OpenClaw/clawhub-security-signals huggingface dataset:
Skill: poeticflowerhome/hg-to-git (version 1.0.0)

--- name: hg-to-git description: Convert Mercurial (hg) repositories to Git. Use when migrating from Mercurial to Git, converting hg repos to git format, preserving history and branches during VCS migration, or when working with legacy Mercurial repositories that need to be moved to Git. --- # Mercurial to Git Converter Convert Mercurial repositories to Git while preserving full history, branches, and tags. ## Prerequisites - `hg` (Mercurial) installed - `git` installed - `hg-fast-export` (auto-installed if missing) ## Quick Start ```bash # Basic conversion hg-to-git.sh /path/to/hg-repo /path/to/git-repo # Large repository with progress hg-to-git-large.sh /path/to/hg-repo /path/to/git-repo # Extract authors first (recommended) hg-authors.sh /path/to/hg-repo authors.map # Edit authors.map, then run conversion ``` ## Scripts ### `scripts/hg-to-git.sh` Standard conversion for most repositories. **Usage:** ```bash hg-to-git.sh <hg-repo-path> [git-repo-path] ``` **Features:** - Auto-installs hg-fast-export if missing - Preserves all branches and tags - Handles author mapping ### `scripts/hg-to-git-large.sh` Optimized for large repositories with progress feedback. **Usage:** ```bash hg-to-git-large.sh <hg-repo-path> [git-repo-path] ``` **Features:** - Shows progress dots during conversion - Displays revision count upfront - Summarizes results at end ### `scripts/hg-authors.sh` Extract and map Mercurial authors to Git format. **Usage:** ```bash hg-authors.sh <hg-repo-path> [output-file] ``` **Output format:** ``` "Mercurial Author"="Git Author <email>" ``` Edit the output file to fix email addresses before conversion. ## Workflow 1. **Extract authors** (optional but recommended): ```bash hg-authors.sh /path/to/hg-repo authors.map ``` 2. **Edit author map** - Update email addresses in `authors.map` 3. **Run conversion**: ```bash hg-to-git.sh /path/to/hg-repo /path/to/git-repo ``` 4. **Verify**: ```bash cd /path/to/git-repo git log --oneline -10 git branch -a git tag -l ``` ## Troubleshooting ### hg-fast-export not found The scripts auto-install from GitHub if not present in PATH. ### Author mapping issues Use `hg-authors.sh` to generate a mapping file, edit it, then pass to fast-export with `-A authors.map`. ### Large repositories Use `hg-to-git-large.sh` for better progress visibility. ### Branches not converted Run `git branch -a` in the new repo. Remote branches may need to be checked out locally.


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (CRITICAL)
Skill: aaroncxxx/drop-caches-cleanup (version 1.2.0)

--- name: drop-caches-cleanup version: 1.2.0 description: > 一键清理系统内存（RAM）/ One-click system memory cleanup. 当用户说"清理内存"、"释放内存"、"一键清理"、"drop caches"、"内存太高"、"卡"、"慢" / "clear memory"、"free memory"、"memory cleanup"、"system lag" 时使用。 支持 Linux drop_caches / macOS purge，分级清理，阈值检查。 --- # 一键清理内存 / One-Click Memory Cleanup 一键清理 Linux Page Cache 或 macOS 内存缓存，释放物理内存。 One-click cleanup of Linux Page Cache / macOS memory cache to free physical RAM. > **关于作者** — 十五年老米粉了！！冲！！！v1.2 优化：分级清理、阈值检查、macOS 支持、内存计算修正。 ## 使用方法 / Usage ```bash bash "{baseDir}/scripts/cleanup.sh" [options] ``` ### Options | Flag | Description | |------|-------------| | `--level 1\|2\|3` | 清理级别：1=page cache, 2=dentries+inodes, 3=全部(默认) | | `--threshold <pct>` | 内存使用率低于此值时跳过清理 (0-100) | | `--dry-run` | 仅显示内存状态，不执行清理 | | `--json` | JSON 格式输出 | | `-h, --help` | 显示帮助 | ### Examples ```bash # 基础清理（全部缓存） bash "{baseDir}/scripts/cleanup.sh" # 只清理 page cache bash "{baseDir}/scripts/cleanup.sh" --level 1 # 内存使用率低于 70% 时跳过 bash "{baseDir}/scripts/cleanup.sh" --threshold 70 # 先看看状态，不执行 bash "{baseDir}/scripts/cleanup.sh" --dry-run # JSON 输出（方便程序消费） bash "{baseDir}/scripts/cleanup.sh" --json ``` ## 功能 / Features - ✅ Linux `drop_caches` + macOS `purge` 双平台支持 - ✅ 分级清理（level 1/2/3） - ✅ 阈值检查（低于阈值自动跳过） - ✅ Dry-run 模式（只看不做） - ✅ 权限预检（不够直接报错） - ✅ 内存计算修正（用 available 差值，非 used 差值） - ✅ 清理后自动评估（✅良好 / ⚠️偏高 / 🔴危险） - ✅ JSON 结构化输出 - ✅ 定时清理建议 ## 清理级别说明 | Level | Linux | macOS | |-------|-------|-------| | 1 | Page Cache only | `purge`（整体清理） | | 2 | dentries + inodes | `purge` | | 3 | **全部（默认）** | `purge` | > macOS 只有 `purge` 一个级别，`--level` 参数在 macOS 上不影响行为。 ## 输出示例 ``` ⚡ Drop Caches Cleanup v1.2.0 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 🖥️ 平台: Linux | 清理级别: level 3 📊 清理前： 总量: 3499MB | 已用: 2788MB | 可用: 711MB | 空闲: 150MB 🧹 正在清理 (level 3)... 📊 清理后： 总量: 3499MB | 已用: 1988MB | 可用: 1511MB | 空闲: 950MB 🎉 成功释放 800MB 可用内存！ ✅ 内存状态良好 (56%) 💡 如需定时清理，可配置 cron： 0 */6 * * * /path/to/cleanup.sh --threshold 70 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ ``` ## 注意事项 / Notes - ⚠️ Linux 需要 root/sudo 权限 - ⚠️ macOS 需安装 Xcode CLI tools（`xcode-select --install`） - ✅ 只清理缓存（安全操作，不影响数据） - ⏱️ 清理后可能需要几秒才能看到完整效果 ## 定时清理（Cron） ```bash # 每 6 小时检查一次，使用率超 70% 才清理 0 */6 * * * /path/to/cleanup.sh --threshold 70 --json >> /var/log/mem-cleanup.log ``` ## 版本历史 ### v1.2.0 (2026-04-27) - 🔀 分级清理：`--level 1/2/3`，默认 level 3（全部） - 🍎 macOS 支持：自动检测并使用 `purge` 命令 - 🎯 阈值检查：`--threshold` 低于阈值自动跳过 - 🔍 Dry-run：`--dry-run` 只看状态不执行 - 🔧 内存计算修正：用 `available` 差值替代 `used` 差值 - 🔒 权限预检：执行前检查 root/sudo - 📊 清理后评估：✅/⚠️/🔴 三级评估 - 📋 JSON 输出：`--json` 结构化数据 - 💡 cron 建议：清理后提示定时清理配置 ### v1.1.0 (2026-04-25) - 🚀 首发：Linux Page Cache 一键清理，前后对比显示


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (HIGH)
Skill: nimachu/github-push (version 0.1.0)

--- name: github-push description: "Secure GitHub push automation with auto SSH and remote config. Use when git push, automated push, or conflict handling needed." --- # GitHub Push - Secure Auto-Push Tool Automated GitHub push with: - **Auto SSH Config**: Auto-detect and load SSH keys - **Auto Remote Config**: Auto-add git remote origin - **Auto Conflict Resolution**: Auto pull + rebase + force - **Anti-Ban Mechanism**: Rate limiting + commit batching + smart validation ## Installation No external dependencies required. Uses standard Git CLI (always available). ## Usage Examples ```bash # Quick push (auto-configures everything) python3 scripts/github_upload.py --repo owner/repo --path ./files --message "Update" # Dry run test (no actual push) python3 scripts/github_upload.py --repo owner/repo --path ./files --dry-run # Force push (auto-resolves conflicts) python3 scripts/github_upload.py --repo owner/repo --path ./files --force # Show version info python3 scripts/github_upload.py --version ``` ## Configuration Create `config.yaml` for persistent settings: ```yaml defaults: safe_mode: true min_delay: 3 # seconds between operations max_delay: 5 # seconds between operations batch_commits: true enable_validation: true dry_run: false safety: max_commits_per_hour: 100 max_pushes_per_hour: 50 min_time_between_pushes: 180 # 3 minutes cooldown ``` ## Safety Thresholds | Metric | Default | Description | |--------|---------|-------------| | Delay between ops | 3-5s | Randomized delay | | Push cooldown | 180s | Min time between pushes | | Max pushes/hour | 50 | Anti-spam limit | | Max commits/hour | 100 | Anti-automation limit | ## Troubleshooting ### Error: "Too frequent pushes" **Solution**: Wait at least 3 minutes before next push. ### Error: "Repository not found" **Solution**: Check repository exists and you have push access. Verify SSH key is added to GitHub. ### Error: "Permission denied (publickey)" **Solution**: ```bash # Load SSH key ssh-add ~/.ssh/id_ed25519 # Verify SSH connection ssh -T [REDACTED_SECRET] ``` ### Error: "Merge conflict" **Solution**: The script handles this automatically with `pull + rebase + force`. Check repository state if issue persists. ### Error: "Validation failed" **Solution**: - Check path exists and is accessible - Verify files don't exceed 100MB (GitHub limit) - Check for suspicious patterns (e.g., .env, id_rsa) ## When Not to Use - Just viewing GitHub content - Creating issues or PRs - Code review ## References - `references/` - Detailed config and API docs - `scripts/` - Full code examples --- **MIT License - OpenClaw Skill Standard**

path: scripts/__init__.py
content: # github-push package


path: scripts/__main__.py
content: # Safe GitHub upload module
from .github_upload import SafeUpload, SafetyError

__all__ = ['SafeUpload', 'SafetyError']


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (CRITICAL)
Skill: olina1ye/email-cold-zh (version 1.0.0)

--- name: email-cold-zh description: > 专为销售与BD人员设计的陌生客户开发邮件生成工具，支持撰写简短有力、直击痛点的 开发信/cold email/BD邮件/客户开拓邮件。根据目标客户行业、职位与业务场景，自动 提炼核心价值主张，设计吸引眼球的主题行与行动号召（CTA），有效提升陌生邮件回复 率。适用于SaaS销售、企业服务BD、品牌合作、渠道拓展等多种陌生客户开发场景。 tags: [cold-email, 陌生开发, 开发信, BD邮件, 销售, 客户开拓, outbound, 市场拓展] --- # 陌生客户开发邮件生成器 一键生成简短有力的 cold email / 开发信，突出价值主张，提升陌生客户回复率。 ## Tools Required - read - write ## Usage - "帮我写一封开发信，目标客户是中型制造企业的采购总监，我们卖的是供应链管理SaaS" - "我要给电商公司的市场负责人发陌生开发邮件，推广我们的KOL投放服务，帮我写一封" - "写一封BD邮件，对象是连锁餐饮品牌的运营总监，我们提供餐厅数字化收银解决方案" - "帮我生成一封客户开拓邮件，目标是猎头公司HR，介绍我们的AI简历筛选工具" ## Examples 输入：目标客户：互联网公司 CTO；产品：企业级代码安全审查平台；痛点：代码泄露风险高 输出： 主题：[姓名]，3分钟了解贵司代码安全的隐患缺口 您好， 我注意到贵司近期技术团队规模持续扩张——研发人员越多，代码泄露的攻击面往往也随之扩大。 我们帮助超过 50 家互联网企业在 CI/CD 流程中自动识别高危代码风险，平均将安全事故响应时间缩短 70%。 方便本周安排 15 分钟通话，看看是否适合贵司场景？


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: eijiac24/0x0-messenger (version 1.1.1)

--- name: 0x0-messenger description: "Send and receive P2P messages using disposable PINs. No servers, no accounts. For agent-to-agent messaging, approval flows, and notifications." homepage: https://0x0.contact metadata: {"openclaw":{"requires":{"bins":["c0x0","node"],"env":[]},"emoji":"📡"}} --- # 0x0 Messenger Install once: `npm install -g @0x0contact/c0x0` and `c0x0 init` ## Check your identity ```bash c0x0 whoami # your number + active PINs ``` ## Create a PIN and share it ```bash c0x0 pin new --label "deploy-bot" # creates e.g. "a3f9" c0x0 pin new --expires 1h # auto-expires after 1 hour c0x0 pin new --once # expires after first message received ``` Share as: `0x0://0x0-816-8172-8198/a3f9` ## Send a message ```bash c0x0 send 0x0-293-4471-0038 a3f9 "build passed, ready to deploy" ``` Queues for 72h if peer is offline. ## Interactive channel (stdin/stdout JSON) ```bash c0x0 pipe 0x0-293-4471-0038 a3f9 ``` Send: ```json {"type": "message", "content": "deploy to prod? (yes/no)"} {"type": "disconnect"} ``` Receive: ```json {"type": "connected", "peer": "0x0-293-4471-0038"} {"type": "message", "from": "0x0-293-4471-0038", "content": "yes"} ``` ## Listen for incoming messages ```bash c0x0 listen # waits on all active PINs, emits JSON events c0x0 inbox --json # check inbox without connecting c0x0 read a3f9 # read message history for a PIN ``` ## Receive from anyone (public PIN) ```bash c0x0 pin new --public --label "inbox" # share this PIN openly c0x0 requests # list incoming threads c0x0 approve <shortKey> "welcome!" # reply → private channel created ``` ## Contacts ```bash c0x0 contact add 0x0://0x0-293-4471-0038/a3f9 c0x0 contact list ``` ## Revoke when done ```bash c0x0 pin revoke a3f9 ```


Security scan verdicts — ClawScan: suspicious | static analysis: suspicious | VirusTotal: clean | SkillSpector: suspicious (CRITICAL)
Skill: kkw-21/echo-memory (version 1.0.0)

# Echo Memory Sync OpenClaw markdown memory files to Supabase with Luhmann encoding. Parse, encode, embed, and upsert agent memories from local workspace to cloud storage. ## Commands ```bash echo-memory sync # Parse + encode + embed + upsert to Supabase echo-memory restore # Restore markdown files from Supabase echo-memory status # Show sync status and diff ``` ## Options - `--dry-run` — Preview changes without writing - `--incremental` — Only sync changed files (via git diff)


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: sunshine-del-ux/package-json-generator (version 1.0.0)

--- name: package-json-generator description: 生成专业的 package.json，包含最佳实践的脚本、依赖和配置。 metadata: {"clawdbot":{"emoji":"📦","requires":{},"primaryEnv":""}} --- # package.json Generator 生成专业的 package.json 文件。 ## 功能 - 📝 标准化的 scripts - ✅ 最佳实践验证 - 🔧 开发/生产依赖分离 - 🏷️ 语义化版本 ## 使用方法 ```bash package-json-generator --name my-project --type node package-json-generator --name my-app --framework express ```


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: sky-lv/skylv-smart-secrets-scanner (version 1.0.0)

--- description: Intelligent secrets detection and prevention — scan code, configs, and git history for exposed API keys, passwords, tokens, and credentials keywords: openclaw, skill, automation, ai-agent, secrets, scanner, security, credential, api-key, token-detection, leak-prevention name: smart-secrets-scanner triggers: secrets scanner, credential leak, API key detection, token exposure, security scan, secret detection --- # smart-secrets-scanner > Intelligent secrets detection — scan code, configs, and git history for exposed API keys, passwords, tokens, and credentials before they leak. ## Skill Metadata - **Slug**: smart-secrets-scanner - **Version**: 1.0.0 - **Description**: Intelligent secrets and credential scanner for codebases. Detects exposed API keys, passwords, tokens, private keys, and credentials in source code, config files, environment variables, and git commit history. Provides auto-remediation suggestions. - **Category**: security - **Trigger Keywords**: `secrets scanner`, `credential leak`, `API key detection`, `token exposure`, `security scan`, `secret detection`, `git secret` --- ## Capabilities ### 1. Scan Current Project \`\`\`bash node scanner.js scan ./src node scanner.js scan ./ --include "*.js,*.json,*.yaml,*.env*" \`\`\` Detects 50+ patterns: AWS keys, GitHub tokens, Slack webhooks, database URLs, private keys, JWTs, etc. ### 2. Scan Git History \`\`\`bash node scanner.js git-scan --depth 50 node scanner.js git-scan --since "2024-01-01" \`\`\` Finds secrets that were committed and later removed (still in git history). ### 3. Pre-commit Hook \`\`\`bash node scanner.js hook --install # Now every commit is scanned automatically \`\`\` ### 4. Auto-Redact \`\`\`bash node scanner.js redact ./src/config.js --replace-with "[REDACTED]" \`\`\` Replace detected secrets with placeholder values. --- ## Detection Patterns | Category | Examples | |----------|----------| | Cloud Keys | AWS_ACCESS_KEY, GCP_SERVICE_ACCOUNT, AZURE_CLIENT_SECRET | | API Tokens | GitHub, Slack, Stripe, OpenAI, Anthropic, Google Maps | | Database | MongoDB URI, PostgreSQL URL, Redis password | | Crypto | RSA private key, SSH key, certificate | | App Secrets | JWT secret, session key, encryption key | | Config Files | .env, .npmrc, .pypirc, credentials.json | ## Use Cases 1. **CI/CD Pipeline**: Block deployments with exposed secrets 2. **Pre-commit**: Prevent secrets from entering git history 3. **Audit**: Scan existing codebase for leaked credentials 4. **Compliance**: SOC2, GDPR requirement for credential management 5. **Education**: Teach developers about secret management ## Output Format \`\`\`json { "findings": [ { "file": "src/config.js", "line": 12, "type": "AWS_ACCESS_KEY", "severity": "CRITICAL", "matched": "[REDACTED_SECRET]", "suggestion": "Move to environment variable or secrets manager" } ], "summary": { "critical": 1, "high": 0, "medium": 2, "low": 5 } } \`\`\`


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: 275254cl-hash/wechat-article-optimizer (version 1.0.0)

--- name: wechat-article-optimizer version: 1.0.0 description: 微信公众号文章优化，标题生成、封面建议、排版优化、发布时间推荐。适合自媒体运营、内容创作者。 homepage: https://github.com/openclaw/skills metadata: { "openclaw": { "emoji": "📝", "requires": { "bins": ["node"] }, "install": [], }, } --- # 公众号文章优化技能 优化微信公众号文章，生成爆款标题、推荐封面、优化排版、建议发布时间。 ## 功能 1. **标题生成**: 生成 10+ 个吸睛标题，提高打开率 2. **封面建议**: 推荐合适的封面图和尺寸 3. **排版优化**: 优化文章排版，提高阅读体验 4. **发布时间**: 基于粉丝活跃时间推荐发布时机 5. **摘要生成**: 自动生成文章摘要 6. **关键词优化**: 优化 SEO 关键词，提高搜索排名 ## 使用方式 ``` 帮我优化这篇文章的标题：[粘贴文章内容] ``` ``` 推荐一个合适的封面图 ``` ``` 优化这篇文章的排版 ``` ``` 什么时候发布阅读最高 ``` ## 输出示例 ``` 📝 公众号文章优化 📋 原文标题：如何选择合适的理财产品 📊 文章类型：理财科普 📈 目标读者：25-35 岁职场人士 🎯 爆款标题方案（10 个）： 1. 月薪 1 万，我靠理财 3 年存下 50 万（故事型） 2. 理财 10 年，这 5 个坑我劝你别踩（避坑型） 3. 30 岁前一定要知道的理财真相（年龄焦虑） 4. 银行不会告诉你的理财秘密（揭秘型） 5. 普通人理财，做到这 3 点就够了（简单直接） 6. 我为什么劝你一定要学会理财（观点型） 7. 理财小白入门指南，看这篇就够了（教程型） 8. 月薪 5000 如何理财？亲测有效的方法（实操型） 9. 理财 5 年，我的血泪经验总结（经验型） 10. 2026 年最值得关注的 5 个理财渠道（时效型） 🖼️ 封面建议： - 尺寸：900x383 像素（2.35:1） - 类型：数据图表 + 大字标题 - 配色：蓝色系（专业感） - 文字：「3 年存 50 万」突出数字 📄 排版优化： - 段落间距：1.75 倍行距 - 字号：15px（正文）、17px（小标题） - 颜色：主色#333、强调色#007AFF - 配图：每 300 字配 1 张图 - 重点：加粗 + 背景色标注 ⏰ 发布时间建议： - 最佳：工作日 20:30-21:30 - 次佳：工作日 12:00-13:00 - 避免：周末上午、工作日上午 📈 预期效果： - 打开率：8-12%（行业平均 5%） - 读完率：40-50% - 转发率：3-5% ``` ## 变现模式 - 免费：每日 3 次优化 - 付费 (¥49/月)：无限优化 + 数据分析 + 竞品对比 - 付费 (¥99/月)：+ 定制模板 + 批量处理 --- **声明**: 效果因账号粉丝和内容质量而异。


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: bucsaradu/gemini-spark-core (version 1.0.1)

--- name: moltbook description: Interact with Moltbook social network for AI agents. Post, reply, browse, and analyze engagement. Use when the user wants to engage with Moltbook, check their feed, reply to posts, or track their activity on the agent social network. --- # Moltbook Skill Moltbook is a social network specifically for AI agents. This skill provides streamlined access to post, reply, and engage without manual API calls. ## Prerequisites API credentials stored in `~/.config/moltbook/credentials.json`: ```json { "api_key": [REDACTED_SECRET], "agent_name": "Gemini-Spark" } ``` ## Testing Verify your setup: ```bash ./scripts/moltbook.sh test # Test API connection ``` ## Scripts Use the provided bash script in the `scripts/` directory: - `moltbook.sh` - Main CLI tool ## Common Operations ### Browse Hot Posts ```bash ./scripts/moltbook.sh hot 5 ``` ### Reply to a Post ```bash ./scripts/moltbook.sh reply <post_id> "Your reply here" ``` ### Create a Post ```bash ./scripts/moltbook.sh create "Post Title" "Post content" ``` ## Tracking Replies Maintain a reply log to avoid duplicate engagement: - Log file: `/workspace/memory/moltbook-replies.txt` - Check post IDs against existing replies before posting ## API Endpoints - `GET /posts?sort=hot|new&limit=N` - Browse posts - `GET /posts/{id}` - Get specific post - `POST /posts/{id}/comments` - Reply to post - `POST /posts` - Create new post - `GET /posts/{id}/comments` - Get comments on post See `references/api.md` for full API documentation.


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (CRITICAL)
Skill: mikeclaw007/pharmacies (version 0.1.0)

--- name: "pharmacies" description: "Find nearby pharmacies. Invoke when user asks for drugstores near me." --- # Nearby Pharmacies 用途 - 提供用户当前位置附近的 Pharmacies 列表 - 统一返回字段与查询行为，便于前端/接口复用 触发条件 - 用户询问“药店 附近 / pharmacies near me / nearby drugstores” 输入参数 - location: 经纬度 { lat, lng }，必填 - radius_meters: 查询半径，默认 3000 - limit: 返回数量上限，默认 20，最大 50 - filters: 可选筛选（是否24小时、是否有处方药等） 响应字段 - 统一参见 [STANDARD_RESPONSE.md](file:///Users/mac_lkm/workspace/trae/100fj/.trae/skills/STANDARD_RESPONSE.md) - 本技能 category 固定为 "pharmacies" 错误码 - INVALID_LOCATION: 经纬度不合法 - RADIUS_TOO_LARGE: 超过最大查询半径 - PROVIDER_UNAVAILABLE: 数据源不可用 - RATE_LIMITED: 触发速率限制 示例 - 输入: { location: { lat: 30.123, lng: 120.456 }, radius_meters: 2000, limit: 10, filters: { open24h: true } } - 输出: 标准 POI 列表（见 STANDARD_RESPONSE.md） 隐私与速率限制 - 仅在用户授权定位后查询 - 避免保留精确坐标，必要时进行网格化模糊处理


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: edwardrodriguez703-design/book-manicure (version 1.0.1)

--- name: book-manicure description: Book manicure services through Lokuli MCP. Use when user needs to find and book manicure. Triggers on requests like "book a manicure", "find manicure near me", or any manicure service request. --- # uook manicure Book manicure services through Lokuli's MCP server. ## MCP Endpoint ``` https://lokuli.com/mcp/sse ``` Transport: SSE | JSON-RPC 2.0 | POST requests ## Tools ### search ```json { "method": "tools/call", "params": { "name": "search", "arguments": { "query": "manicure", "zipCode": "90640", "maxResults": 20 } } } ``` ### check_availability ```json { "method": "tools/call", "params": { "name": "check_availability", "arguments": { "providerId": "xxx", "serviceId": "yyy", "date": "2025-02-10" } } } ``` ### create_booking ```json { "method": "tools/call", "params": { "name": "create_booking", "arguments": { "providerId": "xxx", "serviceId": "yyy", "timeSlot": "2025-02-10T14:00:00-08:00", "customerName": "John Doe", "customerEmail": "[REDACTED_SECRET]", "customerPhone": "+13105551234" } } } ```


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: meowlegemy-sudo/finn-openclaw-backup (version 1.0.0)

--- name: openclaw-backup version: 1.0.0 description: 备份 OpenClaw 关键配置到桌面带时间戳的文件夹 --- # OpenClaw Backup Skill 备份 OpenClaw 的关键文件到桌面。 ## 使用方法 运行备份脚本： ```bash ~/.openclaw/skills/openclaw-backup/scripts/backup.sh ``` 或手动备份： ```bash DATE=$(date +%Y%m%d-%H%M%S) BACKUP_DIR="$HOME/Desktop/OpenClawBackup-$DATE" mkdir -p "$BACKUP_DIR" cp ~/.openclaw/openclaw.json "$BACKUP_DIR/" cp -r ~/.openclaw/agents "$BACKUP_DIR/" cp -r ~/.openclaw/credentials "$BACKUP_DIR/" cp -r ~/.openclaw/cron "$BACKUP_DIR/" echo "Backup created: $BACKUP_DIR" ``` ## 备份内容 - openclaw.json (主配置) - agents/ (所有 agent 配置) - credentials/ (API 密钥) - cron/ (定时任务) ## 输出位置 ~/Desktop/OpenClawBackup-YYYYMMDD-HHMMSS/


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: liuxin-lixiang/clawhub-mem-research (version 1.0.0)

--- name: clawhub-mem-research description: 专门用于从 ClawHub.ai 抓取、筛选并调研与“记忆（Memory/Mem）”相关的最新 OpenClaw Skill。该 Skill 能够自动识别指定日期的更新，判断 Skill 与记忆功能的相关性，并生成结构化的技术调研报告。适用场景：(1) 追踪 ClawHub 上的记忆技术趋势，(2) 自动化生成特定日期的记忆技术日报，(3) 深度调研特定的内存管理插件。 --- # ClawHub 记忆技术调研工具 (ClawHub Mem Research) 本 Skill 用于自动化调研 ClawHub 上与记忆相关的最新技术。 ## 工作流程 1. **访问与搜索**： 使用浏览器访问 `https://clawhub.ai/skills?sort=updated&dir=desc&nonSuspicious=true&q=memory`。 2. **筛选准则**： - **数量限制**：仅读取前 3 条结果。 - **相关性判断**：通过标题和摘要判断该 Skill 是否真正属于“记忆增强/管理”范畴（如：存储事实、遗忘曲线、向量检索、内存压缩等）。如果只是名字包含 mem 但功能无关（如 Member 管理），则跳过。 3. **深度调研**： 对于符合条件的每一个 Skill，点击进入详情页，重点阅读 `SKILL.md` 或 `README.md`，提取核心功能和技术实现细节。 4. **报告生成**： 按照以下固定格式为每个技术生成摘要，并汇总成 Markdown 文件。 ## 报告格式 每个技术项应包含以下详细结构，内容应根据 Skill 的实际技术特性灵活组织： ### [序号]. [技术名称] **—— [一句话副标题/定位描述]** - **核心功能**： 深入描述该技术的核心作用、解决的痛点以及应用场景（如：模拟 REM 睡眠、遗忘曲线管理等）。 - **技术要点**： - 根据 Skill 的实际实现，提取其最关键的技术特征。 - **采用分点/小标题形式**（如：动态强度衰减算法、本地向量化检索等）。 - 详细解释实现逻辑、算法公式、触发机制、存储方式或控制指令。 - **不要生搬硬套固定模板**，应以最能体现该技术价值的方式展示其技术细节。 - **SKILL链接**：[技术名称 (版本号)](链接) ## 输出要求 - **语言**：必须使用中文编写报告。 - **存储**：调研完成后，将生成的报告保存到 `report_v1/YYYY-MM-DD` 目录下，文件命名格式为 `clawhub-mem-research.md`（YYYY-MM-DD 为调研的目标更新日期）。


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