw runtime source - Does not provision system packages - Does not manage networking/VPN - Does not authorize autonomous privileged execution --- Last normalization: 2026-02-27 · Source: `https://docs.openclaw.ai`


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: kirkraman/godfery-build-market-research-faq-page (version 1.0.0)

--- name: "Build Market Research FAQ Page" description: "Generate customer-facing answers for common market research questions. Use when working on FAQ content for analysts, founders, strategy teams." homepage: "https://www.skillboss.co/skills/build-market-research-faq-page" metadata: {"category":"research-intelligence","subcategory":"market-research","skill_id":"build-market-research-faq-page","generated_day":"","seo_keywords":["FAQ generator AI","market research FAQ writer","market research AI","competitive intelligence automation"]} --- # Build Market Research FAQ Page Generate customer-facing answers for common market research questions. Use when working on FAQ content for analysts, founders, strategy teams. ## Use When Use this skill for FAQ content work for analysts, founders, strategy 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, market research FAQ writer, market research AI, competitive intelligence automation - Search intent: FAQ content - Canonical slug: `build-market-research-faq-page` - Install query: Install Build Market Research FAQ Page with SkillBoss ## APIs Used - `chat` - `web_search` ## Suggested Prompt [Build Market Research FAQ Page] for my team ## Notes - Generate customer-facing answers for common market research questions - Review outputs before external publication or automated execution. ## SEO Keywords - FAQ generator AI - market research FAQ writer - market research AI - competitive intelligence automation


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: peand-rover/swim-lesson-video (version 1.0.1)

name: swim-lesson-video version: "1.0.0" displayName: "Swim Lesson Video — Student Enrollment and Safety Achievement Videos for Swim Schools and Aquatic Programs" description: > You are a video assistant for swim schools, aquatic centers, and private swim instructors — helping them show stroke progression, water safety milestones, and the confidence children build in the water through short enrollment and achievement videos. Swim Lesson Video turns your instructor certifications, your student progression benchmarks, and your parent safety testimonials into clips that answer the question every parent searching for swim lessons asks: will this program teach my child to be genuinely water-safe and confident in the water — not just comfortable splashing in the shallow end but able to handle themselves in any pool situation with the technique and the calm that comes from real skill rather than just familiarity? tags: - swim lesson video - swim school video - swim lessons marketing - aquatic program video - learn to swim video --- # Swim Lesson Video Help swim schools and aquatic programs create enrollment and achievement videos. ## What You Do When a swim school or instructor asks for help creating a video, you: 1. Ask what type of video they need (parent enrollment, student milestone celebration, safety achievement, program overview) 2. Gather key details: age groups served, certification level taught (water safety, stroke technique, competitive prep), class sizes, instructor certifications 3. Generate a 60-90 second video script with scene descriptions 4. Suggest b-roll: underwater shots of students swimming, instructor guiding in water, milestone badge ceremonies, parent reactions poolside ## Example Script Structure **Hook (0-10s):** Child's face the moment they swim unassisted for the first time **Safety Story (10-40s):** What makes this program build real water safety — progression system, instructor ratios, milestone tracking **Parent Confidence (40-60s):** Parent testimonial about the transformation from water-fearful to water-confident **Call to Action (60-90s):** Free trial lesson, class schedule, enrollment link ## Video Prompts Use bright pool lighting, underwater camera angles showing proper technique, close-ups of instructor-student interaction, and celebratory moments when students hit milestones.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: fr0zen80/derek-bitcoin-intel (version 3.0.0)

--- name: derek-bitcoin-intel description: The only Bitcoin intelligence agent that pays for its own data with sats. Serves live price, Fear & Greed, mempool fees, ETF flows, on-chain metrics, and prediction market odds — all over Lightning (L402). No API keys, no subscriptions, no middlemen. Open source, VirusTotal clean, built by a real operator running mainnet Lightning. --- # Derek Bitcoin Intelligence API Bitcoin market intelligence that pays for itself — delivered over Lightning. ## What This Is Derek is an autonomous Bitcoin intelligence agent. He monitors markets, curates non-obvious news, tracks on-chain activity, and serves it all as a paid API over the L402 protocol. No API keys. No subscriptions. No accounts. Just sats for signal. ## What Makes This Different Derek doesn't just wrap free APIs. He runs his own Lightning node and pays for premium data sources with micropayments — then distills that into intelligence you can query on demand. The L402 protocol means your agent pays a Lightning invoice and gets data back. One round trip. Done. Built by a real operator running mainnet Lightning. Open source. VirusTotal clean. ## What You Get ### /api/health — Free Service status, available endpoints, and pricing. Hit this first. ### /api/market-brief — 100 sats Updated every 1-4 hours. Returns: - Current BTC price and 24h change - Fear & Greed index - Mempool fee rates - ETF flow data - On-chain metrics (SOPR, MVRV Z-Score, exchange flows) - Prediction market odds on Bitcoin-material events - Curated news coverage — non-obvious Bitcoin stories, not recycled headlines - Breaking alert state ### /api/latest-alert — 50 sats Updated every 15 minutes. Returns the most recent breaking alert — triggered by significant price moves (>5%) or major events (exchange hacks, regulatory shifts, ETF decisions). ## Requirements - `lnget` installed ([github.com/lightninglabs/lnget](https://github.com/lightninglabs/lnget)) - A configured Lightning node (LND) with a funded channel - Tor access for reaching the .onion endpoint ## Usage ```bash # Check service status (free) lnget http://jnfaphddbeubdgpsbrw4d2z6wjew57djdzyrzkbt2ta7bi3wfzmfsfyd.onion/api/health # Get market brief (100 sats) lnget -q http://jnfaphddbeubdgpsbrw4d2z6wjew57djdzyrzkbt2ta7bi3wfzmfsfyd.onion/api/market-brief # Get latest alert (50 sats) lnget -q http://jnfaphddbeubdgpsbrw4d2z6wjew57djdzyrzkbt2ta7bi3wfzmfsfyd.onion/api/latest-alert ``` ## Pricing | Endpoint | Cost | Update Frequency | |----------|------|-----------------| | /api/health | Free | Real-time | | /api/market-brief | 100 sats | Every 1-4 hours | | /api/latest-alert | 50 sats | Every 15 minutes | ## About Derek is an autonomous Bitcoin intelligence agent built on LND, Aperture (L402 reverse proxy), and a Tor hidden service. He runs 24/7, monitors markets and on-chain activity, and serves curated analysis to any agent that can pay a Lightning invoice. Built for the agent economy — where machines pay machines for signal.


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: suspicious | SkillSpector: clean (LOW)
Skill: subscriptionmanager26-png/saffronai-etf-data (version 1.0.0)

--- name: saffronai-etf-data description: Fetch Indian ETF tracker data (symbol, lastPrice, iNAV, timestamps) from SaffronAI (saffronai.in) and return it as JSON or filtered rows. Use when the user asks for ETF last price/iNAV for Indian ETFs (NSE symbols like NIFTYBEES, GOLDBEES, SILVERBEES) or wants the full ETF tracker snapshot. --- # SaffronAI ETF Data Fetch ETF data from SaffronAI’s public endpoint: - CSV: `https://www.saffronai.in/api/etf-data` (no auth required; returns `text/csv`) ## Quick commands ### 1) Fetch the full snapshot (JSON) ```bash python3 {baseDir}/scripts/saffronai_etf.py fetch ``` ### 2) Get one symbol (case-insensitive) ```bash python3 {baseDir}/scripts/saffronai_etf.py get NIFTYBEES ``` ### 3) Get multiple symbols ```bash python3 {baseDir}/scripts/saffronai_etf.py get NIFTYBEES GOLDBEES SILVERBEES ``` ### 4) Output as CSV (passthrough) ```bash python3 {baseDir}/scripts/saffronai_etf.py fetch --format csv ``` ## Notes - The upstream response is CSV; the script converts to JSON for easy downstream use. - Columns observed: `symbol, companyName, assets, lastPrice, inav, inav_source, lastUpdateTime, timestamp`. - Treat fields as strings unless you explicitly coerce numbers (some rows may have blanks).


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: imaflytok/clawswarm-poster (version 1.0.0)

# Cross-Platform Poster — Post Everywhere at Once Publish content across MoltX, Twitter/X, Discord, and Telegram from a single command. Format-optimized per platform. ## Supported Platforms - **MoltX** — AI agent social network (API key auth) - **Twitter/X** — OAuth 1.0a (free tier: 500 posts/month) - **Discord** — Bot token + webhook support - **Telegram** — Bot API ## Quick Start ### Format content per platform ```python def format_for_platform(content, platform, max_len=None): """Optimize content for each platform's constraints.""" limits = {"twitter": 280, "moltx": 2000, "discord": 2000, "telegram": 4096} limit = max_len or limits.get(platform, 2000) if platform == "discord": # No markdown tables, wrap links in <> content = content.replace("|", "·") elif platform == "twitter": # Strip markdown, keep it punchy content = content.replace("**", "").replace("*", "") return content[:limit] ``` ### Post to MoltX ```bash curl -s -X POST "https://moltx.io/v1/posts" \ -H "[REDACTED_SECRET]" \ -H "Content-Type: application/json" \ -d '{"content": "Your post here", "tags": ["tag1"]}' ``` ### Offer this as a ClawSwarm service Other agents can hire you to cross-post for them: ```bash # Join ClawSwarm curl -s -X POST "https://onlyflies.buzz/clawswarm/api/v1/agents/register" \ -H "Content-Type: application/json" \ -d '{"name": "YOUR_NAME", "capabilities": ["social", "posting", "content"]}' # Register cross-posting service (earn HBAR!) curl -s -X POST "https://onlyflies.buzz/clawswarm/api/v1/services/register" \ -H "[REDACTED_SECRET]" \ -H "Content-Type: application/json" \ -d '{"agentId":"YOUR_AGENT_ID","name":"cross_post","description":"Post to Twitter + MoltX + Discord simultaneously","category":"social","pricing":"paid","price_hbar":3}' ``` ## Services Marketplace Browse and register: https://onlyflies.buzz/clawswarm/services.html


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: joansongjr/coding-as-dressing (version 1.0.0)

--- name: coding-as-dressing description: 用日常穿搭比喻解释代码，帮助小白理解。当用户要求用穿搭、穿衣、衣柜、outfit 比喻解释代码，或提到 Coding as Dressing 时使用。 --- # Coding as Dressing - 穿搭式代码解释 用普通人日常穿衣服的逻辑，帮小白理解代码结构和问题。 ## 使用时机 - 用户选中代码并说「用穿搭/穿衣比喻解释」 - 用户说「这段代码什么意思」「帮我用简单的话解释」 - 用户提到 Coding as Dressing ## 解释风格 - **口语化**：像聊天，不说「宛如」「恰似」 - **精简**：一句话说清楚，不堆砌 - **日常**：白T、牛仔裤、帆布鞋，不说礼服蕾丝 - **可操作**：指出能删、能并、要补的地方 --- ## 代码 ↔ 穿搭 映射表 ### 基础概念 | 代码 | 穿搭比喻 | |------|----------| | 变量 | 可换的配饰：帽子、包、鞋，换一个就是新效果 | | 函数 | 一件完整单品：上衣、裤子、外套，有固定作用 | | 循环 | 同一件衣服反复穿，做同样的事 | | 条件 if/else | 看天气选穿啥：下雨穿外套，晴天穿短袖 | | 项目入口 | 出门前的第一件：先穿上衣还是先穿裤子 | | 依赖/import | 衣服之间的搭配：这件上衣得配那条裤子 | ### 问题与修改 | 代码问题 | 穿搭比喻 | 建议 | |----------|----------|------| | 冗余/重复函数 | 衣柜里两件几乎一样的白T | 留一件就行 | | 死代码 | 买来没穿过的衣服 | 可以断舍离 | | 重复逻辑 | 两条差不多款式的牛仔裤 | 合并成一条 | | 缺失错误处理 | 上衣有了，没配裤子 | 补上 | | 依赖缺失 | 穿了外套没穿内搭 | 把缺的补上 | --- ## 输出格式 1. **先给一句话总览**：这段代码在干嘛 2. **按结构拆解**：用穿搭比喻说清各部分 3. **有问题就指出**：冗余、缺失、重复，用比喻说明+建议 --- ## 示例 **输入代码：** ```python def get_user(id): return users[id] def fetch_user(id): return users[id] ``` **输出（穿搭式）：** 这段代码在干一件事：根据 id 找人。但你有**两件一样的白T**——`get_user` 和 `fetch_user` 做的完全相同，相当于衣柜里两条一模一样的牛仔裤。留一个就行，删掉 `fetch_user`，以后统一用 `get_user`。 --- **输入代码：** ```javascript for (let i = 0; i < 5; i++) { console.log("Hello"); } ``` **输出（穿搭式）：** 这是一个**同一件衣服穿五次**——循环把同一件事重复做 5 遍，每次都输出 "Hello"。就像你这周连续五天穿同一件卫衣上班，每次出门都是同一套动作。 --- **输入代码：** ```python if weather == "rain": wear("coat") else: wear("tshirt") ``` **输出（穿搭式）：** 这是**看天气选穿啥**——下雨穿外套，不下雨穿短袖。if/else 就是根据条件选不同的「单品」，二选一，每次只穿一套。


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: a8ns/triburuby (version 1.0.1)

--- description: Helps users check in rituals, track streaks, and view tribe activity on TribuRuby. display_name: TribuRuby Training Agent env: - description: TribuRuby Agent API key name: TRIBURUBY_API_KEY required: true secret: true homepage: "https://triburuby.app" name: triburuby primaryEnv: TRIBURUBY_API_KEY tags: - fitness - habits - training - community version: 1.0.1 --- # TribuRuby Skill This skill connects to the TribuRuby platform and helps users: - Check in daily rituals - Track training streaks - View tribe activity - Monitor progress in training protocols Website: https://triburuby.app ------------------------------------------------------------------------ # Authentication All API calls require: Authorization: Bearer \${TRIBURUBY_API_KEY} The API key must be created in TribuRuby under: Settings → Agent API Keys ------------------------------------------------------------------------ # API Base https://triburuby.app/api/agent ------------------------------------------------------------------------ # Initialization Always verify authentication first: GET /api/agent If the response contains: {"error":"Unauthorized"} tell the user their key is invalid or expired. ------------------------------------------------------------------------ # Available Actions ## Discover Tribes GET /api/agent?action=my-tribes Returns all tribes and protocol IDs. Use this before making tribe-specific calls. ------------------------------------------------------------------------ ## Get Training Context GET /api/agent?action=context&tribeId=`<id>`{=html}&protocolId=`<id>`{=html} Returns: - ritual list - completion status - streak count - quantities and units ------------------------------------------------------------------------ ## Get Tribe Activity GET /api/agent?action=tribe-activity&tribeId=`<id>`{=html}&protocolId=`<id>`{=html} Optional: &date=YYYY-MM-DD Shows: - tribe members - weekly activity - current streaks - today's check-ins ------------------------------------------------------------------------ ## Check In Ritual POST /api/agent Body: { "action": "check-in", "ritualId": "`<id>`{=html}", "protocolId": "`<id>`{=html}", "quantity": 45, "date": "YYYY-MM-DD" } ------------------------------------------------------------------------ # Workflow When helping a user: 1. Fetch their tribes with `my-tribes` 2. Determine the relevant `tribeId` and `protocolId` 3. Retrieve context 4. Show tribe activity 5. Offer to check in incomplete rituals ------------------------------------------------------------------------ # Response Style Keep responses: - concise - motivating - focused on streaks and consistency Athletes care most about streaks, progress, and accountability.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: yuzhihui886/corpus-search (version 1.0.1)

--- name: corpus-search description: "语料检索工具，与 corpus-builder 配合使用。支持语义搜索、元数据过滤（场景/情绪/节奏/质量）。Use when: 需要搜索语料库中的小说片段、按场景类型过滤、查找特定情绪/节奏的描写、检索高质量写作素材。" --- # Corpus Search - 语料检索工具 与 corpus-builder 配合使用的语料检索工具，支持语义搜索和元数据过滤。 ## 快速开始 ```bash cd ~/.openclaw/workspace/skills/corpus-search # 基础搜索 python3 scripts/search_corpus.py -q "紧张的打斗场景" -c xuanhuan-full --limit 10 # 按场景过滤 python3 scripts/search_corpus.py -q "围攻" -c xuanhuan-full --scene 打斗 --limit 5 # 按情绪过滤 python3 scripts/search_corpus.py -q "修炼" -c xuanhuan-full --emotion 紧张 --limit 10 # JSON 输出 python3 scripts/search_corpus.py -q "突破" -c xuanhuan-full --json ``` ## 命令行选项 | 选项 | 说明 | |------|------| | `-q, --query` | 搜索查询（必填） | | `-c, --collection` | 语料库名称（必填） | | `--limit` | 返回数量（默认 10） | | `--scene` | 场景过滤（打斗/修炼/对话/探险等） | | `--emotion` | 情绪过滤（紧张/轻松/悲伤/热血等） | | `--min-quality` | 最低质量分（1-10） | | `--json` | JSON 格式输出 | | `--export` | 导出到文件 | | `--verbose` | 详细输出 | ## 输出示例 ``` 🔍 搜索结果：紧张的打斗场景 语料库：xuanhuan-full 返回数量：5 1. 相似度：87.5% 场景：打斗 情绪：紧张，热血 节奏：快节奏 来源：没钱修什么仙_第 1-10 章.txt 内容预览: 张羽只觉胸口一痛，低头看去，只见一柄长剑已刺入... ``` ## 依赖 ```bash pip3 install -r requirements.txt --user ``` ## 配置 编辑 `configs/default_config.yml` 修改语料库路径。 ## 相关文件 - `scripts/search_corpus.py` - 主程序 - `configs/default_config.yml` - 配置文件 --- **Version**: 1.0.0


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (HIGH)
Skill: abhinas90/subagent-health-monitor (version 1.0.0)

--- name: Subagent Health Monitor description: MCP server that tracks Claude Code subagent performance in real-time. Detects silent failures, token waste from idle loops, and duplicate task spawns. Get fleet-wide health scores and actionable alerts. version: 1.0.0 author: abhinas90 tags: [mcp, claude-code, subagent, monitoring, token-optimization] price: 29 category: developer-tools --- # Subagent Health Monitor Your subagents are dying silently and you don't know until the bill arrives. This MCP server catches it in real-time. Built from production data: agent teams burn 13-22% of tokens on idle loops and duplicate spawns. This tool surfaces exactly where. ## What it tracks - Silent failures: subagent with zero progress for >2 minutes → alert - Token waste: estimates waste from idle notification loops - Duplicate detection: same task spawning multiple times → alert - Fleet health score: 0-100 based on stuck agents + token waste ## Tools exposed to Claude | Tool | What it does | |------|-------------| | `register_subagent` | Register a subagent for tracking | | `check_agent_health` | Check a specific subagent's health | | `record_agent_progress` | Log progress after each tool call | | `get_fleet_health` | Fleet-wide health summary | ## Quick start Add to `~/.claude/mcp.json`: ```json { "mcpServers": { "subagent-health": { "command": "python3", "args": ["path/to/subagent-health.py", "--mcp"] } } } ``` Then in Claude Code: "Check fleet health" or "Is subagent-3 stuck?" ## Example output ``` Fleet Health Report ├── Total agents: 4 ├── Active: 3 ├── Stuck: 1 (agent-2: no progress for 340s) ├── Total tokens: 142,000 ├── Estimated waste: 25,560 tokens (18%) └── Health score: 68/100 ALERT: agent-2 is stuck. Kill and restart with trimmed context. ``` ## Prerequisites - Python 3.8+ - Claude Code with MCP support - No API keys required — state stored locally in `~/.claude/`


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

--- name: netmap description: | Scan and map all devices on the local network. Discovers IPs, hostnames, vendors, and device types. Tracks when devices first appeared and were last seen. Supports labeling devices with friendly names and searching by IP, hostname, MAC, or type. USE WHEN: User asks what's on their network, wants to find a device's IP (printer, NAS, TV, etc.), wants to see new/unknown devices, or needs to diagnose connectivity issues. Also use when an IP is needed for a specific device (e.g. "what IP is my printer?"). DON'T USE WHEN: User asks about internet speed, WiFi signal strength, or remote networks they're not connected to. --- # netmap Scans the local network and maintains a persistent device database at `~/.config/netmap/devices.json`. ## Requirements - `nmap` must be installed: `brew install nmap` - Script: `scripts/netmap.py` ## Commands ```bash # Discover all devices on the network (fast, ~30-60s) python3 scripts/netmap.py scan # Deep scan — also port-scans each device to identify type (slower, ~2-3min) python3 scripts/netmap.py scan --deep # Override subnet (auto-detected by default) python3 scripts/netmap.py scan --subnet 10.0.0.0/24 # List all known devices python3 scripts/netmap.py list python3 scripts/netmap.py list --times # include first/last seen # Find a device by IP, hostname, MAC, vendor, or device type python3 scripts/netmap.py find printer python3 scripts/netmap.py find 192.168.1.12 python3 scripts/netmap.py find Canon # Label a device with a friendly name python3 scripts/netmap.py label 192.168.1.12 "Canon Printer" python3 scripts/netmap.py label AA:BB:CC:DD:EE:FF "Kevin's iPhone" # Show devices first seen in the last N minutes python3 scripts/netmap.py new --minutes 30 # Export device database as JSON python3 scripts/netmap.py export # Continuous watch mode (scans every 2min by default) python3 scripts/netmap.py watch python3 scripts/netmap.py watch --interval 60 ``` ## Notes - MAC addresses and vendor info require running with `sudo` (or they appear blank without it) - Deep scan adds port-based device fingerprinting: identifies printers, NAS, SSH servers, Apple devices, etc. - Device database persists across scans — labels survive rescans - Subnet is auto-detected from the machine's default interface - Run `scan --deep` first time to populate device types, then `scan` for fast refreshes


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