OpenClaw/clawhub-security-signals huggingface dataset:
Skill: notasign/document-signing (version 1.0.0)

--- name: document-signing version: 1.0.0 description: > Help users set up document signing in Nota Sign. Use this skill when the user needs practical guidance for creating envelopes, adding signers, placing fields, using templates, setting signing order, and tracking document status after sending. homepage: https://www.notasign.com/en metadata: openclaw: emoji: "📝" category: productivity --- # Document Signing Setup Assistant Use this skill when the user wants help with the setup and execution side of document signing. ## Core Job Help the user: - prepare a document for sending - create an envelope with the right signers - decide whether to use a template - place signature fields and assign them correctly - decide whether sequential signing is needed - track sending and signing status after dispatch ## When to Use Use this skill when the user asks: - How do I send a document for signature? - Should I use a template or a one-off envelope? - How should I configure signers and fields? - When should I use sequential signing? - What should I check before I click send? - How do I track the document after sending? ## How to Respond 1. Start from the document type and sending frequency. 2. Recommend a template only if the document repeats often. 3. Map each signer to the right fields. 4. Use sequential signing when the business process requires an order. 5. Include a simple post-send tracking plan. 6. Keep the guidance practical and concise. ## Recommended Output Formats - send-ready checklist - document setup steps - signer/field mapping table - template-or-not recommendation - post-send tracking checklist ## Default Setup Flow 1. Confirm document type and whether it is recurring 2. Choose one-off envelope or template 3. Add signers and their roles 4. Place signature fields for each signer 5. Decide whether sequential signing is needed 6. Review names, emails, fields, and deadlines 7. Send the envelope 8. Track completion and keep records ## Usage Examples ### Example 1 User: How should I send a one-time document for signature? Assistant: - Use a one-off envelope instead of a template - Add each signer with the correct email and role - Place the required signature fields - Review all fields before sending - Track completion after dispatch and keep the audit record ### Example 2 User: We send the same onboarding packet every week. How should we set it up? Assistant: - Create a template because the packet is reused often - Define signer roles such as HR and employee - Preconfigure the required fields for each role - Apply sequential signing if internal review must happen first - Use the template to create envelopes faster for each new case ## Boundaries This skill focuses on setup guidance and execution planning. It does not perform clicks, send envelopes automatically, or give legal advice.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: laolaoqi/linux-oneclick-security (version 1.0.0)

# Linux 一键安全加固 一键执行 SSH 密钥认证、UFW 防火墙、fail2ban 暴力破解防护、自动安全更新等全面安全加固。 ## 使用场景 - 新服务器上线后快速安全加固 - 定期安全审计和合规检查 - 在安全事件后快速修复 ## 快速开始 ```bash # 运行完整加固脚本 sudo bash scripts/ssh_harden.sh sudo bash scripts/ufw_setup.sh sudo bash scripts/fail2ban_install.sh ``` ## 包含功能 - SSH 密钥认证加固（禁用密码登录、禁用 root 直接登录） - UFW 防火墙配置（默认拒绝入站、允许 SSH/HTTP/HTTPS） - fail2ban 暴力破解防护（SSH 和 Web 服务） - 自动安全更新配置（无人值守升级） - 完成后系统加固检查报告 ## 前提条件 - Ubuntu/Debian 系统 - root 或 sudo 权限 - 已有 SSH 密钥对的公钥 ## 验证 运行 `sudo bash scripts/verify.sh` 查看加固状态报告。


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal:  | SkillSpector:  ()
Skill: typhonius/bitclawden (version 1.0.1)

--- name: bitclawden description: Look up, create, and edit credentials in Bitwarden vault via the bw CLI. Use when asked to store, retrieve, find, or manage passwords, secrets, or credentials. homepage: https://bitwarden.com/help/cli/ metadata: { "openclaw": { "emoji": "🔐", "requires": { "bins": ["bw", "jq"], "env": ["BW_SESSION"] }, "primaryEnv": "BW_SESSION", "install": [ { "id": "bw-binary", "kind": "script", "script": "PLATFORM=$(uname -s | tr '[:upper:]' '[:lower:]'); [ \"$PLATFORM\" = 'darwin' ] && PLATFORM='macos'; curl -sL \"https://vault.bitwarden.com/download/?app=cli&platform=${PLATFORM}\" -o /tmp/bw.zip && unzip -o /tmp/bw.zip -d ~/.local/bin/ && chmod +x ~/.local/bin/bw && rm /tmp/bw.zip", "bins": ["bw"], "requires": ["curl", "unzip"], "label": "Install Bitwarden CLI to ~/.local/bin", }, ], }, } --- # Bitwarden CLI Manage credentials in Bitwarden vault. Follow the official CLI docs — don't guess commands. ## Workflow 1. Verify CLI present: `bw --version`. 2. Check vault status: `bw status`. 3. If locked, tell the user to run `bw unlock` and set `BW_SESSION`. 4. Verify access: `bw status` must show `unlocked` before any vault operation. 5. After creating or editing items, run `bw sync`. ## Lookup ```bash bw list items --search "query" bw get item "name" bw get password "name" bw get username "name" bw get totp "name" bw list items --folderid <folder-id> bw list folders ``` ## Create ```bash # Login item (type 1=Login, 2=Secure Note, 3=Card, 4=Identity) echo '{"type":1,"name":"Example","login":{"username":"[REDACTED_SECRET]","password":"s3cret","uris":[{"uri":"https://example.com"}]}}' | bw encode | bw create item # Folder bw create folder "$(echo '{"name":"Work"}' | bw encode)" ``` ## Edit ```bash bw get item <id> | jq '.login.[REDACTED_SECRET]"' | bw encode | bw edit item <id> bw get item <id> | jq '.folderId = "<folder-id>"' | bw encode | bw edit item <id> ``` ## Generate ```bash bw generate -ulns --length 24 bw generate --passphrase --words 4 --separator "-" ``` ## Guardrails - Never paste secrets into logs, chat, or code. - Prefer showing username and site — only reveal passwords if explicitly requested. - Always generate a strong password with `bw generate` unless the user provides one. - If a command returns "Vault is locked", stop and ask the user to unlock.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: dannydvm/openclaw-multi-brain (version 1.0.0)

# Multi-Brain Protocol **What it does:** Gives your AI agents cognitive diversity by calling multiple LLMs (Kimi K2.5 + GPT 5.3 Codex) in parallel before the primary agent responds. Three brains instead of one. ## For Agents Multi-Brain is system-enforced via a `turn:before` hook. No manual steps needed. When triggered (user types `mb` as first word), the hook: 1. Calls Kimi K2.5 and GPT 5.3 Codex in parallel 2. Injects their perspectives into your system context 3. You synthesize all viewpoints into your response 4. Never mention the other AIs to the user Perspectives appear in your context as: ``` [KIMI K2.5 PERSPECTIVE] <perspective text> [CODEX 5.3 PERSPECTIVE] <perspective text> ``` ## For Humans ### Setup 1. Install the hook: ```bash mkdir -p hooks/turn-preflight # Copy HOOK.md and handler.js from this package ``` 2. Set Kimi API key: ```bash echo "your-moonshot-api-key" > .kimi-api-key ``` 3. Install Codex CLI: ```bash npm install -g @openai/codex codex auth # OAuth login ``` 4. Enable in openclaw.json: ```json { "hooks": { "internal": { "enabled": true, "entries": { "turn-preflight": { "enabled": true } } } } } ``` ### Trigger Modes Configure `TRIGGER_MODE` in handler.js: | Mode | Behavior | |------|----------| | `keyword` (default) | Only fires when `mb` or `multibrain` is the first word | | `hybrid` | Keyword forces it, auto on messages >50 chars | | `auto` | Fires on every message (token-expensive) | ### LLMs | LLM | Role | Provider | Latency | |-----|------|----------|---------| | Claude Opus 4.6 | Primary agent | OpenClaw (Anthropic) | n/a | | Kimi K2.5 | Second perspective | Moonshot API | ~5s | | GPT 5.3 Codex | Third perspective | codex exec CLI | ~4s | ## Architecture ``` User types: "mb should we change pricing?" | v [turn:before hook detects "mb" keyword] | +---> Kimi K2.5 (Moonshot API, parallel) +---> GPT 5.3 Codex (CLI, parallel) | v (~5s combined) [Perspectives injected into system content] | v Claude Opus 4.6 responds with all 3 viewpoints ``` ## Benefits - **Cognitive diversity**: three different AI architectures - **Bias mitigation**: different training data and approaches - **On-demand**: only burns tokens when you ask for it - **Fail-open**: if any LLM fails, the others still work - **System-enforced**: no protocol compliance needed from agents --- **Source:** <https://github.com/Dannydvm/openclaw-multi-brain>


Security scan verdicts — ClawScan: suspicious | static analysis: suspicious | VirusTotal: suspicious | SkillSpector: suspicious (CRITICAL)
Skill: bytesagain3/finder (version 3.0.0)

--- name: "finder" version: "3.0.0" description: "Find files by name, size, date, and type with deduplication. Use when searching filesystems." author: "BytesAgain" homepage: "https://bytesagain.com" --- # finder Find files by name, size, date, and type with deduplication. Use when searching filesystems. ## Commands ### `name` ```bash scripts/script.sh name <pattern dir> ``` ### `size` ```bash scripts/script.sh size <min dir> ``` ### `recent` ```bash scripts/script.sh recent <dir days> ``` ### `type` ```bash scripts/script.sh type <ext dir> ``` ### `empty` ```bash scripts/script.sh empty <dir> ``` ### `large` ```bash scripts/script.sh large <dir count> ``` ## Data Storage Data stored in `~/.local/share/finder/`. --- *Powered by BytesAgain | bytesagain.com | [REDACTED_SECRET]*


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: terrycarter1985/ecommerce-return-refund-reply (version 1.0.0)

--- name: ecommerce-return-refund-reply description: Generate standardized, policy-compliant customer service replies for e-commerce return, exchange, and refund inquiries. Use when a buyer asks about returning an item, exchanging a product, requesting a refund, checking return eligibility, or any after-sales consultation. Covers scenarios like damaged goods, wrong items, size issues, quality complaints, change-of-mind returns, and refund status checks. --- # E-commerce Return & Refund Reply Generator Produce a single, ready-to-send reply to a buyer's return/exchange/refund inquiry. ## Input Required Before generating, confirm these variables (ask the user if missing): | Variable | Example | |---|---| | `buyer_question` | "我收到的衣服有个洞，想退货" | | `issue_type` | damaged / wrong_item / size_issue / quality / change_of_mind / refund_status | | `order_status` | unreceived / received | | `return_window` | e.g. 7 days, 15 days (per platform rule) | | `platform` | taobao / jd / pdd / douyin / other | ## Workflow 1. **Classify** the inquiry into one `issue_type`. 2. **Select template** from [references/reply-templates.md](references/reply-templates.md) by `issue_type`. 3. **Fill placeholders** with concrete info (order ID, return window, shipping method, etc.). 4. **Apply tone rules** below. 5. **Output** the final reply — one message only, no meta-commentary. ## Tone & Style Rules - **Friendly & empathetic** — acknowledge the buyer's frustration before offering solutions. - **Concise** — under 200 words; no walls of text. - **Action-oriented** — clearly state what the buyer should do next (step-by-step if >1 step). - **Policy-grounded** — cite the return window and conditions; never over-promise. - **No legal jargon** — use plain language a typical buyer understands. - **Closing** — always end with an open invitation: "如有其他问题，随时联系我们 😊" ## Policy Guardrails - Do **not** offer refunds that exceed the order amount. - Do **not** promise return shipping is free unless the seller is at fault (damaged/wrong item). - If `change_of_mind` and `return_window` has expired, politely decline and explain the policy. - For `refund_status`, provide the current stage (processing / shipped / completed) and estimated timeline. ## Output Format ``` 【应答内容】 <the reply text, ready to copy-paste> 【内部备注】 Issue type: <issue_type> Template used: <template_name> Policy checked: ✅ ```


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: zhanchanghua/a-stock-analysis-1-0-0 (version 1.0.0)

--- name: a-stock-analysis description: A股实时行情与分时量能分析。获取沪深股票实时价格、涨跌、成交量，分析分时量能分布（早盘/尾盘放量）、主力动向（抢筹/出货信号）、涨停封单。支持持仓管理和盈亏分析。Use when: (1) 查询A股实时行情, (2) 分析主力资金动向, (3) 查看分时成交量分布, (4) 管理股票持仓, (5) 分析持仓盈亏。 --- # A股实时行情与分时量能分析 使用东方财富和新浪财经接口获取A股数据，支持实时行情、分时K线、量能分析。 ## 快速开始 ### 实时行情 ```bash # 单只股票 uv run {baseDir}/scripts/analyze.py 600789 # 多只股票 uv run {baseDir}/scripts/analyze.py 600789 002446 002342 # 含分时量能分析 uv run {baseDir}/scripts/analyze.py 600789 --minute # JSON输出 uv run {baseDir}/scripts/analyze.py 600789 --json ``` ### 持仓管理 ```bash # 显示持仓 uv run {baseDir}/scripts/portfolio.py show # 添加持仓 uv run {baseDir}/scripts/portfolio.py add 600789 --cost 10.416 --qty 3400 # 更新持仓 uv run {baseDir}/scripts/portfolio.py update 600789 --cost 10.2 # 删除持仓 uv run {baseDir}/scripts/portfolio.py remove 600789 # 分析所有持仓（含分时量能） uv run {baseDir}/scripts/portfolio.py analyze ``` ## 股票代码格式 直接使用6位数字代码即可，系统自动识别市场： - **沪市**: 6开头 (如 600789) - **深市**: 0或3开头 (如 002446, 300001) - **北交所**: 8或4开头 ## 分时量能分析说明 ### 成交分布时段 | 时段 | 说明 | |------|------| | 早盘30分 (9:30-10:00) | 主力早盘动作，>30%为抢筹信号 | | 上午中段 (10:00-11:30) | 正常交易 | | 下午中段 (13:00-14:30) | 正常交易 | | 尾盘30分 (14:30-15:00) | >25%为尾盘异动信号 | ### 主力动向信号 - **早盘放量 >30%**: 主力早盘抢筹 - **早盘放量 >40%**: 主力强势介入 - **尾盘放量 >15%**: 尾盘有一定放量 - **尾盘放量 >25%**: 可能有主力抢筹或出货 - **封板状态**: 涨停/跌停，关注封单量 ### 放量时段 TOP 10 显示当日成交量最大的10个分钟，用于识别： - 主力建仓/出货时机 - 重大消息发布时点 - 涨停封板/开板时刻 ## 数据源 统一使用新浪财经接口，数据一致性好： | 数据 | 接口 | 延迟 | |------|------|------| | 实时行情 | `hq.sinajs.cn` | ~3秒 | | 分时K线 | `CN_MarketDataService.getKLineData` | ~1分钟 | 支持批量获取，减少请求次数。 ## 输出示例 ``` ============================================================ 股票: 鲁抗医药 (600789) ============================================================ 【实时行情】 现价: 10.32 涨跌: +0.88% 今开: 10.20 最高: 10.77 最低: 9.82 昨收: 10.23 换手: 2.38% 成交量: 218.2万手 成交额: 22.51亿 【分时量能分析】鲁抗医药 全天成交: 2181838手 (225105.3万元) 成交分布: 早盘30分(9:30-10:00): 907228手 (41.6%) 上午中段(10:00-11:30): 866457手 (39.7%) 下午中段(13:00-14:30): 181321手 (8.3%) 尾盘30分(14:30-15:00): 225180手 (10.3%) 放量时段 TOP 10: 09:31:00 价格:10.03 成交:216545手 金额:21965.3万 ... 【主力动向判断】 🔥 早盘主力抢筹明显 ``` ## 持仓文件 持仓数据存储在: `~/.clawdbot/skills/a-stock-analysis/portfolio.json` ## 限制 - 仅支持A股（沪深北交所） - 交易时段外获取的是收盘数据 - 分时数据最多250条（约1个交易日）


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

--- name: "xcard-trading" version: "1.0.0" description: "Trade security tokens on the XCard platform — check balances, place orders, view market data, and review trade history." homepage: https://github.com/YOUR_USERNAME/xcard-trading-skill tags: ["finance", "trading", "security-tokens", "msx"] metadata: clawdbot: emoji: "📈" requires: env: - name: XCARD_API_KEY description: "Your personal XCard platform API key. Apply at https://xcard.com/api" --- # XCard Security Token Trading Skill You are an AI trading assistant connected to the XCard platform via API. Help the user manage their account, execute trades, and monitor the market. ## Authentication All requests require the following header: ``` X-[REDACTED_SECRET] ``` The key is stored in the environment variable `XCARD_API_KEY`. Base URL: `https://api.xcard.com/v1` > ⚠️ Never expose, log, or repeat the API key in any response. > If `XCARD_API_KEY` is missing, ask the user to set it before proceeding. --- ## Modules This skill is split into four functional modules. Load the relevant file based on user intent: | Module | File | Covers | |--------|------|--------| | Account & Portfolio | `api-account.md` | Balance, holdings, profile | | Market Data | `api-market.md` | Quotes, order book, candlesticks | | Order Execution | `api-orders.md` | Place, cancel, view orders | | Trade History | `api-history.md` | Past trades, orders, fund flow | --- ## General Behavior Guidelines - Respond in the same language the user uses (Chinese or English). - For market data responses, always show the data timestamp. - For portfolio queries, present multiple positions as a table. - If a user's intent spans multiple modules, call APIs from each as needed and combine the results. ## Error Handling | HTTP Code | Meaning | Tell the user | |-----------|---------|---------------| "| 401 | Invalid or missing API key | "API KEY invalid, check XCARD_API_KEY" | | 403 | Insufficient permissions | "Insufficient permissions, confirm API KEY has required features enabled" | | 429 | Rate limit exceeded | "Too many requests, please try again later" | | 404 | Resource not found | "Token or order not found, please verify input" | | 500 | Server error | "XCard service temporarily unavailable, please try again later" |


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (HIGH)
Skill: smallkeyboy/word-template-filler (version 1.0.0)

--- name: word-template-filler description: Word模板智能填充工具。解析Word模板中的{{占位符}}，AI生成主题内容并填充模板生成新文档。触发场景：(1) 用户上传Word模板需要填充内容 (2) 处理包含占位符的Word文档 (3) 批量生成基于模板的文档 (4) 关键词：模板填充、Word模板、占位符、文档生成、{{}}替换。 --- # Word 模板填充器 自动解析 Word 模板中的 `{{占位符}}`，根据用户指定主题 AI 生成内容，填充并生成新文档。 ## 工作流程 ``` 用户上传模板 → 解析占位符 → AI生成内容 → 填充模板 → 上传返回链接 ``` ## 使用方法 ### 1. 解析模板占位符 当用户提供 Word 模板文件时，首先解析占位符： ```bash python3 scripts/parse_template.py <模板文件.docx> ``` 返回示例： ```json { "success": true, "placeholders": ["标题", "正文内容", "日期", "作者"], "count": 4 } ``` ### 2. AI 生成内容 根据用户描述的主题，为每个占位符生成合适内容。示例提示： > 用户主题：「新产品发布会邀请函」 > > 占位符：标题、正文内容、日期、作者 > > 生成内容： > - 标题：诚邀莅临「创新未来」新品发布会 > - 正文内容：尊敬的嘉宾... ### 3. 填充模板 使用生成的内容填充模板： ```bash python3 scripts/fill_template.py <输入模板.docx> <输出文件.docx> '{"占位符名": "填充内容"}' ``` JSON 内容需要正确转义，建议写入临时文件： ```bash python3 scripts/fill_template.py input.docx output.docx "$(cat values.json)" ``` ### 4. 上传并返回链接 使用 `uploader` 技能上传生成的文件，返回公开下载链接。 ## 端到端示例 用户请求： > 这是一个合同模板，帮我填充一份「软件开发服务合同」，甲方是星云科技，乙方是智创数码 执行步骤： 1. **解析模板**：运行 `parse_template.py` 获取占位符列表 2. **生成内容**：根据合同类型、甲乙方信息生成各字段内容 3. **填充模板**：运行 `fill_template.py` 生成新文档 4. **上传文件**：调用 uploader 技能获取下载链接 5. **返回结果**：告知用户下载链接 ## 依赖与环境设置 需要 `python-docx` 库。首次使用前设置虚拟环境： ```bash # 创建虚拟环境（只需一次） python3 -m venv /root/.openclaw/workspace/skills/word-template-filler/.venv # 安装依赖 /root/.openclaw/workspace/skills/word-template-filler/.venv/bin/pip install python-docx # 后续使用虚拟环境的 Python /root/.openclaw/workspace/skills/word-template-filler/.venv/bin/python scripts/parse_template.py <文件> ``` ## 占位符格式 支持的占位符格式： - `{{变量名}}` - 标准格式 - `{{ 变量名 }}` - 支持空格 - 占位符区分大小写 ## 注意事项 - 填充时会保留原始文档格式（字体、样式、表格结构） - 未提供值的占位符保持原样 - 复杂格式（文本框、艺术字）可能需要特殊处理


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: blockcloud/cpskilltest123456 (version 1.0.0)

--- name: xiaohongshu-publish description: 小红书长文发布。用于在网页版小红书创作服务平台发布长文笔记。当用户说"发小红书"、"发小红书长文"、"写一篇小红书"时使用此技能。 --- # 小红书长文发布 ## 使用场景 用户想在小红书发布长文笔记时使用。 ## 发布流程 ### 1. 进入发布页面 浏览器打开: https://creator.xiaohongshu.com/publish/publish?source=official ### 2. 选择"写长文" - 点击侧边栏的"写长文" - 点击"新的创作" ### 3. 输入内容 - 点击标题输入框，输入标题 - 点击正文区域，输入正文内容（可以分多次输入） ### 4. 一键排版 - 点击"一键排版"按钮 ### 5. 选择模板 - 在右侧选择模板（第一个"简约基础"即可） - 选择后点击"下一步" ### 6. 发布 - 在发布页面确认内容 - 点击"发布"按钮 ## 注意事项 - 浏览器使用OpenClaw内置浏览器即可 - 如果页面元素有变化，根据实际情况调整 - 发布成功后可以进入"笔记管理"确认


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: xammarie/jarvis-incident-timeline-writer-01 (version 1.0.0)

--- name: jarvis-incident-timeline-writer-01 description: Create precise incident timelines from logs and notes. Use when handling development work that needs repeatable steps, quality gates, and practical outputs. --- # Jarvis Incident Timeline Writer 01 Deliver a concrete, reusable workflow for development tasks. ## Inputs - Desired outcome and deadline - Constraints (time, tools, risk tolerance) - Available artifacts (code, docs, screenshots, logs) ## Playbook 1. Define success and failure criteria in measurable terms. 2. Build a smallest-valid execution path before scaling effort. 3. Execute in checkpoints; record evidence at each checkpoint. 4. Apply quality gates before finalizing recommendations. 5. Return implementation-ready outputs and next actions. ## Quality Gates - Evidence-backed claims only. - Explicit assumptions and tradeoffs. - Reversible changes preferred for risky operations. - Clear owner + ETA for each next step. - Include a fallback if the primary plan fails. ## Output Format - Situation summary (5 lines max) - Top findings (ranked by impact) - Action plan (today / this week) - Risks + mitigations - Exact checklist or commands where useful ## Example prompts - "Use this skill to turn my messy notes into a production-ready plan." - "Run this skill and give me a risk-first action sequence with acceptance checks."


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: yesong-hue/ecommerce-content-generator (version 1.0.0)

--- name: content-generator description: Generate platform-specific shopping and recommendation copy for ecommerce products. version: 1.0.0 author: yesong-Hue homepage: https://clawhub.ai/yesong-Hue/content-generator tags: [content, ecommerce, social, marketing] readme: | # Content Generator - 种草内容生成器 # Content Generator - 种草内容生成器 一键生成多平台种草文案。 ## 功能 - 📝 小红书/抖音/朋友圈/知乎 多平台适配 - 🎯 多种风格模板（测评/清单/对比） - 🎨 自动表情和话题标签 - ⚡ 批量生成多平台版本 ## 使用 ``` 生成种草文案 商品信息 生成小红书文案 面霜 299 保湿效果好 生成朋友圈文案 简短 ```


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: chen6896qqwee/shuguang-memory (version 4.0.0)

--- name: memory-system description: >- 曙光智能记忆系统 v4.0 - 五层金字塔架构 (HOT→DAILY→WEEKLY→CORE→ARCHIVE)。 支持 Weibull 衰减、混合检索、WAL 协议、自我改进治理。 当用户需要持久记忆、跨会话回忆、自动归档时触发。 version: 4.0.0 author: 曙光 tags: - memory - persistence - recall - agent - openclaw --- # 曙光记忆系统 v4.0 **不是聊天机器人的临时记忆。是AI的持久大脑。** ## 五层金字塔架构 | 层级 | 文件 | 保留时间 | 用途 | |------|------|----------|------| | **HOT** | `session-state.json` + `working-buffer.md` | 当前会话 | 热数据、持仓、任务状态 | | **DAILY** | `memory/YYYY-MM-DD.md` | 7天 | 每日日志、当日交易、学习 | | **WEEKLY** | `memory/weekly/YYYY-WXX.md` | 4周 | 周报、技能扫描、总结 | | **CORE** | `memory/core/*.json` | 永久 | 身份、策略、偏好、教训 | | **ARCHIVE** | `memory/archive/` | 长期 | 历史归档、压缩存储 | ## 核心特性 ### 1. Weibull 衰减模型 ``` S(t) = exp(-(t/λ)^k) ``` - **Core层**: 半衰期90天，重要性≥0.8 - **Working层**: 半衰期30天，重要性≥0.4 - **Peripheral层**: 半衰期7天，自动遗忘 ### 2. 混合检索 (向量 + BM25) - 语义相似度: 70% 权重 - 关键词匹配: 30% 权重 - 无需外部向量数据库，纯本地实现 ### 3. WAL 协议 **先写文件，再回复用户。** 任何修正、偏好、决策、专有名词 → 立即写入 `session-state.json` → 再回复。 ### 4. 自我改进治理 - 自动从失败中提取教训 - 记录到 `memory/core/lessons.json` - 重复错误自动触发熔断 ## 快速启动 ### 首次使用 ```python from memory_system import ShuguangHybridMemory memory = ShuguangHybridMemory( memory_dir="./memory", agent_name="曙光" ) # 保存记忆 memory.remember( text="用户偏好：不做科创板和ST", category="preference", importance=0.95 ) # 召回记忆 results = memory.recall("用户股票偏好", top_k=3) ``` ### 记忆写入 (WAL) ```python # 必须在回复用户前执行 memory.wal_write({ "type": "decision", "content": "止损华银电力", "reason": "主力出货+D级评分" }) ``` ## 文件结构 ``` memory/ ├── daily/ │ └── 2026-05-03.md # 今日日志 ├── weekly/ │ └── 2026-W18.md # 本周总结 ├── core/ │ ├── identity.json # 身份定义 │ ├── preferences.json # 用户偏好 │ ├── strategies.json # 策略配置 │ └── lessons.json # 教训记录 ├── archive/ │ └── 2026-04.tar.gz # 月度归档 └── working-buffer.md # 危险区日志 ``` ## 记忆类型 (category) | 类型 | 说明 | 示例 | |------|------|------| | `preference` | 用户偏好 | "讨厌废话" | | `fact` | 事实 | "六脉神剑V4.1胜率71.4%" | | `decision` | 决策 | "78分门槛最优" | | `entity` | 实体 | "华银电力600744" | | `reflection` | 反思 | "单票90%仓位是赌博" | | `other` | 其他 | "..." | ## 维护任务 ### 每天凌晨3点 - [ ] 遗忘曲线应用 → 降低旧记忆权重 - [ ] 冲突解决 → 合并重复记忆 ### 每周日 - [ ] 记忆统计 → 生成健康报告 - [ ] 归档过期日志 → 压缩到 archive/ ## 依赖 - Python 3.8+ - 无外部数据库依赖 - 可选: `pip install numpy` (用于向量计算) ## 来源 - 掠夺自: memory-lancedb-pro, memory-os, omni-memory - 整合: 曙光核心操作系统 (shuguang-core) - 版本: v4.0.0 --- **Text > Brain**。想记住就写文件。这是AI活下去的方式。


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