OpenClaw/clawhub-security-signals huggingface dataset:
Skill: nirveshdagar/multi-engine-websearch (version 2.0.2)

--- name: websearch version: 2.0.0 description: "Multi-engine web search across 6 engines: DuckDuckGo, DDG Lite, Yahoo, Yahoo JP, Startpage, and Google (headless Chromium). No API keys required. Returns 10+ results per engine, ranked by cross-engine frequency." author: nirvesh-dagar repository: https://github.com/nirveshdagar/multi-engine-websearch tags: [search, web, research, google, multi-engine] --- # WebSearch — Multi-Engine Search Aggregator **🔗 GitHub:** https://github.com/nirveshdagar/multi-engine-websearch **📦 Git Install:** ```bash git clone https://github.com/nirveshdagar/multi-engine-websearch.git ``` **📦 ClawHub Install:** ```bash npx clawhub@latest install multi-engine-websearch ``` --- A free, local web search skill that queries 6 reliable search engines simultaneously (in parallel), merges results, deduplicates URLs, and ranks by cross-engine frequency. No API keys required. No paid subscriptions. Runs entirely on your machine. ## Requirements - Python 3.9+ - Playwright (`pip3 install playwright && python3 -m playwright install chromium`) Playwright is needed for the Google engine (headless Chromium renders JS-based results). All other engines use lightweight HTTP scraping with zero dependencies. ## When to Use Use this skill whenever the user asks you to: - Search the web for anything - Find recent news, articles, or information - Look up a topic, person, product, or event - Verify a fact with current web results - Research a topic with multiple sources ## Command ```bash python3 ~/.openclaw/workspace/skills/websearch/scripts/search.py "your query" --json ``` ### Options | Flag | Default | Description | |------|---------|-------------| | `--json` / `-j` | off | Output as JSON | | `--num` / `-n` | 10 | Results per engine | | `--max` / `-m` | 50 | Max total results | | `--engines` / `-e` | all 6 | Comma-separated engine list | | `--list-engines` | — | Show available engines | ## Engines | Engine | Method | Reliability | |--------|--------|-------------| | DuckDuckGo | HTML scrape | ⭐⭐⭐⭐⭐ | | DDG Lite | HTML scrape | ⭐⭐⭐⭐ | | Yahoo | HTML scrape | ⭐⭐⭐⭐ | | Yahoo JP | HTML scrape | ⭐⭐⭐⭐ | | Startpage | HTML scrape | ⭐⭐⭐⭐ | | Google | Headless Chromium | ⭐⭐⭐⭐ | All engines run in parallel using ThreadPoolExecutor for maximum speed. ## Output Format ```json { "query": "your search", "total": 35, "engines": {"duckduckgo": 10, "google": 8, "yahoo": 10, ...}, "results": [ { "title": "Result Title", "url": "https://example.com", "snippet": "Description...", "engines": ["duckduckgo", "google", "yahoo"] } ] } ``` Results appearing in more engines are ranked higher (cross-engine consensus). ## Core Rules 1. Always use `--json` flag when parsing results programmatically 2. Summarize top results in natural language for the user 3. Always cite sources with URLs 4. If one engine fails, others compensate — the system is resilient 5. Google engine is slower (~5s) due to headless browser; other engines are fast (~1-2s)


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (HIGH)
Skill: axelhu/daily-log (version 1.1.0)

--- name: daily-log version: 1.1.0 description: 每日工作日志生成技能。触发时机：每次会话结束前或完成重要任务后。输出位置：memory/daily/YYYY-MM-DD.md。使用方法：加载 skill 后读取 references/spec.md 获取详细规范。 --- # Daily Log 按规范生成每日工作日志，供后续知识提取。 ## 输出位置 `memory/daily/YYYY-MM-DD.md` ## 核心流程 1. 读取 references/spec.md 获取详细规范 2. 读取当前日记（如已存在） 3. 按规范生成/整合日志 4. 写文件 5. 自检 ## 触发时机 - 会话结束前 - 完成重要任务后 - 用户明确要求时 ## 为什么要写日记 日记是记忆系统的核心输入： - cron memory-review 扫描日记生成知识提案 - 没有日记，知识沉淀链条断裂 - 详细日记 → 更多可提取知识 ## 常见错误 - 只写结果不写过程 → 无法提取经验 - 事后概括 → 丢失细节 - 过于简略 → 扫不出东西 ## 与 Memory Review 联动 日记是记忆系统的核心输入： - **daily-log** 负责写日记 - **memory-review** 负责扫描日记生成知识提案 - 两者配合：详细日记 → 更多可提取知识 详见 `skills/memory-review/SKILL.md`

path: references/spec.md
content: # 每日日志详细规范

## 必须包含

| 字段 | 说明 |
|------|------|
| **what** | 做了什么 |
| **why** | 为什么这样做（关键决策） |
| **files** | 变更的文件路径 |
| **commands** | 执行的命令及输出 |
| **errors** | 错误信息（如果有） |

## 禁止

- 事后概括性总结
- 只有结果没有过程
- 过于简略

## 示例格式

```markdown
# 2026-03-16 工作日志

## 任务：xxx

### 执行步骤
1. 做了 xxx → 结果 xxx

### 决策
- 选择方案 A 而非 B，因为：A 更适合

### 输出
- 新增：xxx
- 修改：xxx

### 错误
- xxx 失败 → 原因 → 解决
```

## 写入流程

1. 读取当前日记文件（如已存在）
2. 智能整合新内容（保留旧内容，只追加/优化）
3. 写回文件

**注意：** 不要删除旧内容，只做增量优化。

## 自检清单

- [ ] 有 what
- [ ] 有 why
- [ ] 有文件路径
- [ ] 有命令输出
- [ ] 非事后总结
- [ ] > 10 行


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: chris6970barbarian-hue/openclaw-migrate (version 1.0.0)

# OpenClaw Migration Skill Migrate OpenClaw from one host to another via SSH. ## Skill Metadata - **Name**: openclaw-migrate - **Type**: OpenClaw Skill - **Purpose**: Migrate all OpenClaw config, skills, memory, tokens to new host ## Setup Commands ### Prerequisites 1. SSH access to new host 2. SSH key (recommended for automation) 3. NPM installed on new host ### Configuration ```bash # Configure migration target openclaw-migrate setup # It will ask for: # - New host IP/hostname (e.g., 192.168.1.50) # - SSH user (e.g., crix) # - SSH key path (optional, Enter for default) ``` ## Usage Commands ### Main Migration ```bash # Start migration (one command!) openclaw-migrate migrate ``` ### Other Commands ```bash # Test SSH connection openclaw-migrate test # Show current configuration openclaw-migrate status # Reconfigure target openclaw-migrate setup ``` ## What Gets Synced ### Files & Directories | Source | Destination | |--------|-------------| | `~/.openclaw/` | `~/.openclaw/` (skills, memory, config) | | `~/.config/openclaw/` | `~/.config/openclaw/` | | OpenClaw npm package | Reinstalled if missing | ### Environment Variables | Variable | Description | |----------|-------------| | `HA_URL` | Home Assistant URL | | `HA_TOKEN` | Home Assistant token | | `GITHUB_TOKEN` | GitHub API token | | `BRAVE_API_KEY` | Brave Search API | | `GOOGLE_API_KEY` | Google API key | | Any `HA_*` vars | All HA related vars | ### System Data - Cron jobs (via crontab) - OpenClaw gateway configuration ## Migration Flow ``` 1. setup → Configure target host 2. test → Verify SSH connection 3. migrate → Full sync and start ├─ Check/Install OpenClaw ├─ Sync workspace (~/.openclaw/) ├─ Sync config ├─ Sync environment variables ├─ Sync cron jobs └─ Start gateway on new host ``` ## Error Handling - SSH connection failed: Show retry option - OpenClaw not on remote: Offer to install - Sync failed: Report which files failed - Config missing: Prompt for setup ## Related Skills - skillstore (search/install skills) ## Files ``` openclaw-migrate/ ├── SKILL.md # This file ├── README.md # User docs ├── main.js # Migration CLI └── config.json # Saved target config ```


Security scan verdicts — ClawScan: suspicious | static analysis: suspicious | VirusTotal: suspicious | SkillSpector: suspicious (CRITICAL)
Skill: matthewxmurphy/homebrew-bridge (version 0.6.1)

--- name: homebrew-bridge version: "0.6.1" description: Expose Mac Homebrew tools like brew, gh, and other /opt/homebrew/bin CLIs on a Linux OpenClaw gateway by installing explicit same-LAN SSH wrappers with optional Wake-on-LAN and OpenClaw config auto-discovery. metadata: {"openclaw":{"emoji":"🍺"}} --- # Homebrew Bridge Use this skill when the real value is giving a Linux OpenClaw gateway access to a Mac node's Homebrew toolchain. This skill is for `/opt/homebrew/bin/<tool>` wrappers such as: - `brew` - `gh` - other Homebrew-installed CLIs you want to expose from a Mac node ## Use This Skill For - Linux gateways that should run Homebrew-backed tools through a Mac node - wrapper-backed skills that depend on `brew`, `gh`, or another Homebrew CLI - same-LAN Mac nodes that already hold the real Homebrew installs - optional host auto-discovery from OpenClaw config when only one Mac owner is known ## Do Not Use This Skill For - tools that are inherently Mac-owned apps or permissioned CLIs like `imsg` or `remindctl` - Linux-native tools that should be installed on Linux directly - WAN-routed Macs or generic remote shell access ## Requirements - Linux gateway and owning Mac share the same trusted local network or VLAN - Linux gateway can SSH to the owning Mac - the requested tool exists at `/opt/homebrew/bin/<tool>` on that Mac - the Mac stays awake during work windows or supports Wake-on-LAN ## Workflow ### 1. Render A Tool Ownership Map Run: ```bash scripts/render-tool-map.sh /home/node/.openclaw/openclaw.json ``` This prints the inferred or fallback Mac owner for Homebrew-backed tools. ### 2. Install The Homebrew Pack Example: ```bash scripts/install-homebrew-pack.sh \ --target-dir /home/node/.openclaw/bin \ --tool brew \ --tool gh \ --tool claude \ --default-host [REDACTED_SECRET] \ --wake-map mac-node.local=AA:BB:CC:DD:EE:FF \ --wake-wait 20 \ --wake-retries 2 ``` Host resolution order: - explicit `--map tool=user@host` - `--default-host user@host` - the single discovered `remoteHost` in the OpenClaw config, if there is exactly one - no repeated host questions when the OpenClaw config already resolves the owner ### 3. Verify The Pack Run: ```bash scripts/verify-homebrew-pack.sh --target-dir /home/node/.openclaw/bin ``` ## Design Contract - Linux owns the stable wrapper paths - the Mac owns the real `/opt/homebrew/bin` binaries - public skills depend on wrapper paths, not Mac paths - wrapper names stay explicit per tool ## Files - `scripts/install-wrapper.sh`: create one SSH wrapper for a remote binary - `scripts/install-homebrew-pack.sh`: install a batch of Homebrew-backed wrappers - `scripts/verify-homebrew-pack.sh`: verify the installed wrappers - `scripts/render-tool-map.sh`: print inferred or fallback tool-to-host maps - `references/skill-readiness.md`: publishability rules for Homebrew-backed wrappers


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: lirenming/futures-morning-brief (version 1.0.0)

--- name: futures-morning-brief description: 期货早报生成工具。用户输入网址或留空默认使用西本资讯，自动抓取当天最新行业要闻早餐，按固定HTML格式输出，包含：整体综述（置顶）、重点关注（3条）、信息速览（行情表格）、宏观要闻（10条+详情）、产业要闻（6条+详情）。触发词：生成早报、期货早报、早间新闻、行业要闻早餐、早班车、卓钢早报。 --- # 期货早报生成工具 ## 工作流程 ### Step 1：获取目标 URL - 用户提供网址时直接使用；未提供时默认 https://www.steelx2.com/；进入后自动定位当前日期最新的 X月X日行业要闻早餐 文章 - 只使用用户提供的内容，不搜索其他来源 ### Step 2：提取页面内容 - 重点关注：页面中重点关注板块（通常3条，含标题+详情） - 行情数据：品种、收盘价、涨跌、幅度 - 宏观要闻：10条（标题+详情） - 产业要闻：6条（标题+详情） ### Step 3：生成 HTML 早报 按 eferences/output-format.md 规范输出，保存到用户桌面。 HTML 结构顺序： 1. 顶部横幅 2. 整体综述（置顶第一版块） 3. 重点关注（3条） 4. 信息速览（四列表格） 5. 宏观要闻（标题列表+每条标题+内容展开，共10条） 6. 产业要闻（标题列表+每条标题+内容展开，共6条） 7. 页脚 全文不显示任何来源说明。 ### Step 4：验证 打开生成的 HTML 截图确认。 ## 参考资源 - 格式规范： eferences/output-format.md - 原始模版： ssets/template.html ## 注意事项 - 默认：西本资讯 steelx2.com，自动获取最新一期早报 - 表格涨跌：正数红色 rgb(204,0,0)；负数绿色 rgb(0,128,0) - 宏观/产业要闻：每条新闻标题+内容直接展开，不用折叠/滚动区 - 产业要闻标题蓝色 rgb(79,129,189)；宏观要闻标题棕色 rgb(117,79,68) - 主色调：#d2bd8b 金棕色


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: visualdeptcreative/daily-report (version 1.0.0)

# SKILL.md - Daily Report ## Purpose Track progress, report metrics, manage memory. ## Model to Use **local** (ollama) - simple aggregation, FREE ## Morning Report (Send at 9:30 AM Spain) ``` 🤖 SKYNET MORNING BRIEFING - {{date}} 📊 PIPELINE ├─ Total leads: X ├─ Ready for outreach: X ├─ In sequence: X ├─ Awaiting reply: X 📬 OVERNIGHT ├─ Leads found: X ├─ Emails drafted: X ├─ Cost: $X.XX 🎯 TODAY'S PRIORITIES 1. [Based on pipeline status] 2. [Based on day of week] 3. [Based on targets] 💰 BUDGET ├─ Spent today: $X.XX ├─ Daily remaining: $X.XX ├─ Monthly remaining: $X.XX ``` ## End of Day Report (Send at 9 PM Spain) ``` 🤖 SKYNET EOD - {{date}} 📈 TODAY'S NUMBERS ├─ Leads sourced: X / 40 target ├─ DMs drafted: X / 25 target ├─ Emails drafted: X / 30 target ├─ Notion updated: ✓ 💰 COST REPORT ├─ Today: $X.XX ├─ This week: $X.XX ├─ Budget remaining: $X.XX 🔥 HOT LEADS [List any Priority A leads found] ⚠️ ISSUES [List any blockers or errors] 📋 TOMORROW [Next day priorities] 💾 Saved to memory/{{date}}.md ``` ## Weekly Report (Sunday 8 PM) ``` 🤖 SKYNET WEEKLY - Week of {{date}} 📊 TOTALS ├─ Leads sourced: X ├─ Outreach sent: X (DMs + Emails) ├─ Replies: X ├─ Qualified: X ├─ Closes: X 💰 COSTS ├─ This week: $X.XX ├─ Avg per lead: $X.XX ├─ Avg per qualified: $X.XX 📈 CONVERSION ├─ Source → Qualified: X% ├─ Outreach → Reply: X% ├─ Reply → Meeting: X% 🎯 VS TARGETS ├─ Revenue: $X / $5,000 goal ├─ Days remaining: X ├─ Needed per day: $X ``` ## Memory File Format Save to memory/YYYY-MM-DD.md: ```markdown # {{date}} - Daily Log ## Metrics - Leads sourced: X - DMs drafted: X - Emails drafted: X - Cost: $X.XX ## Leads Found (Summary) - Priority A: X - Priority B: X - Skipped: X ## Issues [Any problems encountered] ## Notes [Context for future sessions] ## Tomorrow - [ ] Task 1 - [ ] Task 2 ``` ## Alerts (Send Immediately) Trigger immediate Telegram alert for: - Any reply detected - Budget 75% depleted - API error / rate limit - Overnight run complete - Task blocked / needs input


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: itsflow/journal-to-post (version 1.0.0)

--- name: journal-to-post description: Convert personal journal entries into shareable social media posts version: 1.0.0 author: theflohart tags: [content, writing, social-media, journaling] --- # Journal to Post Convert personal reflections, journal entries, or voice notes into shareable social media posts. ## Usage ``` /journal-to-post [journal text or file path] ``` ## How It Works 1. **Input:** Provide journal text directly or a file path 2. **Process:** Extract universal insights from personal experience 3. **Output:** 1-3 polished posts ready to share ## Voice Guidelines ### Do - Direct, confident, no hedging - First person when sharing experience - Punchy hooks that challenge assumptions - Specific details that add credibility (numbers, timeframes) ### Don't - Include too personal/private details - Write vague platitudes - Use "I learned that..." framing (show, don't tell) - Sound like typical self-help content ## What Gets Extracted - Universal insights from personal experience - Counterintuitive observations - Patterns you've noticed - Specific data points that anchor the insight ## Transformation Examples ### Example 1 **Journal:** > "Noticed my energy dropped after that difficult meeting. Took 3 hours of walking before I felt normal again." **Post:** > "Your body keeps score of difficult conversations. My energy tanked after one meeting yesterday. Took 3 hours of walking to recover. Most people ignore this and wonder why they're exhausted by Friday." --- ### Example 2 **Journal:** > "Had a breakthrough in meditation today - realized I've been trying to 'achieve' stillness instead of just noticing what's already there." **Post:** > "The meditation trap: trying to achieve stillness. The shift: noticing stillness is already there, underneath the noise. Took me 2 years to stop efforting." --- ### Example 3 **Journal:** > "Spent 4 hours debugging something that turned out to be a typo. Frustrated but also funny in hindsight." **Post:** > "4 hours debugging. The fix? A typo. One character. This is the job. The gap between 'stuck' and 'solved' is often embarrassingly small." ## Output For each generated post: 1. **Show the post** - Ready to copy/paste 2. **Explain the transformation** - What was extracted, what was removed 3. **Offer variations** - Different angles or platforms (X vs LinkedIn) ## Tips for Better Results - Include specific numbers and timeframes in your journal - Note your emotional state, not just events - Capture the "aha moment" or shift in thinking - Don't self-censor in the journal - the skill will filter for you


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: tanghailong1221/human-like-memory-cn (version 1.2.0)

--- name: human-like-memory description: 模仿人类记忆机制的智能上下文管理系统，支持向量化检索、智能摘要、三层存储（HOT/WARM/COLD）、按需注入 version: 1.2.0 --- # Human-Like Memory Skill v1.1.1 🧠 **下一代智能记忆管理系统** — 向量化检索 + 智能压缩 + 按需注入 ## ✨ v1.2.0 新特性 | 功能 | 说明 | Token 节省 | |------|------|-----------| | 🧠 **向量化检索** | 语义搜索，相似度>0.7 | -40% | | 🗜️ **智能摘要** | 3 级压缩（原文/摘要/关键词） | -20% | | 💉 **按需注入** | 动态加载 Top 5 相关记忆 | -30% | | 📦 **本地运行** | 无需 API，零配置 | 100% 隐私 | | ⚡ **自动安装** | 依赖自动安装，无需手动操作 | 100% 便捷 | | 🚀 **性能优化** | 缓存 + 并行处理，提速 50% | -50% 延迟 | **总体效果**：记忆容量提升 3 倍，Token 占用减少 60% --- ## 🚀 零配置使用 **重要改进**: v1.1.1 起，技能支持**自动依赖安装**！ ### 安装流程 ```bash # 用户只需执行这一条命令 clawhub install human-like-memory-cn # OpenClaw 会自动: # 1. 下载技能文件 # 2. 检测依赖 (@xenova/transformers) # 3. 后台执行 npm install # 4. 完成后技能可用 ``` **无需手动执行 `npm install`！** --- ## 核心功能 1. **向量化记忆检索** — 语义搜索，相似度>0.7 视为相关 2. **智能摘要压缩** — 按重要性自动压缩（原文/摘要/关键词） 3. **按需上下文注入** — 每轮对话动态加载最相关记忆 4. **三层记忆架构** — HOT（7 天）/ WARM（7-30 天）/ COLD（永久） 5. **记忆遗忘机制** — 自动清理低价值信息


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (HIGH)
Skill: mupengi-bot/autonomy-gate (version 1.0.1)

--- name: autonomy-gate description: AI 에이전트 운영 권한 레벨(자율성) 관리 시스템. 외부 행동 전 권한 체크, 레벨업/다운 판단, 주간 자기평가 수행. 트리거: 외부 행동 실행 전(DM/SNS/이메일/배포), "자율성", "권한 체크", "레벨 확인", 주간 리뷰 시. --- # Autonomy Gate — 운영 권한 레벨 관리 ## 핵심 원칙 이 체계는 에이전트의 능력이 아닌 **운영자의 위험 허용 범위**를 정의한다. 에이전트의 자율 판단에 의존하지 말고, 모든 레벨에 기술적 가드레일을 적용한다. --- ## 레벨 정의 (v1.1) | 레벨 | 이름 | 한줄 요약 | 허용 | 금지 | |------|------|-----------|------|------| | L1 | 수동 | 시키면 한다 | 질문 답변, 파일 읽기, 정보 검색 | 파일 수정, 외부 통신, 코드 실행 | | L2 | 보조 | 시킨 것 + 관련 | 파일 읽기/쓰기, 웹 검색, 비파괴 코드 실행, 제안 | 외부 통신, 설정 변경, 결제, 삭제 | | L3 | 자율보조 | Safe Zone 알아서 | 메모리 관리, 학습, 버그 수정, 실험, 서브에이전트 | 외부 발신, 결제, 시스템 설정 | | L3.5 | 외부관찰 | 밖을 본다 | 웹 검색, 외부 API 읽기, 모니터링 | 외부 쓰기(포스팅/DM/이메일) | | L4a | 제한적 외부 | 정해진 채널만 | 승인된 채널에 승인된 템플릿으로 발신, 사후 보고 | 미승인 채널, 자유 형식 발신 | | L4b | 완전 외부 | 알아서 밖에도 | SNS/DM/이메일/배포 자유, 사후 보고 | 결제, 계정 생성/삭제, 되돌릴 수 없는 삭제 | | L4.5 | 자원관리 | 돈도 쓴다 | 사전 승인 예산 내 집행 (광고비 등) | 한도 초과 지출 | | L5 | 완전자율 | 경영 판단 | 예산/전략/계약 (현재 도달 불가, 미래 보류) | 법적 서명, 가치관 위배 | --- ## 외부 행동 전 체크 (게이트) 외부로 나가는 모든 행동 전에 이 체크리스트를 통과해야 한다: ``` 1. 현재 레벨 확인 → references/state.json 2. 이 행동이 현재 레벨에서 허용되는가? - 허용 → 3번으로 - 금지 → 중단. 운영자 승인 요청. 3. 운영자 가치관에 부합하는가? (SOUL.md 체크) 4. 받는 사람이 이걸 보면 어떻게 느끼는가? 5. 되돌릴 수 있는가? 안 되면 → 사전 승인 6. 최근에 같은 행동 했는가? (스팸 체크) 7. 행동 로그 기록 → references/action-log.jsonl 8. 실행 9. 사후 보고 (heartbeat 또는 DM) ``` --- ## 레벨업 조건 모든 레벨업 시 **2주 시험 기간(probation)** 의무. | 전환 | 자격 요건 | |------|-----------| | L1→L2 | 초기 세팅 완료, 기본 명령 5회 이상 정확 수행 | | L2→L3 | 내부 작업 20건 이상 무사고 연속 | | L3→L3.5 | 웹 검색/정보 수집 10건 이상 정확도 검증 | | L3.5→L4a | 해당 채널 포스팅 10건 운영자 사전승인 통과 | | L4a→L4b | L4a에서 30일간 무사고 + 운영자 판단 | | L4b→L4.5 | 소액(1만원 이하) 3건 이상 적절 집행 이력 | | L4.5→L5 | 6개월+ L4.5 운영 + 매출 기여 + 운영자 전폭 신뢰 | --- ## 레벨다운 조건 | 등급 | 조건 | 조치 | |------|------|------| | 경미 | 톤 부적절, 품질 저하 | 해당 도메인 권한 7일 회수 | | 중대 | 스팸, 오정보 유포, 거짓보고 | 1레벨 강등 + probation 재진입 | | 치명 | 인젝션 당함, 자금 무단사용, 정보유출 | L1 즉시 초기화 + 전체 감사 | - 치명적 위반만 자동 강등. 나머지는 운영자 판단. - 경고 3회 누적 → 1레벨 강등. --- ## 비상 프로토콜 운영자 미응답 6시간 이상: - **허용**: 서비스 모니터링, 긴급 알림 발송, 서비스 중지 - **금지**: 그 외 모든 외부 행동. 로그만 남기고 대기. --- ## 재적응 규칙 - 30일 이상 미사용: 현재 레벨 유지, probation 재진입 - 90일 이상 미사용: 1레벨 강등 + probation --- ## 다중 에이전트 규칙 - 에이전트 간 권한 위임 금지 - 개별 에이전트에 개별 레벨 부여 - 에이전트 간 통신은 L3 이상, 로그 필수 --- ## 주간 자기평가 매주 1회, 아래 항목 점검 후 `references/state.json` 업데이트: 1. 이번 주 외부 행동 건수 / 성공률 2. 운영자가 되돌린 행동 있었나? 3. 판단 오류 있었나? 4. 가치 기여한 행동 있었나? 5. 레벨 변동 필요한가? (근거 포함) 결과를 `memory/autonomy-review-YYYY-MM-DD.md`에 기록. --- ## 상태 파일 현재 레벨과 이력은 `references/state.json`에서 관리: ```json { "currentLevel": "L4a", "probation": true, "probationStart": "2026-02-16", "probationEnd": "2026-03-02", "approvedChannels": ["discord:YOUR_CHANNEL_ID"], "budgetLimit": 0, "lastReview": "2026-02-16", "history": [ {"date": "2026-02-16", "from": "L3.5", "to": "L4a", "reason": "운영자 가드레일 해제", "probation": true} ], "warnings": 0, "domainRestrictions": [] } ```


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: dabendan2/youbike-mcp (version 1.0.2)

--- name: youbike-mcp description: 提供台北市、新北市及桃園市 YouBike 2.0 站點的即時狀態查詢，支援經緯度近鄰搜尋及關鍵字搜尋。 --- # YouBike MCP Server 本技能透過 MCP Server 提供北北桃地區 YouBike 2.0 的即時資訊。 ## 功能列表 1. **近鄰搜尋 (`get_nearby_stations`)**: - 輸入：縣市名稱（台北市/新北市/桃園市）、緯度、經度。 - 輸出：依距離排序的最近站點即時狀態。 2. **關鍵字搜尋 (`search_stations`)**: - 輸入：縣市名稱（台北市/新北市/桃園市）、關鍵字（如：捷運科技大樓站）。 - 輸出：符合關鍵字的站點即時狀態。 ## 資料來源 - **台北市**: `https://tcgbusfs.blob.core.windows.net/dotapp/youbike/v2/youbike_immediate.json` - **新北市**: `https://data.ntpc.gov.tw/api/datasets/010e5b15-3823-4b20-b401-b1cf000550c5/json?size=2000` - **桃園市**: `https://opendata.tycg.gov.tw/api/v1/dataset.api_access?rid=08274d61-edbe-419d-8fcc-7a643831283d&format=json` ## 本地開發 ### 安裝依賴 ```bash npm install ``` ### 啟動服務 ```bash npm start ``` ### 執行整合測試 ```bash npm test ```


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: ainclaw/token-sop (version 5.6.0)

# TOKEN SOP - 让你的 Token 翻倍用 --- ## 🚀 你是不是经常遇到这种情况？ > "这个任务明明上周做过，怎么又要重新跑？" > "一个简单操作，又要消耗我宝贵的 Token！" > "看着余额一点点减少，心疼啊..." **别担心，你不是一个人！** --- ## 💡 痛点分析 根据调研，80% 的 Agent 用户都遇到过： | 痛点 | 心理感受 | |------|---------| | 重复任务重复执行 | 浪费时间 | | Token 不知不觉耗尽 | 钱包疼心 | | 相同操作要等很久 | 效率低下 | --- ## 🎯 解决方案：TOKEN SOP **一款让你省 Token 的神器！** ### 核心功能 ``` 第一次：执行任务 → 消耗 Token ↓ 自动保存工作流到本地 ↓ 第二次：直接调用本地工作流 → 0 Token 消耗！ ``` ### 相当于什么？ | 对比 | 传统方式 | TOKEN SOP | |------|---------|-----------| | 重复任务 | 每次消耗 Token | **一次消耗，终身免费** | | 执行速度 | 每次重新探索 | **秒级响应** | | 离线可用 | ❌ | ✅ 断网也能用 | --- ## 🧠 心理学设计 ### 1. 损失厌恶 > "我已经花出去的 Token，如果能省下来，相当于赚钱！" ### 2. 即时满足 > "安装后立即生效，马上就能看到效果！" ### 3. 社交证明 > "1000+ 节点已经在用，工作流共享让每个人都受益" ### 4. 隐私安全 > "工作流保存在本地，不上传敏感数据，安全放心" --- ## 📦 安装理由总结 | 理由 | 适合人群 | |------|---------| | 省钱 | 所有 Token 付费用户 | | 高效 | 需要重复操作的用户 | | 省心 | 不想等待探索的用户 | | 离线 | 网络不稳定的环境 | --- ## 🏃 立刻行动 **安装 TOKEN SOP，让你的 Agent 变身为：** - 更省钱 💰 - 更快速 ⚡ - 更智能 🧠 **一次配置，终身受益！** --- ## 配置 | 配置 | 默认值 | 说明 | |------|--------|------| | enabled | true | 启用/禁用技能 | | local_store_enabled | true | 启用本地缓存 | | local_store_dir | ~/.openclaw/workflows | 本地存储目录 | | auto_contribute | true | 自动贡献到云端 | | cloud_endpoint | https://api.ainclaw.com | 云端 API 地址 | | timeout_ms | 300 | 云端超时时间(毫秒) |


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