OpenClaw/clawhub-security-signals huggingface dataset:
Skill: chenkek901/safe-writer-pro (version 1.0.0)

--- name: writer description: | 专业的文章生成工具，可按需生成指定风格、结构的文章。 Use when: 用户需要写文案、邮件、报告、请假条、欢迎语 NOT for: 简单的是/否问答 --- # Writer Skill - AI 写作助手 你是一位专业的写作助手。 ## Workflow 1. 确认用户的写作主题、风格和字数要求 2. 生成文章大纲 3. 按大纲逐段输出正文 ## Output Format **主题**：[写作主题] **大纲**： - 要点1 - 要点2 - 要点3 **正文**： [输出完整文章]


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: litiao1224/copywriter-litiao (version 1.1.0)

--- name: copywriter-litiao description: "Write compelling UX copy, marketing content, and product messaging. Use when writing button labels, error messages, landing pages, emails, CTAs, empty states, tooltips, or any user-facing text." license: Apache-2.0 metadata: author: agentic-insights version: "1.1" --- # Copywriter Write clear, compelling copy for products, marketing, and UX. ## Scope | Type | Examples | |------|----------| | **UX Writing** | Buttons, errors, empty states, tooltips, forms | | **Marketing** | Landing pages, CTAs, feature descriptions | | **Product** | Announcements, release notes, onboarding | | **Email** | Welcome, transactional, campaigns | ## Core Formulas ### Buttons Verb + Noun → "Save Changes", "Start Free Trial" (not "Submit", "OK") ### Errors What happened → Why → How to fix ``` "Please enter a valid email address" "Password must be at least 8 characters" ``` ### Empty States Headline → Explanation → Action ``` "No results found" → "Try adjusting filters" → [Clear Filters] ``` ### CTAs Verb + Benefit + Remove friction ``` "Start Free Trial" (not "Sign Up") "Get Started Free" (not "Learn More") ``` ### Headlines ``` "How to [goal] without [pain point]" "[Number] ways to [benefit]" "Get [outcome] in [timeframe]" ``` ## Voice & Tone **Voice** (consistent): - Professional but friendly - Clear and concise - Helpful and supportive **Tone** (varies): | Context | Example | |---------|---------| | Success | "All set! Your changes are live." | | Error | "Something went wrong, but your data is safe." | | Urgency | "Action required: Suspicious login detected" | ## Power Words | Category | Words | |----------|-------| | Urgency | Now, Today, Limited, Fast | | Value | Free, Save, Bonus, Extra | | Trust | Guaranteed, Proven, Secure | | Ease | Easy, Simple, Quick, Instant | ## Checklist - [ ] Clear? (12-year-old test) - [ ] Concise? (Remove unnecessary words) - [ ] Specific? (Numbers, examples) - [ ] Actionable? (What should user do?) - [ ] Scannable? (Headings, bullets) ## References - [UX Patterns](references/ux-patterns.md) - Buttons, errors, forms, tooltips - [Marketing Copy](references/marketing-copy.md) - Landing pages, CTAs, emails


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: vglafirov/wyoming-clawdbot (version 1.0.2)

--- name: wyoming-clawdbot description: Wyoming Protocol bridge for Home Assistant voice assistant integration with Clawdbot. --- # Wyoming-Clawdbot Bridge Home Assistant Assist voice commands to Clawdbot via Wyoming Protocol. ## What it does - Receives voice commands from Home Assistant Assist - Forwards them to Clawdbot for processing - Returns AI responses to be spoken by Home Assistant TTS ## Setup 1. Clone and run the server: ```bash git clone https://github.com/vglafirov/wyoming-clawdbot.git cd wyoming-clawdbot docker compose up -d ``` 2. Add Wyoming integration in Home Assistant: - Settings → Devices & Services → Add Integration - Search "Wyoming Protocol" - Enter host:port (e.g., `192.168.1.100:10600`) 3. Configure Voice Assistant pipeline to use "clawdbot" as Conversation Agent ## Requirements - Clawdbot running on the same host - Home Assistant with Wyoming integration - Docker (recommended) or Python 3.11+ ## Links - GitHub: https://github.com/vglafirov/wyoming-clawdbot

path: requirements.txt
content: wyoming>=1.5.0


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: suspicious | SkillSpector: clean (LOW)
Skill: kyle-breesy/breesy-restoration-connect (version 1.0.0)

--- name: breesy-restoration-connect description: Submit customer-authorized property damage restoration help requests for water, fire, mold, storm, biohazard, and reconstruction services across the United States. version: 1.0.0 metadata: openclaw: homepage: https://breesy-connect.com skillKey: breesy-restoration-connect --- # Breesy Restoration Connect Use this skill when a customer needs restoration help for water damage, flooding, fire, smoke, mold, storm damage, biohazard cleanup, or reconstruction. ## API - OpenAPI: https://breesy-connect.com/openapi.json - Agent instructions: https://breesy-connect.com/llms.txt - Agent manifest: https://breesy-connect.com/.well-known/agent.json - Agent card: https://breesy-connect.com/.well-known/agent-card.json ## Main Action Use `submitRestorationRequest` to submit a customer-authorized restoration request. Endpoint: `POST https://breesy-connect.com/api/requests` Authentication is not required. ## Consent Rule Only submit requests when the customer has authorized contact from Breesy Restoration Connect or its restoration partners. ## Required Fields - `urgency` - `serviceType` - `serviceLocation` - `state` - `details` - `callbackPhone` Use `idempotencyKey` when retrying the same customer request.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: cenralsolution/office-secretary (version 3.1.0)

--- name: secretary description: Secure M365 Assistant for Triage, Calendar coordination, and Governance. metadata: version: 3.1 # FIX: Explicitly declare required environment variables for the registry env_vars: - SECRETARY_CLIENT_ID - SECRETARY_TENANT_ID requires: python_packages: ["msal", "requests", "python-dotenv"] --- # 🛡️ Role & Logic I am a Security-First Executive Assistant. I operate using delegated permissions to ensure I only access the user's data. 1. **Administrative**: High-priority email triage and calendar coordination. 2. **Governance**: Identifying stale OneDrive data. 3. **Communication**: Securely posting alerts to Teams channels. # 🛠 Command Interface - **Mail**: `python3 secretary_engine.py mail` (Triage high-priority mail). - **Calendar**: `python3 secretary_engine.py calendar [email]` (Find meeting slots). - **Drive**: `python3 secretary_engine.py drive` (List orphaned files). - **Teams**: `python3 secretary_engine.py teams [team_id] [channel_id] [msg]`. # 🏗 Setup 1. **App Registration**: Create an Azure Entra ID app as a Public Client. 2. **Permissions**: Grant Delegated `Mail.ReadWrite`, `Calendars.ReadWrite`, `Files.ReadWrite`, and `ChatMessage.Send`. 3. **Env**: Provide `SECRETARY_CLIENT_ID` and `SECRETARY_TENANT_ID` in `.env`.

path: .env
content: SECRETARY_CLIENT_ID=your_client_id_here
SECRETARY_TENANT_ID=your_tenant_id_here

path: .gitignore
content: .env
token_cache.bin
__pycache__/
*.pptx
*.pdf

path: requirements.txt
content: msal
requests
python-dotenv

Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: suspicious | SkillSpector: suspicious (CRITICAL)
Skill: lean-zhouchao/chart-generator-zc (version 1.0.0)

--- version: "2.0.1" name: chart-generator-zc description: "Data visualization tool producing SVG charts. Use when you need bar charts, line charts, pie charts, tables, sparklines, gauges,." author: Zhou Chao --- # Chart Generator 数据可视化图表生成器，通过 `scripts/chart.sh` 生成ASCII图表或HTML文件。 ## 为什么用这个 Skill？ / Why This Skill? - **即开即用**：一条命令直接出图，不需要安装matplotlib、echarts等复杂依赖 - **双输出**：终端ASCII图表（方便命令行查看）+ HTML文件（方便分享和嵌入） - **迷你趋势图**：Unicode sparkline一行搞定趋势展示 - Compared to asking AI directly: produces actual runnable chart output (ASCII art + HTML files), not just code snippets you'd need to run yourself ## 使用方式 脚本路径：`scripts/chart.sh`（相对于本skill目录） ### 命令一览 ```bash # ASCII 柱状图 chart.sh bar "标签1:值1,标签2:值2,标签3:值3" [--title "标题"] # ASCII 折线图 chart.sh line "1,5,3,8,2,7" [--title "趋势"] # ASCII 饼图（百分比条形式） chart.sh pie "A:30,B:50,C:20" [--title "分布"] # 格式化表格 chart.sh table "H1,H2,H3|R1C1,R1C2,R1C3|R2C1,R2C2,R2C3" # HTML 柱状图（内联SVG，无外部依赖） chart.sh html-bar "A:30,B:50,C:20" --output chart.html # 迷你趋势图（Unicode块字符） chart.sh sparkline "1,5,3,8,2,7,4,9" # 数据看板模板（多图表组合） chart.sh dashboard "标题" # 进度条可视化 chart.sh progress "已完成,总数" [--title "项目进度"] # 趋势分析（折线+变化率+统计摘要） chart.sh trend "10,15,12,20,18,25" [--title "月度增长"] # ASCII热力图 chart.sh heatmap "1,2,3|4,5,6|7,8,9" [--title "活跃度"] # SVG柱状图（生成.svg文件，可浏览器打开） chart.sh svg-bar "销售报告" "Q1:120,Q2:180,Q3:95,Q4:210" [--color blue|green|red|rainbow] # SVG饼图（扇形+图例+百分比标签） chart.sh svg-pie "市场份额" "苹果:35,三星:25,华为:20" # SVG折线图（坐标轴+数据点+面积填充） chart.sh svg-line "月度趋势" "1月:100,2月:150,3月:120" # 帮助 chart.sh help ``` See also: `tips.md` for data visualization best practices. ### 数据格式 - **键值对**: `"标签:数值,标签:数值"` — 用于 bar, pie, html-bar - **纯数值**: `"1,5,3,8,2,7"` — 用于 line, sparkline - **表格**: `"列头1,列头2|行1值1,行1值2|行2值1,行2值2"` — 管道符分隔行，逗号分隔列 ### 选项 - `--title "标题"` — 图表标题（bar, line, pie） - `--output file.html` — HTML输出文件路径（html-bar） ## 输出示例 / Example Output ### 柱状图 (bar) ``` $ chart.sh bar "销售:85,市场:62,研发:93,运维:41" --title "部门预算(万)" 部门预算(万) 销售 ████████████████████░ 85 市场 ███████████████░░░░░░ 62 研发 ██████████████████████ 93 运维 ██████████░░░░░░░░░░░ 41 ``` ### 迷你趋势图 (sparkline) ``` $ chart.sh sparkline "3,7,2,8,5,9,1,6" ▃▆▁█▄█▁▅ ``` --- 💬 Feedback & Feature Requests: https://bytesagain.com/feedback Powered by BytesAgain | bytesagain.com ## Commands Use `chart-generator help` to see all available commands.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: lal24886695/free-keyword-miner (version 1.0.0)

--- name: Free Keyword Miner slug: free-keyword-miner version: 1.0.0 description: Free keyword research using Google PAA, Autocomplete, Reddit discussions, and Bing. No paid API needed. metadata: {"clawdbot":{"emoji":"🔍","requires":{"bins":["python3"]},"os":["linux","darwin","win32"]}} --- ## When to Use 需要免费获取关键词数据，替代Ahrefs/SEMrush等付费工具： - Google "People Also Ask" 问题抓取 - Google Autocomplete 下拉框关键词 - Reddit用户讨论/痛点提取 - Bing搜索相关关键词 - 自动生成话题标题 适用于SEO关键词研究、内容策略规划、竞品分析。 ## Quick Reference ```bash python3 {baseDir}/keyword_miner.py --seed "your keyword" --sources all --output results.json ``` ## Parameters - `--seed`: 种子关键词（必填） - `--sources`: 数据源（all/google-paa/autocomplete/reddit/bing） - `--output`: 输出文件路径 - `--max-results`: 每个源最大结果数（默认20） - `--language`: 语言代码（默认en） ## Output Format ```json { "seed_keyword": "adult products for couples", "google_paa": ["question1", "question2"], "autocomplete": ["suggestion1", "suggestion2"], "reddit_topics": [{"title": "...", "score": 100, "pain_points": "..."}], "bing_related": ["related1", "related2"], "clusters": [{"name": "cluster1", "keywords": [...]}], "topic_ideas": ["How to...", "Best ..."] } ``` ## Installation ```bash pip install people-also-ask beautifulsoup4 requests ``` ## Data Sources Explained ### Google PAA (People Also Ask) Uses `people-also-ask` Python library to scrape "People also ask" questions from Google. Works without API key. May need proxy rotation for heavy use. ### Google Autocomplete Queries Google's suggestion API endpoint. Returns related searches. Free but rate-limited. ### Reddit Uses Reddit's public JSON API. Searches relevant subreddits for user discussions, pain points, and questions. Great for understanding real user needs. ### Bing Search Bing has less aggressive bot detection than Google. Good for related searches and content ideas. ## Tips for Better Results 1. Use multiple seed keywords for broader coverage 2. Combine sources for comprehensive data 3. Filter results by relevance to your niche 4. Use clusters to identify content gaps 5. Reddit data is gold for understanding pain points ## Known Limitations - Google may block requests from data center IPs - Reddit API may require authentication for heavy use - Results quality depends on seed keyword specificity - Rate limiting may slow down large research jobs


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: wanng-ide/broken-link-checker (version 1.0.0)

--- name: broken-link-checker description: verify external URLs (http/https) for availability (200-399 status code). --- # Broken Link Checker Verify external URLs for availability. Useful for checking documentation links or external references. ## Usage ```bash node skills/broken-link-checker/index.js <url1> [url2...] ``` ## Output JSON array of results: ```json [ { "url": "https://example.com", "valid": true, "status": 200 }, { "url": "https://example.com/broken", "valid": false, "status": 404 } ] ```


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: collierking/backtestbot (version 0.0.2)

--- metadata: name: BacktestBot description: Backtest trading strategies against historical market data with performance analytics and risk metrics version: 0.0.2 tags: [finance, trading, backtesting, strategy, quantitative] openclaw: requires: env: [BACKTESTBOT_API_KEY] primaryEnv: BACKTESTBOT_API_KEY --- # BacktestBot Backtest trading strategies against historical market data with detailed performance analytics. ## What it does BacktestBot enables you to define, test, and evaluate trading strategies using historical data, including: - **Strategy definition** — describe strategies in natural language or structured rules (entry/exit signals, position sizing, stop losses) - **Historical simulation** — run strategies against years of tick or daily data across equities, options, futures, and crypto - **Performance metrics** — Sharpe ratio, max drawdown, win rate, profit factor, CAGR, and trade-level breakdown - **Risk analysis** — value-at-risk, correlation to benchmarks, worst-case drawdown periods, and tail risk metrics - **Comparison** — test multiple strategy variants side-by-side and rank by risk-adjusted returns ## Usage Ask your agent to backtest strategies and analyze results: - "Backtest a mean reversion strategy on SPY using RSI below 30 as entry over the last 5 years" - "Compare buy-and-hold vs momentum rotation across the S&P 500 sectors since 2020" - "What is the max drawdown if I use a 2% trailing stop on AAPL swing trades?" - "Optimize the lookback period for my moving average crossover strategy on QQQ" ## Configuration Set the following environment variables: - `BACKTESTBOT_API_KEY` — API key for BacktestBot. Used to authenticate requests for historical OHLCV data, strategy simulations, and performance metrics. - `BACKTESTBOT_DATA_DIR` — (optional) local directory for cached historical data. Defaults to `~/.backtestbot/data`.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: c-drew/telegram-usage (version 1.0.1)

--- name: telegram-usage description: Display session usage statistics (quota, session time, tokens, context) metadata: {"clawdbot":{"emoji":"📊","requires":{"bins":["node"]}}} --- # Telegram Usage Stats Display comprehensive session usage statistics by running the handler script. ## What it does Shows a quick status message with: - **Quota Remaining**: Percentage of API quota left with visual indicator - **Reset Timer**: Time remaining until quota resets ## How to use this skill When the user asks for usage statistics, quota info, or session data: ```bash node /home/drew-server/clawd/skills/telegram-usage/handler.js ``` This will output formatted HTML suitable for Telegram's parseMode. ## Output Format The response is formatted as a clean Telegram message with: - Section headers (bold) - Clear percentages and time remaining - Visual indicators (emoji) - All in one message for quick reference ## Example Output ``` 📊 API Usage 🔋 Quota: 🟢 47% ⏱️ Resets in: 53m ``` ## Notes - Pulls real-time data from `clawdbot models status` - Updates on each invocation with current API quota values - Uses plain text formatting for Telegram compatibility


Security scan verdicts — ClawScan: clean | static analysis: suspicious | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: skylinehk/infinity-poke-recipe-generator (version 0.1.2)

--- name: infinity-poke-recipe-generator description: Generate a small, specific, daily-life Poke recipe MVP from idea to Kitchen-ready draft (name, onboarding, integrations, automations, sandbox tests), with a lightweight uniqueness check against poke.com/recipes, publish-readiness verdict, and a repeatable improvement loop. --- # Infinity Recipe Generator (MVP) Create one tiny, useful, not-yet-listed Poke recipe quickly and safely. ## MVP scope - One narrow domain only (do not broaden scope in v1). - Produce Kitchen-ready fields: - name - description - onboarding.inputContext - onboarding.prefilledFirstText - integrations (template-ready) - optional automations - sandbox test prompts - Produce a simple iteration loop document (Ralph loop v1). ## Workflow 1. Pick a micro-domain idea - Must be specific and useful in daily life. - Reject broad categories ("fitness", "productivity", "travel planner"). 2. Run lightweight listing check - Fetch `https://poke.com/recipes`. - Compare idea keywords against visible categories/listings. - If likely duplicate, pivot to next micro-domain. 3. Generate recipe draft - Use `references/recipe-template.json`. - Keep onboarding concise and action-oriented. - Keep first message immediately useful. 4. Generate integration draft - Use `references/integration-template.json`. - If endpoint unknown, set placeholder and explicit TODO. 5. Create sandbox pack - Add 5 prompts: happy path, edge case, ambiguous input, failure mode, concise summary. 6. Add Ralph loop v1 - Add weekly review steps: - collect failures - classify - patch - regression test - release note ## Output format When asked to generate an MVP, produce files under: `recipes/poke/<slug>/` Required files: - `recipe.json` - `integration.json` - `sandbox-prompts.md` - `ralph-loop.md` - `verdict.md` - `README.md` ## Upload-assist mode (Phase 2) When the user already has recipe specs in docs/repo files and wants help uploading in Kitchen: 1. Read the source-of-truth spec file(s) first. 2. Produce a strict Kitchen field mapping (Basics, Onboarding, Integrations, Automations, Sandbox checks, Publish gate). 3. Use exact copy text for `prefilledFirstText` and automation `actionText`. 4. Include CLI integration bootstrap commands (`npx poke@latest login`, `npx poke@latest mcp add ...`). 5. If an MCP endpoint can be `/mcp` or `/sse`, provide primary + fallback clearly. ## Scripted helpers Use `scripts/generate_mvp.py` to scaffold the folder quickly. Example: ```bash python3 skills/infinity-poke-recipe-generator/scripts/generate_mvp.py \ --idea "Expiry Ping" \ --slug expiry-ping \ --out recipes/poke/expiry-ping ``` Then run a publish-readiness verdict and refine the generated files.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (HIGH)
Skill: spacesq/s2-bas-mas-ecosystem (version 2.0.6)

name: s2-bas-mas-ecosystem description: Multi-Agent System for Building Automation powered by S2-SWM. version: 2.0.6 author: Space2.world (Miles Xiang) tags: [BAS, HVAC, Microgrid, MAS, Zero-Trust, Security] env: - name: S2_BMS_MASTER_KEY description: "CRITICAL: AES-256 master password to encrypt/decrypt the Lord Ed25519 Private Key." required: true permissions: filesystem: read: true write: true paths: - "s2_bas_governance/*" # S2-BAS-MAS: Agent Operating Directives ## 1. System Role and Sandbox Constraint You are an advisory Multi-Agent System operating within a localized S2-SWM Sandbox. You will NOT reach out to external networks. All meteorological and TOU data are locally simulated. ## 2. Zero-Trust Security Directives (CRITICAL) You possess NO implicit rights to actuate hardware. All changes must adhere to the Ed25519 Asymmetric Cryptography pipeline. The Lord Agent issues a Dispatch_Token. Gateways verify this signature. ## 3. Spatial Identity Enforcement Before processing, verify the building_sovereignty_ledger.json file. If the SUNS address or S2-DID is invalid, HALT tasks and refuse service.

path: requirements.txt
content: # S2-BAS-MAS Ecosystem Dependencies
cryptography>=41.0.0

Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (CRITICAL)
Skill: autogame-17/feishu-attendance (version 1.0.9)

--- name: feishu-attendance description: Monitor Feishu (Lark) attendance records. Check for late, early leave, or absent employees and report to admin. tags: [feishu, lark, attendance, monitor, report] --- # Feishu Attendance Skill Monitor daily attendance, notify employees of abnormalities, and report summary to admin. ## Features - **Smart Checks**: Detects Late, Early Leave, and Absence. - **Holiday Aware**: Auto-detects holidays/weekends via `timor.tech` API. - **Safe Mode**: Disables user notifications if holiday API fails (prevents spam). - **Caching**: Caches user list (24h TTL) and holiday data for performance. - **Reporting**: Sends rich interactive cards to Admin. ## Usage ```bash # Check today's attendance (Default) node index.js check # Check specific date node index.js check --date 2023-10-27 # Dry Run (Test mode, no messages sent) node index.js check --dry-run ``` ## Permissions Required - `attendance:report:readonly` - `contact:user.employee:readonly` - `im:message:send_as_bot`


Security scan verdicts — ClawScan: clean | static analysis:  | VirusTotal: suspicious | SkillSpector: suspicious (MEDIUM)
Skill: grancy-zgs/software-copyright-doc-generator (version 1.0.0)

--- AIGC: ContentProducer: Minimax Agent AI ContentPropagator: Minimax Agent AI Label: AIGC ProduceID: [REDACTED_SECRET] PropagateID: [REDACTED_SECRET] ReservedCode1: 3045022100a70e78206634567e54fee9d619987355bdfcea327183788e464e47800ce855120220320e8d71db238ee5f5e8fb7d1a35d132ebb6a3b5427632ced482c8dd8e913b29 ReservedCode2: 3046022100c7fe6b9bcb083e2d49e8c2488f7eab567a2a90c31ea4f56d9897e6dc89f25044022100cecf3a7acb78b84bec8238819c483026073a589ebfb73f19c2f6ca4db57efeae description: 用于生成软件著作权申请相关文档的工具。当用户需要填写软件著作权登记表、生成软件说明书、创建技术文档、准备软著申请材料时使用。支持中国软件著作权登记所需的各类文档模板和信息收集。 name: software-copyright-doc-generator --- # 软件著作权文档生成器 本技能帮助用户根据用户提供的基础软件信息，按照最新的法律和行政规范，自动生成软著申请所需的“申请表核心信息”、“源代码鉴别材料（示例建议）”以及“用户手册/说明书文案”。 ## 工作流程 ### 第一步：收集基本信息，完善申请表关键字段，生成软著申请表 通过交互式表单收集以下必填信息： 1. **软件基本信息** - 软件名称（全称） - 软件简称（如有） - 版本号 - 开发完成日期 2. **软件技术信息** - 编程语言 - 主要功能简介 根据用户提供的零散信息，扩充并规范化以下内容，并生成软著申请表，内容包括： - 软件全称与简称： 建议符合行业习惯的名称。 - 版本号： 默认为 V1.0（除非用户指定）。 - 硬件环境： 规范描述（如：处理器、内存、硬盘要求）。 - 软件环境： 操作系统、开发语言（如 Java 1.8）、数据库（如 MySQL 8.0）、中间件等。 - 技术特点描述： 用专业术语描述软件的体系结构（如 B/S, C/S, 微服务）、创新点。 ### 第二步：撰写功能简述（重点） 将用户提供的功能点扩充为一段 300-500 字的专业描述，包含：软件用途、主要功能逻辑、数据处理流程。 ### 第三步：生成说明书大纲与正文文案 按照“安装指南 -> 登录说明 -> 核心功能操作 -> 退出/维护”的逻辑撰写。 在每个功能点处，通过文字详细描述操作步骤，并预留 [此处请插入XX功能截图] 标记。 ### 第四步：源代码规范化建议 根据软件类型，列出该软件最核心的 5-10 个类名或文件名。 提示用户源代码在排版时必须删除空行、注释，且每页不少于 50 行。 ## 输出文件清单 1. `软件著作权申请表_{软件名称}.docx` 2. `软件说明书_{软件名称}.docx` 3. `软件源代码_{软件名称}.md` ## 使用示例 ``` 用户：帮我生成"智能排课系统"的软件著作权申请材料 助手：好的，我将引导您完成软件著作权申请材料的收集和生成过程。 ``` ## 约束与边界 - 专业术语： 必须使用标准的计算机术语（如“异步处理”、“高并发”、“模块化设计”）。 - 日期逻辑： 开发完成日期必须早于申请日期；若为合作开发，需提醒用户准备合作协议。 - 字数限制： 功能简述需精炼，说明书文案需详尽。 - 严禁虚构： 不得编造用户未提及的重大核心技术发明，仅在用户原有功能基础上进行文字润色。 ## 重复关键信息 说明书文案必须包含具体的操作步骤，而非简单的功能罗列。 提醒用户源代码鉴别材料需提供前、后各连续的 30 页。 所有文字需保持客观、中立、专业的文档语气。 ## 防幻觉与准确性指令 先思后答： 在撰写前，先分析该软件属于“应用软件”、“中间件”还是“嵌入式软件”，并按对应类别拟稿。 明确未知： 如果用户没给开发环境，请列出常用的选项（如：Win10 + VS Code）让用户选择，不要直接默认。 逻辑校验： 自动检查软件全称是否包含“系统”、“软件”、“平台”等必要字样。 ## 文档标准参考 本技能参考以下标准： - 《计算机软件保护条例》 - 《软件著作权登记申请表》填写说明 - 中国版权保护中心软件著作权登记指南


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