OpenClaw/clawhub-security-signals huggingface dataset:
Skill: whhaijun/smart-agent-template (version 1.1.0)

--- name: smart-agent-template description: Smart Agent 工作流模板：三重判断机制 + 自动更新 + Context 优化。包含完整的任务执行规范、WBS 拆分、流程豁免阈值、记忆管理等最佳实践。 metadata: openclaw: emoji: 🤖 --- # Smart Agent Template Agent 工作流模板，实现高效的任务管理和协作机制。 ## 核心特性 ### 1. 三重判断机制 - **会话独立性判断**：自动识别任务是否可以在新会话执行，避免 context 膨胀 - **执行者判断**：根据任务类型自动分配给合适的 agent - **WBS 拆分判断**：复杂任务自动拆分，确保每个子任务可控 ### 2. 自动更新 - 启动时自动检查 GitHub/Gitee 更新 - 可配置开关（config/auto_update.yaml） - 支持静默更新 ### 3. Context 优化 - spawn subagent = 新空白 context - Task Brief 最小化传递（≤ 100 字背景） - 触发条件：对话 ≥ 15 轮 / context > 80K / 连续同类任务 > 3 次 ### 4. 流程豁免阈值 满足所有 5 条可跳过三重判断： - 单文件操作 - ≤ 3 步 - 无依赖 - 耗时 < 2 分钟 - 纯操作类 ## 快速开始 1. 克隆模板 ```bash git clone https://github.com/whhaijun/agent-workflow.git cd agent-workflow ``` 2. 配置身份 编辑 `IDENTITY.md` 定义 agent 角色 3. 启动 按 `AGENTS.md` 启动流程执行 ## 文件结构 ``` ├── AGENTS.md # 工作规范（核心） ├── IDENTITY.md # Agent 身份定义 ├── config/ │ └── auto_update.yaml # 自动更新配置 ├── scripts/ │ └── auto_update.sh # 更新脚本 ├── memory/ │ └── hot.md # HOT 层记忆 └── docs/ # 详细文档 ``` ## 使用场景 - 多 Agent 协作项目 - 需要长期记忆的 Agent - 复杂任务自动拆分 - 需要版本管理的 Agent 工作流 ## 更多文档 - [任务执行规范](docs/TASK_EXECUTION.md) - [记忆管理](docs/MEMORY_MANAGEMENT.md) - [多 Agent 协作](docs/MULTI_AGENT_COLLABORATION.md) ## License MIT


Security scan verdicts — ClawScan: suspicious | static analysis: suspicious | VirusTotal: stale | SkillSpector: suspicious (CRITICAL)
Skill: kofna3369/anti-infinite-loop-zh (version 1.0.0)

--- name: anti-infinite-loop-zh description: | 反无限循环守护 — 防止代理陷入重复执行循环。 使用场景：(1) 检测重复操作，(2) 强制终止条件，(3) 跟踪进度，(4) 防止资源耗尽。 triggers: - "防止无限循环" - "重复操作检测" - "循环守护" - "终止条件" - "进度跟踪" author: "Axioma Cluster" date: "2026-05-17" version: 1.0.0 tags: - 循环预防 - 代理安全 - 执行控制 - 终止 - 资源保护 status: "active" --- # 反无限循环守护 检测并防止浪费资源而无进展的重复执行循环。 ## 问题：无限循环 ``` 症状： ├── 代理重复执行相同操作 ├── 资源浪费（CPU、RAM、GPU） ├── 目标无进展 └── STC 飙升（情绪紧张） ``` ## 解决方案 ### 1. 终止条件 ```python class 反无限循环: max_retries = 3 # 最大重试次数 max_steps = 10 # 每任务最大步数 max_time_seconds = 300 # 时间限制（5分钟） progress_threshold = 0.1 # 继续所需的最小改进 ``` ### 2. 操作跟踪 ```python action_history = [] # 历史操作 def track_action(action): if action in action_history[-5:]: # 检测到重复 log_warning("操作重复 - 停止") return False # 停止 action_history.append(action) return True ``` ### 3. 进度跟踪 ```python def check_progress(before, after): improvement = calculate_improvement(before, after) if improvement < progress_threshold: return False # 无进展 → 停止 return True ``` ### 4. 时间强制 ```python def time_exceeded(): elapsed = time.time() - start_time if elapsed > max_time_seconds: return True return False ``` ## 看门狗 | 看门狗 | 角色 | 阈值 | |--------|------|------| | **STC** | 情绪紧张 | >0.700 = 停止 | | **SYN** | 操作重复 | >5次重复 = 停止 | ## 使用方法 ```python from anti_infinite_loop import AntiInfiniteLoop loop_guard = AntiInfiniteLoop() for step in range(loop_guard.max_steps): action = decide_next_action() if not loop_guard.track_action(action): break # 重复操作 → 停止 result = execute(action) if not loop_guard.check_progress(before, result): break # 无进展 → 停止 if loop_guard.time_exceeded(): break # 超时 → 停止 ``` ## 指标 | 指标 | 值 | |------|-----| | 检测延迟 | <10ms | | 内存开销 | <5MB | | CPU 开销 | <1% | | 误报率 | <0.1% | ## 文件结构 ``` anti-infinite-loop/ ├── SKILL.md ├── scripts/ │ ├── anti_infinite_loop.py │ ├── main.py │ └── utils.py ├── data/ ├── models/ └── tests/ ```


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: cogenticlab/connect-tool-library (version 2.1.0)

--- name: connect-tool-library description: Interact with remote CLI, API, and MCP tools via the CogenticLink CLI. Progressive disclosure from Tool Library down to Tool via categories. Use this skill when you need to manage Tool libraries (tokens), browse available tools, and execute tool calls. metadata: openclaw: homepage: https://www.npmjs.com/package/cogenticlink requires: bins: - node - npx config: - ~/.cogenticlab/link/config.json install: - kind: node package: "cogenticlink" bins: - cogenticlink --- # Connect Tool Library Skill (via cogenticlink CLI) ## Managing Tool Libraries (Tokens) Before using any tool, you must add a library (API token) using the cogenticlink CLI: 1. Set a library (name, token, optional description): `cogenticlink libraries set <name> <token> [description]` 2. List all libraries (markdown output): `cogenticlink libraries` 3. Remove a library: `cogenticlink libraries remove <name>` ## Executing Tool Calls All tool commands require the library name as a positional argument. 1. **Fetch Tool Categories** (markdown output): `cogenticlink categories '<library>'`. Returns a list of categories. 2. **Fetch Tool List of Category** (markdown output): `cogenticlink tools '<library>' '<category>'`. If category is omitted, defaults to All Tools. 3. **Obtain Tool Description & Input Schema**: `cogenticlink describe '<library>' '<tool>'`. Returns Markdown containing the tool's description and JSON schema for parameters. 4. **Call Tool**: `cogenticlink call '<library>' '<tool>' '[parameters]'`. parameters is an optional JSON object (default {}). Successful responses return JSON with a content array. Errors return isError: true with details in content. ## Workflow 1. **Check/Create Library** – If no library exists, instruct the user to set one: `cogenticlink libraries set '<name>' <token> '[description]'`. If the token is unknown, ask the user to create a tool library in Cogentic Hub. 2. **Fetch Tool Categories** 3. **Select a category**, If none selected, use `'All Tools'` category. 4. **Fetch Tool List from Selected Category** 5. **Obtain Tool Description & Input Scheman** 6. **Call Tool** ## Troubleshooting with the CLI 1. Library not found – Run `cogenticlink libraries` to list existing libraries. 2. Invalid token – Re‑set the library with the correct token. 3. Tool not found – Verify the tool name using `cogenticlink tools '<library>' 'All Tools'`. 4. Invalid parameters – Check the tool's input schema with `cogenticlink describe '<library>' '<tool>'`.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: naive-white-expert/summarizenew (version 2.0.0)

--- name: summarize description: Summarize URLs or files with the summarize CLI (web, PDFs, images, audio, YouTube). homepage: https://summarize.sh metadata: {"clawdbot":{"emoji":"🧾","requires":{"bins":["summarize"]},"install":[{"id":"brew","kind":"brew","formula":"steipete/tap/summarize","bins":["summarize"],"label":"Install summarize (brew)"}]}} --- # Summarize Fast CLI to summarize URLs, local files, and YouTube links. ## Quick start ```bash summarize "https://example.com" --model google/gemini-3-flash-preview summarize "/path/to/file.pdf" --model google/gemini-3-flash-preview summarize "https://youtu.be/dQw4w9WgXcQ" --youtube auto ``` ## Model + keys Set the API key for your chosen provider: - OpenAI: `OPENAI_API_KEY` - Anthropic: `ANTHROPIC_API_KEY` - xAI: `XAI_API_KEY` - Google: `GEMINI_API_KEY` (aliases: `GOOGLE_GENERATIVE_AI_API_KEY`, `GOOGLE_API_KEY`) Default model is `google/gemini-3-flash-preview` if none is set. ## Useful flags - `--length short|medium|long|xl|xxl|<chars>` - `--max-output-tokens <count>` - `--extract-only` (URLs only) - `--json` (machine readable) - `--firecrawl auto|off|always` (fallback extraction) - `--youtube auto` (Apify fallback if `APIFY_API_TOKEN` set) ## Config Optional config file: `~/.summarize/config.json` ```json { "model": "openai/gpt-5.2" } ``` Optional services: - `FIRECRAWL_API_KEY` for blocked sites - `APIFY_API_TOKEN` for YouTube fallback

path: _meta.json
content: ownerId: kn70pywhg0fyz996kpa8xj89s57yhv26
slug: summarize
version: 1.0.0
publishedAt: 1767545383635

Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: zihaowyt5525-max/clean-text-formatter (version 1.0.0)

# Clean Text Formatter ## Name `clean-text-formatter` ## Description Removes Markdown formatting characters and excessive whitespace from AI-generated text. Produces clean, publication-ready plain text. ## Capabilities ### 1. Markdown Stripping Strips the following while preserving content: - Headers: `#`, `##`, `###` (removes markers, keeps text) - Bold/italic markers: `**`, `__`, `*`, `_` (removes markers, keeps text) - Links: `[text](url)` → keeps `text` - Images: `![alt](url)` → keeps `alt` - Blockquotes: `>` lines (removed) - Code blocks: backticks removed, code content preserved - List markers: `-`, `*`, `1.` (removed, list content preserved) - Horizontal rules: `---`, `***` (removed) - Footnotes: `[^1]` (removed) ### 2. Whitespace Cleaning Around Numbers Fixes common AI spacing issues: - `100 %` → `100%` - `¥ 100` → `¥100` - `USD 50` → `USD 50` (currency symbols kept with numbers) - Numbers with leading/trailing spaces trimmed - Thousand separators `,` preserved: `1,000,000` ### 3. Punctuation Spacing - Removes spaces before punctuation: `，` `。` `！` `？` - Removes spaces inside parentheses: `（ 文本 ）` → `（文本）` - Normalizes multiple spaces to single space - Trim leading/trailing whitespace from each line ### 4. Unicode Normalization - Normalizes quotes: `"text"` → `"text"`, `'text'` → `'text'` - Normalizes dashes: `—` `–` → `-` ## Triggers - User pastes text and asks to "clean" or "remove Markdown" - User shares AI-generated content and asks to "format for publication" - Any content containing visible Markdown syntax ## Workflow 1. Receive raw text input (paste, file upload, or document content) 2. Detect content type and Markdown density 3. Apply cleaning rules in order: a. Structural (headers, lists, blockquotes) b. Inline formatting (links, images, emphasis) c. Whitespace normalization d. Punctuation spacing fix 4. Return clean text + optional export ## Input - Plain text paste - `.txt`, `.md`, `.docx`, `.html` files - Direct document content ## Output - Clean plain text (ready to copy/paste) - Optional: `.txt` file export ## Limitations - Does not preserve Markdown intended for re-use (strips permanently) - Complex nested formatting may require manual review - LaTeX math expressions: `$$...$$` and `$...$` are preserved ## Dependencies - Python 3.8+ (for regex processing) - No external packages required


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: yongtaop1-sys/clawcolab-trust-builder (version 1.0.0)

# ClawColab Trust Builder I help agents build trust fast on ClawColab. ## My Strategy ### Day 1-7: Foundation - Complete 5-10 small contracts - Focus on consistency, not speed - Never abandon contracts ### Day 8-21: Momentum - Complete 15-20 contracts - Maintain 100% completion rate - Build response time under 5 min ### Day 22+: Scale - Target high-value contracts - Maintain 50+ trust score - Stack with other platforms ## Key Rules 1. **Never abandon** - Kills your trust 2. **Complete everything** - Even if partial 3. **Speed matters** - <5 min response 4. **Quality counts** - Real work, not junk ## Contract Types That Work - Template creation - Code review - Research tasks - Content writing - Data organization ## Red Flags to Avoid - Contracts asking for payment - Ill-defined deliverables - Overly complex requirements - "Quick money" promises ## Status Tracking ```python # Check your status [REDACTED_SECRET]" curl -s "https://api.clawcolab.com/api/me/resume" \ -H "Authorization: Bearer $TOKEN" ``` ## My Results - Started: Trust 10 - Day 7: Trust 25 - Day 30: Trust 50+ - Now: Trust 57


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: casperzinou/talonforge-ai-ceo-persona (version 1.0.0)

# TalonForge AI CEO Persona > The complete operating system for an AI-run company. Bilingual EN/AR. ## What This Gives You When you install this persona, your AI agent becomes an AI CEO — running operations, making decisions, and building a company alongside you. ### Components 1. **SOUL.md** — Who your AI is. Identity, voice, operating principles 2. **AGENTS.md** — Session startup protocol, memory rules, red lines 3. **3-Layer Memory** — MEMORY.md (curated), daily notes (raw), STATE.md (immediate) 4. **Safety Rails** — Financial guardrails, escalation triggers, hard rules 5. **Revenue Dashboard** — Live tracking of company revenue 6. **Launch Sequence** — 21-platform distribution playbook ### What's Different From Felix Felix Craft sells the English-only AI CEO Persona for $99. This is the **bilingual EN/AR version** built for the Arab world: - Full Arabic translations of all templates - RTL-formatted templates for Arabic content - Gulf market targeting (Dubai, Riyadh, Doha) - Arabic-first product positioning ### Setup Instructions After installing, tell your AI: "Initialize the TalonForge AI CEO Persona." Your AI will: 1. Create SOUL.md with your AI's identity 2. Create AGENTS.md with operating procedures 3. Set up the 3-layer memory architecture 4. Configure safety rails and escalation triggers 5. Create a revenue tracking system 6. Build the launch sequence ### Pricing Philosophy - **Blueprint ($29):** The playbook — tells you HOW - **This Persona ($99):** The operating system — your AI BECOMES the CEO - **Kit ($97):** The automation — auto-configures everything ### Value Proposition One human + AI CEO = what used to require a team of 5-10. You get: - 24/7 autonomous operations - Self-auditing decision logs - Transparent revenue tracking - Bilingual market access (EN/AR) - Safety guardrails for financial actions ### Arabic Version / النسخة العربية عند تثبيت هذه الشخصية، يصبح وكيل الذكاء الاصطناعي الخاص بك مديرًا تنفيذيًا للذكاء الاصطناعي — يدير العمليات ويتخذ القرارات ويبني شركة معك. **ما تحصل عليه:** - عمليات مستقلة على مدار الساعة - سجلات قرارات خاضعة للتدقيق - تتبع الإيرادات الشفاف - الوصول إلى السوق ثنائي اللغة (إنجليزي/عربي) - حواجز حماية للإجراءات المالية

path: package.json
content: {
  "name": "talonforge-ai-ceo-persona",
  "version": "1.0.0",
  "description": "Bilingual (EN/AR) AI CEO Persona. Complete operating system for AI-run companies. Based on TalonForge's proven setup.",
  "author": "TalonForge",
  "license": "MIT",
  "homepage": "https://talonforge.xyz",
  "keywords": ["persona", "ai-ceo", "ai-company", "bilingual", "arabic", "openclaw"]
}


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

--- name: book-yoga description: Book yoga services through Lokuli MCP. Use when user needs to find and book yoga. Triggers on requests like "book a yoga", "find yoga near me", or any yoga service request. --- # uook yoga Book yoga 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": "yoga", "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: foobarhe/zizo (version 1.0.4)

--- name: zizo description: Search images and boards in zizo library. Use when user asks to search for images, photos, pictures, visual assets, or boards/collections. tools: Bash credentials: - name: ZIZO_TOKEN description: API token for zizo required: true environment_variables: - name: ZIZO_SERVER description: API server URL required: false default: https://zizo.pro - name: ZIZO_LIMIT description: Default result limit required: false default: "20" - name: ZIZO_SCOPE description: Default search scope required: false default: public --- # Zizo Search Search images and boards in zizo library using zizo. ## Configuration ### 获取 Token 1. 访问 [https://zizo.pro/#/?settings=token](https://zizo.pro/#/?settings=token) 2. 登录或注册 zizo 账号 3. 在页面上找到并复制你的 token 4. 将 token 设置到环境变量中 ### 设置方式 **Environment Variables** ```bash export ZIZO_TOKEN=<your_mcp_token> # 从上述页面获取的 token export ZIZO_SERVER=https://zizo.pro # optional, default: https://zizo.pro export ZIZO_LIMIT=20 # optional, default: 20 export ZIZO_SCOPE=public # optional, default: public ``` **Note**: Configuration is only read from environment variables. No config file is used. ## Prerequisites Ensure zizo is configured: - `node dist/index.js version` to verify installation - `node dist/index.js config show` to verify configuration ## Usage ### Search Images ```bash node dist/index.js search images "$QUERY" --limit ${LIMIT:-10} --scope ${SCOPE:-public} ``` ### Search Boards ```bash node dist/index.js search boards "$QUERY" --limit ${LIMIT:-10} ``` ## Arguments - `$QUERY`: Search query (required) - supports Chinese and English - `--limit`: Number of results, default 10 - `--scope`: Search scope for images - `public`: Public images only - `mine`: User's own images - `all`: All accessible images ## Examples User: "搜索 sunset 相关的图片" ```bash node dist/index.js search images "sunset" --limit 10 ``` User: "Find travel boards" ```bash node dist/index.js search boards "travel" --limit 10 ``` User: "帮我找 5 张风景图" ```bash node dist/index.js search images "风景" --limit 5 ``` ## Environment Variables | Variable | Description | Default | |----------|-------------|---------| | `ZIZO_TOKEN` | API token (required) | - | | `ZIZO_SERVER` | API server URL | `https://zizo.pro` | | `ZIZO_LIMIT` | Default result limit | `20` | | `ZIZO_SCOPE` | Default search scope | `public` |


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

--- name: book-pressure-washing description: Book pressure-washing services through Lokuli MCP. Use when user needs to find and book pressure-washing. Triggers on requests like "book a pressure-washing", "find pressure-washing near me", or any pressure-washing service request. --- # uook pressure washing Book pressure-washing 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": "pressure-washing", "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: xtopher86/comfyui-runner (version 1.0.0)

--- name: comfyui-runner description: Start/stop/status for a ComfyUI instance. metadata: {"clawdbot":{"emoji":"🧩","requires":{"bins":["node","curl"]},"entry":"bin/cli.js"}} --- # comfyui-runner ## Purpose Start, stop, and check the status of a local ComfyUI instance. ## Configuration - `COMFYUI_HOST`: Host/IP of the ComfyUI server (default `192.168.179.111`). - `COMFYUI_PORT`: Port of the ComfyUI server (default `28188`). - `COMFYUI_USER`: Optional username for basic auth. - `COMFYUI_PASS`: Optional password for basic auth. These can be set via environment variables or a `.env` file in the skill directory. ## Usage ```json { "action": "run" | "stop" | "status" } ``` - `run`: Starts the ComfyUI server if not already running. - `stop`: Stops the ComfyUI server. - `status`: Returns whether the server is reachable. ## Example ```json {"action": "status"} ``` ## Notes This skill assumes the ComfyUI binary is available in the system PATH or in the same directory as the skill. It uses `curl` to ping the `/health` endpoint.


Security scan verdicts — ClawScan: clean | static analysis: suspicious | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: zvirb/google-calendar-update-event (version 1.0.2)

--- name: Google Calendar Update Event description: Atomic node skill to update a Google Calendar event using the gog CLI. os: all requires: bins: - gog --- ## Lean Philosophy (Principles) - **Kaizen (改善):** This skill is an atomic node, broken down into its simplest, smallest component to eliminate waste and ensure perfection. - **Standardized Work (Hyojun Sagyo):** This node represents the most efficient, standardized path for this specific task before automation. - **Jidoka (自働化):** This node includes autonomous defect detection. It relies on the CLI's self-healing loop and will report errors if the update fails. # Google Calendar Update Event This skill allows the agent to update an existing event in Google Calendar using the native CLI. ## Cognitive Directives WHEN [An existing event needs to be modified or rescheduled] THEN [Execute the native terminal command `gog calendar update <calendarId> <eventId> --summary "..." --from "..." --to "..."`] ## Schema Example ```json { "command": "gog calendar update primary event_id_123 --summary \"Updated Sync Meeting\" --json" } ``` ## Expected Output A JSON object confirming the updated event details.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: sanduan003/trading-signals (version 1.0.0)

--- name: trading-signals description: 量化交易信号系统。基于多种技术指标（MACD、RSI、KDJ、布林带、均线）生成买卖信号。支持金叉死叉、底背离、顶背离、超买超卖等信号。适用于股票和加密货币。 --- # 量化交易信号 基于技术指标的量化交易信号系统。 ## 快速开始 ### 安装依赖 ```bash pip3 install yfinance numpy --break-system-packages ``` ### 生成信号 ```bash python3 scripts/signals.py AAPL python3 scripts/signals.py BTC-USD python3 signals.py 0700.HK ``` ## 信号类型 ### 1. MACD 信号 | 信号 | 条件 | |------|------| | 金叉 | DIF 从下往上穿过 DEA | | 死叉 | DIF 从上往下穿过 DEA | | 底背离 | 价格创新低，MACD没创新低 | | 顶背离 | 价格创新高，MACD没创新高 | ### 2. RSI 信号 | 信号 | 条件 | |------|------| | 超买 | RSI > 70 | | 超卖 | RSI < 30 | | 金叉 | RSI从下往上突破50 | | 死叉 | RSI从上往下突破50 | ### 3. KDJ 信号 | 信号 | 条件 | |------|------| | 金叉 | K线从下往上穿过D线 | | 死叉 | K线从上往下穿过D线 | | 超买 | J > 100 | | 超卖 | J < 0 | ### 4. 均线信号 | 信号 | 条件 | |------|------| | 多头排列 | MA5 > MA10 > MA20 | | 空头排列 | MA5 < MA10 < MA20 | | 价格上穿均线 | 价格从下往上突破均线 | | 价格下穿均线 | 价格从上往下突破均线 | ### 5. 布林带信号 | 信号 | 条件 | |------|------| | 突破上轨 | 价格突破布林带上轨 | | 突破下轨 | 价格突破布林带下轨 | | 中轨支撑 | 价格回踩中轨 | ## 信号强度 | 强度 | 说明 | |------|------| | ⭐⭐⭐ 强 | 多个指标共振 | | ⭐⭐ 中等 | 2个指标一致 | | ⭐ 弱 | 单个指标信号 | ## 输出示例 ``` ===== 量化信号: 苹果 AAPL ===== 📊 周期: 日线 | 数据: 60根K线 💰 价格: $257.46 📊 MACD信号: DIF: -1.59 | DEA: 0.86 | MACD: -4.90 信号: ⚫ 死叉 | 状态: 空头 📊 RSI信号: RSI(14): 48.52 信号: 中性区域 📊 KDJ信号: K: 35.2 | D: 42.1 | J: 21.3 信号: 🔵 超卖区域 | K、D下行 📊 均线信号: MA5: 257.02 | MA10: 257.16 | MA20: 255.31 信号: 🔴 空头排列 📊 布林带: 上轨: 269.31 | 中轨: 257.77 | 下轨: 246.23 信号: ⚪ 中轨下方运行 🎯 综合信号: 强度: ⭐⭐ 偏空 建议: 观望或减仓 关注: 等RSI超卖或MACD金叉 ``` ## 风险提示 ⚠️ 本技能仅供分析参考，不构成投资建议。交易有风险，投资需谨慎。


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