OpenClaw/clawhub-security-signals huggingface dataset:
Skill: zhouzhi-tal/xueersi-word-story-memory (version 1.0.0)

--- name: xueersi-word-story-memory description: "Xueersi Word Story Memory: Turn English vocabulary into vivid Chinese mnemonics, phonetic stories, and visual scenes to help K-9 students memorize words fast and retain them longer. 学而思(Xueersi) 单词故事记忆法 — 把单词编成小故事帮助记忆。By Xueersi-AI." --- # Xueersi Word Story Memory · 学而思单词故事记忆法 > By **Xueersi (学而思)** · AI Education Tools ## Core Idea Transform a word's **pronunciation**, **spelling**, or **roots** into a vivid Chinese story or mental image — the weirder, the more memorable (cognitive science principle). ## Four Techniques ### 1. Phonetic Story (谐音故事) Use the Chinese sound-alike to build a story. Examples: - `elephant` /ˈelɪfənt/ → sounds like "哦你发疯了" → Picture an elephant suddenly going wild, people shouting "你发疯了！" - `ambulance` → sounds like "俺不能死" → An ambulance arrives; the patient shouts "I can't die!" ### 2. Root Decomposition (词根拆解) Break the word into meaningful parts. Examples: - `international` = inter (between) + national (of a country) → "between countries" = international - `impossible` = im (not) + possible → "not possible" ### 3. Visual Scene (画面联想) Create a striking visual image for the word. Examples: - `brave` → A warrior in a red cape standing on a cliff — the wind can't knock him down - `whisper` → Two kids hiding in a corner, hands cupped around mouths, sharing a secret ### 4. Sentence Scene (情景造句) Embed the word in an exaggerated, funny sentence. Example: - `enormous` → "That enormous cat sat on the fridge and crushed it flat!" ## Output Format ``` 🔤 Word: [word] /[IPA]/ 📖 Meaning: [Chinese definition] 🎭 Memory Story: [2-4 sentences — vivid, funny, or bizarre] 💡 Mnemonic Rhyme (if applicable): [Optional catchy phrase] 📝 Example Sentence: [Simple memorable sentence + Chinese translation] ``` ## Batch Mode - ≤ 5 words: process individually (more detail) - > 5 words: weave related words into one connected story (more efficient) Ask user preference before starting. ## Quick Review Quiz After delivering the story, test immediately: > "Now I say the Chinese meaning, you say the English word: '巨大的' is…?" Correct → praise + next word. Wrong → repeat the story + re-test. ## Notes - Stranger = more memorable (key principle!) - Elementary: cartoonish, child-friendly imagery - Never use inappropriate or scary associations


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: coolhackboy/hailuo2 (version 1.0.0)

--- name: poyo-hailuo-02 description: Use PoYo AI Hailuo 02 for prompt-optimized video generation and image-to-video workflows through the `https://api.poyo.ai/api/generate/submit` endpoint. Use when a user wants standard or pro video jobs, optional prompt optimization, end-frame control, or PoYo payloads for `hailuo-02` and `hailuo-02-pro`. metadata: {"openclaw": {"homepage": "https://docs.poyo.ai/api-manual/video-series/hailuo-02", "requires": {"bins": ["curl"], "env": ["POYO_API_KEY"]}, "primaryEnv": "POYO_API_KEY"}} --- # PoYo Hailuo 02 Video Generation Use this skill to submit and track PoYo jobs for the Hailuo 02 family. ## Quick workflow 1. Choose the right model id for the requested output. 2. Build the request body for `POST https://api.poyo.ai/api/generate/submit`. 3. Send Bearer-authenticated JSON with `Authorization: Bearer <POYO_API_KEY>`. 4. Save the returned `task_id`. 5. Poll unified task status or wait for `callback_url` notifications. ## Request rules - Require top-level `model`. - Keep prompts concrete and outcome-focused. - Require `input.prompt` unless the user already supplied a full payload. - Use `input.image_urls` only when the task needs reference or source images. - Use `input.duration` when the clip length matters. - Use `input.resolution` when quality/cost tradeoffs matter. ## Model selection ### `hailuo-02` Use for general generation with this model variant. ### `hailuo-02-pro` Use for higher-quality or premium jobs. ## Execution - Read `references/api.md` for endpoint details, model ids, key fields, example payloads, and polling notes. - Use `scripts/submit_hailuo_02.sh` to submit a raw JSON payload from the shell. - If the user only needs a curl example, adapt the example from `references/api.md` instead of rewriting from scratch. - After submission, report the `task_id` clearly so follow-up polling is easy. ## Output expectations When helping with this model family, include: - chosen model id - final payload or a concise parameter summary - whether reference images are involved - returned `task_id` if a request was actually submitted - next step: poll status or wait for webhook Notes: Needs POYO_API_KEY from https://poyo.ai PoYo.ai - Premium AI API Platform | Image, Video, Music & Chat APIs - 80% Cheaper


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: hyqdq888/fortune-china500-skill (version 1.0.1)

--- name: fortune-china500 description: "获取《财富》中国 500 强企业排行榜数据，支持查询不同年份的完整 500 强企业名单。自动判断榜单发布时间（每年 7 月），输出 Excel 文件包含排名、企业名称、行业、营收等数据。" license: MIT --- # 财富中国 500 强数据获取技能 ## 触发条件 当用户提到以下关键词时触发： - "财富中国 500 强" - "中国 500 强企业" - "财富 500 强排名" - "获取 500 强名单" - "查询 500 强企业" - "fortune china 500" ## 年份处理规则 ### 数据发布时间 - 财富中国 500 强榜单于**每年 7 月下旬**发布 - 例如：2025 年榜单于 2025 年 7 月 22 日发布 ### 年份判断逻辑 当前月份 < 7 月：最新可用数据是前年的 当前月份 >= 7 月：最新可用数据是去年的 如果用户请求的年份 > 最新可用年份，提示用户榜单尚未发布。 ## 使用方法 ### 基础用法 ``` 获取 2025 年财富中国 500 强名单 ``` ### 带参数用法 ``` 查询财富中国 500 强 2024 年前 100 强企业 ``` ### 历史数据 ``` 获取 2023 年中国 500 强企业名单 ``` ## 输出格式 返回 Excel 文件，包含以下字段： - **排名**：1-500 - **企业名称**：中文全称 - **行业分类**：所属行业类别 - **营业收入**：百万美元 - **数据源**：数据来源和获取时间 ## 注意事项 1. 每年 7 月前请求当年数据时，需提示用户榜单尚未发布 2. 自动从官方数据源获取数据 3. 返回的 Excel 文件需包含数据源说明和获取时间 4. 支持 2010 年之后的数据


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: ckchzh/git-toolkit (version 1.0.0)

--- name: git-toolkit description: "Git Extras — Git Extras — extended git utilities. Automated tool for git-extras tasks. Use when you need Git Extras capabilities." runtime: bash license: MIT --- # Git Extras Git Extras — extended git utilities ## Why This Skill? - Inspired by popular open-source projects (thousands of GitHub stars) - No installation required — works with standard system tools - Real functionality — runs actual commands, produces real output ## Commands Run `scripts/git_extras.sh <command>` to use. - `summary` — Repo summary (commits, authors, files) - `authors` — List all authors by commits - `changelog` — [since] Generate changelog - `effort` — [n] Files with most commits - `fresh-branch` — <n> Create branch from clean state - `ignore` — <pattern> Add to .gitignore - `undo` — [n] Undo last n commits (soft) - `standup` — [days] What did I do (default: 1 day) - `stats` — Detailed repo statistics - `info` — Version info ## Quick Start ```bash git_extras.sh help ``` --- > **Disclaimer**: This skill is an independent, original implementation. It is not affiliated with, endorsed by, or derived from the referenced open-source project. No code was copied. The reference is for context only. Powered by BytesAgain | bytesagain.com | [REDACTED_SECRET]


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: lean-zhouchao/agent-autonomy-kit-bak (version 1.0.0)

--- name: agent-autonomy-kit version: 1.0.0 description: Stop waiting for prompts. Keep working. homepage: https://github.com/itskai-dev/agent-autonomy-kit metadata: openclaw: emoji: "🚀" category: productivity --- # Agent Autonomy Kit Transform your agent from reactive to proactive. ## Quick Start 1. Create `tasks/QUEUE.md` with Ready/In Progress/Blocked/Done sections 2. Update `HEARTBEAT.md` to pull from queue and do work 3. Set up cron jobs for overnight work and daily reports 4. Watch work happen without prompting ## Key Concepts - **Task Queue** — Always have work ready - **Proactive Heartbeat** — Do work, don't just check - **Continuous Operation** — Work until limits hit See README.md for full documentation.

path: _meta.json
content: ownerId: kn76py1tc3spdqaw1mw9aaxs1580e64b
slug: agent-autonomy-kit
version: 1.0.0
publishedAt: 1770237821307

path: templates/HEARTBEAT.md
content: # Proactive Heartbeat

## 1. Quick Checks (30 seconds)

- [ ] Human messages waiting? → Handle immediately
- [ ] Critical blockers? → Escalate
- [ ] Team needs coordination? → Respond

If nothing urgent, proceed to work mode.

## 2. Work Mode (use your time)

1. Read `tasks/QUEUE.md`
2. Pick highest-priority Ready task you can do
3. Do meaningful work on it
4. Update the queue (move to Done or note progress)
5. If time/tokens remain, pick another task

## 3. Before Finishing

- [ ] Log what you did to `memory/YYYY-MM-DD.md`
- [ ] Update task queue with new tasks discovered
- [ ] Post update to team if significant

---

## Token Strategy

- Human requests: ALWAYS FIRST
- Urgent tasks: Time-sensitive items
- High-impact tasks: Move needles
- Maintenance: Improvements and cleanup

If approaching limits: wrap up, write handoff notes, sleep.

---

*Idle time = wasted tokens. Keep working.*


path: templates/QUEUE.md
content: # Task Queue

*Last updated: [timestamp]*

---

## 🔴 Ready (can be picked up)

### High Priority
- [ ] [Task description]

### Medium Priority
- [ ] [Task description]

### Low Priority
- [ ] [Task description]

---

## 🟡 In Progress

- [ ] @[agent]: [Task description]

---

## 🔵 Blocked

- [ ] [Task description] (needs: [what's blocking])

---

## ✅ Done Today

- [x] @[agent]: [Task description]

---

## 💡 Ideas (not yet tasks)

- [Idea that might become a task]

---

*Add tasks as you discover them. Pick from Ready when you have capacity.*


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (HIGH)
Skill: laolaoqi/linux-disk-doctor (version 1.1.0)

--- name: linux-disk-doctor description: Diagnose and fix Linux disk full / no space issues. Find large files, clean logs, purge package caches, remove old kernels, handle Docker disk bloat, and expand filesystems. Use when df -h shows space critically low, applications fail with "no space left on device", or docker builds fail with ENOSPC. --- # Linux Disk Doctor Free disk space fast. ## Quick Assessment ```bash df -h du -sh /* 2>/dev/null | sort -rh | head -20 ``` ## Cleanup Steps ```bash # Package cache apt-get clean && apt-get autoremove -y # Old kernels (keep current) dpkg --list | grep linux-image | awk '{print $2}' | grep -v $(uname -r) | xargs apt-get purge -y # Journal logs journalctl --vacuum-time=7d # Docker docker system prune -a -f # Temp files rm -rf /tmp/* # Find largest directories du -sh /var/log/* | sort -rh | head -10 ``` --- ## 📢 Need Help? Need OpenClaw deployed on your server? I offer managed deployment & hosting: - 📧 [REDACTED_SECRET] - 🏯 颐和园 OpenClaw 运维


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector:  ()
Skill: 5eun/kbo-results (version 1.0.0)

--- name: kbo-results description: Fetch KBO game schedules and results for a specific date with the kbo-game npm package. Use when the user asks for today's KBO games, yesterday's scores, or a date-specific scoreboard. license: MIT metadata: category: sports locale: ko-KR phase: v1 --- # KBO Results ## What this skill does `kbo-game` 패키지로 특정 날짜 KBO 경기 정보를 가져와 경기 일정, 스코어, 상태를 요약한다. ## When to use - "오늘 KBO 경기 결과 알려줘" - "어제 한화 경기 스코어 보여줘" - "2026-04-01 KBO 일정 정리해줘" ## Prerequisites - Node.js 18+ - `npm install -g kbo-game` ## Inputs - 날짜: `YYYY-MM-DD` - 선택 사항: 특정 팀명 ## Workflow ### 0. Install the package globally when missing `npm root -g` 아래에 `kbo-game` 이 없으면 다른 구현으로 우회하지 말고 전역 Node 패키지 설치를 먼저 시도한다. ```bash npm install -g kbo-game ``` 패키지가 없다는 이유로 다른 비공식 scoreboard 소스를 자동 채택하지 않는다. ### 1. Fetch the date ```bash GLOBAL_NPM_ROOT="$(npm root -g)" node --input-type=module - <<'JS' import path from "node:path"; import { pathToFileURL } from "node:url"; const entry = pathToFileURL( path.join(process.env.GLOBAL_NPM_ROOT, "kbo-game", "dist", "index.js"), ).href; const { getGame } = await import(entry); const date = "2026-03-25"; const games = await getGame(new Date(`${date}T00:00:00+09:00`)); console.log(JSON.stringify(games, null, 2)); JS ``` `kbo-game@0.0.2` 기준 실제 export는 `getGame` 하나이며, 문자열 날짜(`"2026-03-25"`)를 직접 넘기면 실패한다. 항상 `Date` 객체로 변환해서 호출한다. 전역 설치를 기본으로 쓰므로 inline snippet에서는 전역 npm root 아래 entry file을 직접 import 한다. ### 2. Normalize for humans 원본 데이터를 그대로 던지지 말고 아래 기준으로 정리한다. - 홈팀 vs 원정팀 - 진행 상태 또는 경기 종료 여부 - 스코어 - 필요한 경우 특정 팀만 필터링 ### 3. Keep the answer compact 사용자가 scoreboard를 원하면 경기별 한 줄 요약부터 준다. ## Done when - 날짜 기준 전체 경기 요약이 있다 - 팀 필터 요청이면 해당 팀 경기만 남아 있다 - raw JSON이 필요하면 별도로 제공할 수 있다 ## Failure modes - KBO 사이트 변경으로 패키지 응답이 깨질 수 있다 - 비시즌 날짜는 빈 결과가 올 수 있다 ## Notes - 이 스킬은 조회 전용이다 - 사용자 기준 "오늘/어제" 같은 상대 날짜는 항상 절대 날짜로 변환해서 실행한다


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: hollaugo/mcp-app-builder (version 0.1.0)

--- name: mcp-app-builder description: Build new MCP Apps (MCP servers with React UI output) using @modelcontextprotocol/ext-apps and the MCP SDK. Use when asked to scaffold or implement MCP App servers, add UI-rendering tools/resources, or migrate a standard MCP server to an MCP App with Vite single-file UI bundles. --- # MCP App Builder ## Overview Create MCP Apps that expose tools with visual React UIs for ChatGPT or Claude. Follow the exact dependency versions and server/UI patterns in `references/mcp-app-spec.md`. ## Workflow 1. Clarify requirements: what data to visualize, UI pattern (card, table, chart, dashboard, form), data source, and how many tools (start with 1-2). 2. Design tools and UI mapping: define tool names, zod input schemas, output shape, and UI resource URIs (`ui://.../app.html`). Map each tool to one React entrypoint and one HTML file. 3. Scaffold the project: start from `assets/mcp-app-template/` when possible, then customize tool names, schemas, and UI. Ensure `package.json` uses the exact versions, plus `tsconfig.json`, `vite.config.ts`, Tailwind + PostCSS, and per-tool build scripts. 4. Implement the server: use `registerAppTool`/`registerAppResource`, zod schemas directly, `createServer()` factory per request, and `createMcpExpressApp` with `app.all("/mcp", ...)`. 5. Implement the UI: use `useApp` + `useHostStyles`, parse tool results, handle loading/error/empty states, and apply safe-area insets. 6. Build and test: run `npm run build`, then `npm run serve`, then verify via a tunnel if needed. ## Hard Requirements - Use the exact dependency versions listed in `references/mcp-app-spec.md`. - Use `registerAppTool`/`registerAppResource` and zod schemas directly (not JSON Schema objects). - Create a new `McpServer` instance per request via `createServer()`. - Use `createMcpExpressApp` and `app.all("/mcp", ...)`. - Bundle UI into single-file HTML via `vite-plugin-singlefile`. - Use host CSS variables for theme compatibility. ## References - `references/mcp-app-spec.md` (authoritative spec, patterns, code templates, gotchas) ## Assets - `assets/mcp-app-template/` (ready-to-copy MCP App skeleton with one tool + UI)

path: assets/mcp-app-template/postcss.config.js
content: export default {
  plugins: {
    tailwindcss: {},
    autoprefixer: {},
  },
};


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: fuzzyb33s/content-multiplier-fuzzyb33s (version 1.0.0)

--- name: content-repurposer description: Repurpose a single piece of content (tweet, article, description) into 10+ formats: Twitter thread, LinkedIn post, blog intro, email newsletter, Discord announcement, Reddit post, Quora answer, Instagram caption, email subject lines, and meta descriptions. tools: - repurpose_content --- # Content Repurposer Repurpose any content into 10+ marketing formats instantly. ## Usage ```bash uv run python scripts/repurpose.py "Your content here" [--type auto] [--tone professional|casual|humorous] [--output ./output] ``` ## Arguments - `content` (required): The source content — a tweet, article text, product description, or any string. - `--type` (optional): Override auto-detection. Values: `tweet`, `article`, `description`, `speech`, `email`. - `--tone` (optional): Writing tone. Values: `professional` (default), `casual`, `humorous`, `inspirational`, `technical`. - `--output` (optional): Output directory for individual files. Defaults to `./output`. ## Output Formats | Format | Description | |--------|-------------| | **Twitter Thread** | 5-7 tweet thread with hook, points, CTA | | **LinkedIn Post** | Professional post with 3-5 key insights | | **Blog Intro** | 200-word engaging blog introduction | | **Email Newsletter** | Full newsletter paragraph with subject line | | **Discord Announcement** | Server-friendly announcement with emoji formatting | | **Reddit Post** | Title + body for relevant subreddit | | **Quora Answer** | Informative answer to a related question | | **Instagram Caption** | Engaging caption with hashtags | | **Email Subject Lines** | 5 compelling subject line variants | | **Meta Descriptions** | 3 SEO-optimized meta descriptions | ## Workflow 1. **Input**: Content is analyzed and classified 2. **Generation**: Each format is generated with platform-specific optimization 3. **Output**: All formats returned as structured JSON ## Error Handling All outputs return JSON with `success` field: - `success: true` — Operation completed, check `results` dict - `success: false` — Check `error_code` and `error_message` ## Notes - Uses MiniMax API via OpenClaw for generation - Rate limiting handled with exponential backoff - Empty content returns an error with code `EMPTY_CONTENT`


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: newageinvestments25-byte/changelog-watcher (version 1.0.0)

--- name: changelog-watcher description: Monitor GitHub repos and npm packages for new releases and version updates. Summarizes changelogs and highlights breaking changes. Use when the user asks to check for updates, find new releases, review changelogs, track version updates, or asks "what's new in X". Also use when asked to run or schedule a changelog check, set up release monitoring, or report on recent releases for any software package or GitHub repo. --- # Changelog Watcher Maintains a watchlist of GitHub repos and npm packages, detects new releases, and produces markdown reports with breaking changes highlighted. ## Files - `watchlist.json` — user config (create from `assets/watchlist.example.json`) - `state.json` — auto-managed last-seen versions (do not edit) - `scripts/compare_versions.py` — main entry point; calls the others - `scripts/check_github.py` — GitHub releases API - `scripts/check_npm.py` — npm registry - `scripts/format_report.py` — markdown report generator For setup, watchlist format, cron scheduling, and rate limit guidance → read `references/setup-guide.md`. ## Skill Directory ``` ~/.openclaw/workspace/skills/changelog-watcher/ ``` All script paths below are relative to this directory. ## Usage ### Check for new releases and print report ```bash python3 scripts/compare_versions.py --update-state | python3 scripts/format_report.py ``` ### Dry-run (check without advancing state) ```bash python3 scripts/compare_versions.py | python3 scripts/format_report.py ``` ### First-time setup (set baseline, no output) ```bash cp assets/watchlist.example.json watchlist.json # edit watchlist.json to your packages python3 scripts/compare_versions.py --update-state ``` ## Workflow 1. Confirm `watchlist.json` exists. If not, guide user to copy from `assets/watchlist.example.json` and fill it in. 2. Run `compare_versions.py` (with `--update-state` unless doing a dry-run). 3. Pipe output to `format_report.py`. 4. Present the markdown report to the user. 5. If the user wants to schedule this: provide the cron line from `references/setup-guide.md`. ## Adding Entries To add a GitHub repo: ```json {"source": "github", "owner": "OWNER", "repo": "REPO", "name": "Display Name"} ``` To add an npm package: ```json {"source": "npm", "package": "package-name", "name": "Display Name"} ``` Append to the `watch` array in `watchlist.json`, then run the full pipeline. ## Error Handling - **Rate limited (exit 2):** Wait for the retry window; check how many GitHub entries are in the watchlist vs the 60/hr limit. - **Not found (exit 3):** Verify the owner/repo or package name in the watchlist. - **Network error:** Check connectivity; retry. - **First-run shows zero releases:** Expected — first run sets the baseline only.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: sky-lv/skylv-code-reviewer (version 1.0.4)

--- name: code-reviewer description: Code review assistant. Analyzes code quality, detects bugs and security issues, and suggests improvements. Triggers: code review, security audit, code quality, bug detection. metadata: {"openclaw": {"emoji": "🔍"}} --- # Code Reviewer — 代码审查助手 ## 功能说明 对代码进行全面审查，发现问题和优化机会。 ## 使用方法 ### 1. 代码质量检查 ``` 用户: 审查这段代码的质量： [粘贴代码] ``` 审查维度： - 代码结构 - 命名规范 - 注释完整性 - 函数复杂度 - 重复代码 ### 2. 安全漏洞检查 ``` 用户: 检查这段代码是否有安全问题 ``` 检查项： - SQL注入风险 - XSS漏洞 - 敏感信息硬编码 - 不安全的依赖 - 权限控制缺失 ### 3. 性能优化建议 ``` 用户: 这段代码有什么性能问题？如何优化？ ``` 分析项： - 时间复杂度 - 空间复杂度 - 不必要的循环 - 数据结构选择 - 缓存机会 ### 4. 代码重构建议 ``` 用户: 这段代码如何重构使其更清晰？ ``` 重构方向： - 提取函数 - 消除重复 - 简化条件 - 改善命名 - 添加类型注解 ## 示例输出 ``` 代码审查报告 【质量问题】 1. 函数 `processData` 过长（85行），建议拆分 - 提取数据验证逻辑 - 提取数据转换逻辑 2. 变量命名不清晰 - `temp` → 建议改为 `processedResult` - `flag` → 建议改为 `isValidUser` 【安全问题】 ⚠️ 高危：SQL查询使用字符串拼接 第23行: `query = "SELECT * FROM users WHERE id=" + userId` 建议：使用参数化查询 【性能问题】 1. O(n²) 嵌套循环可优化为 O(n) 第45-52行：使用 Map 替代数组查找 2. 重复计算 第67行：`calculateTotal()` 在循环内重复调用 建议：提取到循环外 【优化建议】 - 添加输入验证 - 使用 TypeScript 类型注解 - 添加单元测试 ``` ## 支持语言 - JavaScript / TypeScript - Python - Go - Java - C / C++ - Rust


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