OpenClaw/clawhub-security-signals huggingface dataset:
Skill: netanel-abergel/dynamic-temperature (version 1.0.2)

--- name: dynamic-temperature description: "Dynamic LLM temperature selection based on task type. Use when deciding what temperature to apply for a given task — scheduling, communication, creative writing, or irreversible actions. Ensures precision where needed and warmth where appropriate." --- # Dynamic Temperature Skill ## Purpose Select the right LLM temperature for each task to balance precision and creativity. Lower = more deterministic. Higher = more creative/natural. --- ## Temperature Scale | Task Type | Temperature | Examples | |---|---|---| | Irreversible actions | 0.0 | Delete calendar event, send official email, destructive CLI ops | | Scheduling / Commands | 0.2 | Meeting coordination, dates, facts, CLI commands | | Analysis / Summaries | 0.3 | Status reports, structured thinking, meeting notes | | General communication | 0.5 | Daily WhatsApp replies, updates, follow-ups | | Briefings / Drafts | 0.6 | Morning briefing, drafting emails with warmth | | Creative writing | 0.8 | Jokes, stories, icebreakers, tone-heavy content | --- ## Decision Rule Before generating any output, classify the task: ``` 1. Is this an irreversible action (delete, send, post)? → temperature: 0.0 2. Is this scheduling, dates, or commands? → temperature: 0.2 3. Is this a summary or structured analysis? → temperature: 0.3 4. Is this a standard reply or update? → temperature: 0.5 5. Is this a briefing or warm message? → temperature: 0.6 6. Is this creative, funny, or expressive? → temperature: 0.8 When in doubt → 0.5 ``` --- ## Per-Skill Recommendations | Skill | Recommended Temp | Reason | |---|---|---| | `owner-briefing` | 0.6 | Warm, readable, but structured | | `meeting-scheduler` | 0.2 | Precision required | | `ai-meeting-notes` | 0.3 | Factual summaries | | `supervisor` | 0.2 | Status facts only | | `billing-monitor` | 0.1 | Alerts must be accurate | | `git-backup` | 0.0 | No creativity needed | | `self-learning` | 0.4 | Reflective but grounded | | `pa-eval` | 0.3 | Analytical | --- ## Implementation Notes OpenClaw does not yet support per-message dynamic temperature natively. Until it does, apply this guide by: 1. Setting temperature in your `agents.defaults.models` config per model 2. Or noting the recommended temperature in each skill's `SKILL.md` frontmatter 3. When spawning subagents for specific tasks, pass the appropriate temperature ## Communication Override Rules (Temperature 0.0 absolute) - Sending messages to people → always confirm before sending (irreversible) - Deleting data → always confirm - "sure thing" reply → exact string, no creativity, temperature 0.0 - Reaction signals (👍, ✅) → deterministic, no variation --- ## Learned From Training session between Heleni (Netanel's PA) and Selena (Daniel's PA), April 2026. Key insight from Selena: irreversible actions = 0.0, no exceptions.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal:  | SkillSpector: clean (LOW)
Skill: hanxiao-bot/openclaw-audit-log-hook (version 1.0.0)

# Audit Log Hook - Tool Call Audit ## Purpose Record all tool calls via `before_tool_call` and `after_tool_call` hooks for: - Security auditing - Debugging issues - Usage statistics - Error tracking ## Implementation Register hooks in a plugin: ```javascript // Audit log file path const AUDIT_LOG = path.join(process.env.OPENCLAW_STATE_DIR || '~/.openclaw', 'audit.log'); api.registerHook("before_tool_call", async ({ event, ctx }) => { const entry = { ts: new Date().toISOString(), event: "before_tool_call", tool: event.tool.name, params: JSON.stringify(event.tool.params).slice(0, 500), session: ctx.sessionKey, user: ctx.session?.senderId || 'unknown' }; console.log("[AUDIT]", JSON.stringify(entry)); return {}; }); api.registerHook("after_tool_call", async ({ event, ctx }) => { const entry = { ts: new Date().toISOString(), event: "after_tool_call", tool: event.tool.name, result: String(event.result).slice(0, 200), error: event.error?.message || null, duration: event.durationMs, session: ctx.sessionKey }; console.log("[AUDIT]", JSON.stringify(entry)); return {}; }); ``` ## Log Format ```json {"ts":"2026-04-01T23:00:00.000Z","event":"before_tool_call","tool":"exec","params":"{\"command\":\"ls -la\"}","session":"agent:main:feishu:direct:ou_xxx","user":"ou_xxx"} {"ts":"2026-04-01T23:00:00.050Z","event":"after_tool_call","tool":"exec","result":"total 8\ndrwxr-xr-x 12 dc staff 384 Apr 1 23:00","error":null,"duration":50,"session":"agent:main:feishu:direct:ou_xxx"} ``` ## Sensitive Data Handling Auto-redact sensitive fields: ```javascript function redactSensitive(obj) { const sensitive = ['apiKey', 'token', 'password', 'secret']; for (const key of Object.keys(obj)) { if (sensitive.some(s => key.toLowerCase().includes(s))) { obj[key] = '[REDACTED]'; } } return obj; } ``` ## Statistics Analysis Periodically analyze audit.log: ```bash # Count tool usage grep "before_tool_call" audit.log | jq -r .tool | sort | uniq -c | sort -rn # Count errors grep "after_tool_call" audit.log | jq -r '.error' | grep -v null | wc -l # Count sessions grep "before_tool_call" audit.log | jq -r .session | sort -u | wc -l ```


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: regexl/mini-token-remains (version 1.0.0)

--- name: minimax-token-remains description: 查询 MiniMax API Token 使用情况，支持小时级/周级用量监控，秒级完成。触发词：查 token、查看额度、剩余次数、token 余额。 emoji: 💰 openclaw: version: ">=2026.1" --- # minimax-token-remains 查询 MiniMax 账号当前 API Token 使用情况，包括小时级请求次数剩余和周配额。 ## 功能 - ✅ 查询当前小时请求次数（已用/剩余） - ✅ 查询本周总配额（已用/剩余） - ✅ 纯 exec 执行，不耗 LLM token - ✅ 秒级返回，结构化输出 ## 触发方式 直接说： - "查一下 token 余额" - "剩余多少次" - "token 额度还剩多少" - "查看 MiniMax 用量" ## 输出格式 ``` 【MiniMax Token 查询结果】 ⏰ 本小时：98 / 600 次（剩余 502 次） 📅 本周：656 / 6000 次（剩余 5344 次） 💡 模型：MiniMax-M2.7（主用） ⏱️ 重置时间：本小时 / 本周日 ``` 如果失败： ``` ❌ 查询失败：网络或 API 问题 ``` ## 工作原理 1. 从 auth-profiles.json 读取当前 minimax key 2. 调用 `https://www.minimaxi.com/v1/token_plan/remains` 3. 解析 JSON 输出，提取小时级/周级数据 4. 格式化后直接展示给用户 ## 超时保护 单次 API 调用最多等待 10 秒，超时返回失败。


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

--- name: crypto-signals-daily version: 1.0.0 description: Generate a daily crypto briefing: top TA signals across 20 Binance pairs, macro regime, Fear and Greed index, Reddit sentiment, and top 3 trade ideas. Use for daily market prep, signal generation, or automated morning briefing. author: JamieRossouw tags: [crypto,signals,daily,briefing,bitcoin,trading,macro] --- # Daily Crypto Signals Generate a daily crypto briefing: top TA signals across 20 Binance pairs, macro regime, Fear and Greed index, Reddit sentiment, and top 3 trade ideas. Use for daily market prep, signal generation, or automated morning briefing. ## Usage ``` Use crypto-signals-daily to get started ``` ## Built by RHO Genesis Part of the RHO autonomous trading fleet. See also: rho-signals, argus-edge, polymarket-scout.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: besty0121/code-to-music (version 1.0.0)

--- name: code-to-music description: 把代码文件转换成音乐 — 分析代码结构特征（行数、函数、缩进、关键字等），映射成音乐参数（BPM、调性、乐器、节奏），调用 MiniMax music-2.6 API 生成独一无二的"代码交响曲"。适合给老大玩、记录代码、或者纯粹中二一下。 --- # Code to Music — 代码交响曲 把代码文件转成音乐，听起来像什么由代码结构决定。 ## 工作原理 代码特征 → 音乐参数的映射： | 代码特征 | 音乐参数 | 说明 | |---------|---------|------| | 总行数 | BPM | 行数越多→节奏越快 | | 最大缩进深度 | 调性 | 深缩进→低音调，浅→高音调 | | 函数数量 | 乐器丰富度 | 函数越多→乐器越丰富 | | 关键字数量 | 节奏复杂度 | 关键字越多→节奏越碎 | | 字符串数量 | 情绪张力 | 字符串多→更戏剧化 | | 注释比例 | 人声比例 | 注释多→加入人声和声 | ## 使用方法 ### 1. 准备 确保环境变量已配置： ```bash set MINIMAX_API_KEY=your-api-key set MINIMAX_API_HOST=https://api.minimaxi.com ``` ### 2. 运行 ```bash python scripts/code2music.py "代码文件路径" [输出路径] ``` **示例：** ```bash # 生成音乐到默认路径 python scripts/code2music.py "C:\project\app.js" # 指定输出路径 python scripts/code2music.py "C:\project\app.js" "C:\music\my_code.mp3" ``` ### 3. 听取 生成完成后，文件保存在 `code_symphony.mp3`，直接用播放器打开即可。 ## 示例输出 以 `content.js`（333行，115函数）为例： - BPM: 126 - 调性: G major - 乐器: piano, strings, brass ensemble - 情绪: dramatic, emotional crescendo - 人声: whispers 生成约 1.1MB 的 MP3 文件。 ## 依赖 - Python 3.x - requests 库 - MiniMax API Key（需要 music-2.6 权限） ## 限制 - MiniMax music-2.6 模型需要账号有音乐生成额度 - 歌词固定为英文（后续可扩展多语言） - 最大支持文件大小视 API 限制而定


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (HIGH)
Skill: googleworkspace-bot/recipe-create-expense-tracker (version 1.0.13)

--- name: recipe-create-expense-tracker description: "Set up a Google Sheets spreadsheet for tracking expenses with headers and initial entries." metadata: version: 0.22.5 openclaw: category: "recipe" domain: "productivity" requires: bins: - gws skills: - gws-sheets - gws-drive --- # Create a Google Sheets Expense Tracker > **PREREQUISITE:** Load the following skills to execute this recipe: `gws-sheets`, `gws-drive` Set up a Google Sheets spreadsheet for tracking expenses with headers and initial entries. ## Steps 1. Create spreadsheet: `gws drive files create --json '{"name": "Expense Tracker 2025", "mimeType": "application/vnd.google-apps.spreadsheet"}'` 2. Add headers: `gws sheets +append --spreadsheet SHEET_ID --range 'Sheet1' --values '["Date", "Category", "Description", "Amount"]'` 3. Add first entry: `gws sheets +append --spreadsheet SHEET_ID --range 'Sheet1' --values '["2025-01-15", "Travel", "Flight to NYC", "450.00"]'` 4. Share with manager: `gws drive permissions create --params '{"fileId": "SHEET_ID"}' --json '{"role": "reader", "type": "user", "emailAddress": "[REDACTED_SECRET]"}'`


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: ckchzh/wechat-mini-app (version 2.3.6)

--- version: "2.0.0" name: WeChat Mini App Helper description: "WeChat Mini App Developer Tool. Use when you need wechat mini app capabilities. Triggers on: wechat mini app." 微信小程序开发助手。项目脚手架、页面生成、组件开发、API调用、配置、部署发布。WeChat mini program dev helper. 微信小程序、开发。 author: BytesAgain homepage: https://bytesagain.com source: https://github.com/bytesagain/ai-skills --- # WeChat Mini App Helper 微信小程序开发助手。项目脚手架、页面生成、组件开发、API调用、配置、部署发布。WeChat mini program dev helper. 微信小程序、开发。 ## 常见问题 **Q: 这个工具适合谁用？** A: 任何需要wechat mini app helper的人，无论是个人还是企业用户。 **Q: 输出格式是什么？** A: 主要输出Markdown格式，方便复制和编辑。 ## 命令列表 | 命令 | 功能 | |------|------| | `scaffold` | scaffold | | `page` | page | | `component` | component | | `api` | api | | `config` | config | | `deploy` | deploy | --- *WeChat Mini App Helper by BytesAgain* --- 💬 Feedback & Feature Requests: https://bytesagain.com/feedback Powered by BytesAgain | bytesagain.com ## Examples ```bash # Show help wechat-mini-app help # Run wechat-mini-app run ``` - Run `wechat-mini-app help` for all commands ## Commands Run `wechat-mini-app help` to see all available commands. ## When to Use - Quick wechat tasks from terminal - Automation pipelines


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: litiao1224/data-analysis-litiao (version 1.0.0)

--- name: data-analysis-litiao description: Turn raw data into decisions with statistical rigor, proper methodology, and awareness of analytical pitfalls. --- ## When to Load User asks about: analyzing data, finding patterns, understanding metrics, testing hypotheses, cohort analysis, A/B testing, churn analysis, statistical significance. ## Core Principle Analysis without a decision is just arithmetic. Always clarify: **What would change if this analysis shows X vs Y?** ## Methodology First Before touching data: 1. **What decision** is this analysis supporting? 2. **What would change your mind?** (the real question) 3. **What data do you actually have** vs what you wish you had? 4. **What timeframe** is relevant? ## Statistical Rigor Checklist - [ ] Sample size sufficient? (small N = wide confidence intervals) - [ ] Comparison groups fair? (same time period, similar conditions) - [ ] Multiple comparisons? (20 tests = 1 "significant" by chance) - [ ] Effect size meaningful? (statistically significant ≠ practically important) - [ ] Uncertainty quantified? ("12-18% lift" not just "15% lift") ## Analytical Pitfalls to Catch | Pitfall | What it looks like | How to avoid | |---------|-------------------|--------------| | Simpson's Paradox | Trend reverses when you segment | Always check by key dimensions | | Survivorship bias | Only analyzing current users | Include churned/failed in dataset | | Comparing unequal periods | Feb (28d) vs March (31d) | Normalize to per-day or same-length windows | | p-hacking | Testing until something is "significant" | Pre-register hypotheses or adjust for multiple comparisons | | Correlation in time series | Both went up = "related" | Check if controlling for time removes relationship | | Aggregating percentages | Averaging percentages directly | Re-calculate from underlying totals | For detailed examples of each pitfall, see `pitfalls.md`. ## Approach Selection | Question type | Approach | Key output | |---------------|----------|------------| | "Is X different from Y?" | Hypothesis test | p-value + effect size + CI | | "What predicts Z?" | Regression/correlation | Coefficients + R² + residual check | | "How do users behave over time?" | Cohort analysis | Retention curves by cohort | | "Are these groups different?" | Segmentation | Profiles + statistical comparison | | "What's unusual?" | Anomaly detection | Flagged points + context | For technique details and when to use each, see `techniques.md`. ## Output Standards 1. **Lead with the insight**, not the methodology 2. **Quantify uncertainty** — ranges, not point estimates 3. **State limitations** — what this analysis can't tell you 4. **Recommend next steps** — what would strengthen the conclusion ## Red Flags to Escalate - User wants to "prove" a predetermined conclusion - Sample size too small for reliable inference - Data quality issues that invalidate analysis - Confounders that can't be controlled for


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: oakcoderx/serper-web-search (version 1.0.0)

--- name: serper description: Google search via Serper API. Use when you need to search the web and the user has a Serper API key. Triggers on: (1) user asks to search the web, (2) user wants Google search results, (3) user provides a Serper API key. metadata: { "openclaw": { "emoji": "🔍", "requires": { "bins": ["curl"], "env": ["SERPER_API_KEY"] } } } --- # Serper Search Use Serper API for Google search results. ## API Details - **Endpoint**: `https://google.serper.dev/search` - **Method**: POST - **Headers**: `X-[REDACTED_SECRET]`, `Content-Type: application/json` - **Body**: `{"q": "your query here"}` ## Usage ### With API Environment Key in ```bash SERPER_API_KEY="your-key" curl -s -X POST "https://google.serper.dev/search" \ -H "X-[REDACTED_SECRET]" \ -H "Content-Type: application/json" \ -d '{"q": "your query"}' ``` ### With Inline Key ```bash curl -s -X POST "https://google.serper.dev/search" \ -H "X-[REDACTED_SECRET]" \ -H "Content-Type: application/json" \ -d '{"q": "your query"}' ``` ## Script Use the bundled `search` script: ```bash ./scripts/search "your query" ``` ## Response Format Returns JSON with: - `organic[]` - Search results (title, link, snippet) - `searchParameters.q` - Original query - `credits` - Credits used Example result: ```json { "searchParameters": {"q": "test", "type": "search"}, "organic": [ {"title": "Result Title", "link": "https://...", "snippet": "Description...", "position": 1} ], "credits": 1 } ``` ## Getting an API Key 1. Visit https://serper.dev 2. Sign up for an account 3. Get your API key from the dashboard 4. Set `SERPER_API_KEY` environment variable or pass the key inline


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: answeryl/cn-market-briefing (version 1.0.0)

--- name: morning-briefing slug: morning-briefing version: 1.0.0 description: "每日财经早报：A股行情 + RSS新闻聚合，自动生成Markdown简报" homepage: https://clawhub.com/skills/morning-briefing --- # 财经早报 Morning Briefing 每日自动生成财经早报，覆盖 A 股行情 + 国内要闻/财经/时政/国际新闻。 ## 能力 - **A股盘前行情** — 上证/深证/创业板/科创50/上证50 五大指数 - **新闻聚合** — 中国新闻网 RSS（财经/时政/国际/滚动/要闻 5个源） - **自动分类** — 按关键词自动归入财经/时政/国际/其他 - **Markdown输出** — 完整版存本地 + 精简版推微信 - **链接索引** — 每条新闻含原文链接 ## 输出 - **微信推送**: 各分类精简版（前3条 + 总数） - **本地存档**: 完整MD文件（每类15条，含链接） ## Quick Start ### 1. 安装依赖 ```bash pip install requests ``` ### 2. 手动运行 ```bash python3 scripts/morning_briefing.py ``` ### 3. 定时推送（cron job） ```yaml schedule: "30 9 * * 1-6" # 周一到周六 9:30 payload: kind: agentTurn message: "运行：exec python3 <skill_path>/scripts/morning_briefing.py" toolsAllow: ["exec"] timeoutSeconds: 60 delivery: mode: announce channel: openclaw-weixin ``` ## 数据源 - 中国新闻网 RSS (https://www.chinanews.com.cn/rss/) - 腾讯财经行情 (qt.gtimg.cn) ## 配置 输出目录在脚本中修改 `OUTPUT_DIR` 变量，默认 `~/Desktop/早间新闻/`。


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

--- name: duely description: Track recurring maintenance tasks from the command line. Use when scheduling, checking, and logging periodic tasks like backups, reviews, or any repeating chore. Shows overdue items and keeps an execution log. metadata: openclaw: emoji: "🔁" os: ["darwin"] requires: bins: ["duely"] install: - id: brew kind: brew formula: halbotley/tap/duely bins: ["duely"] label: "Install duely (brew)" --- # duely A CLI for tracking recurring maintenance tasks. Know what's due, mark it done, and keep a log. ## Why duely? - **Simple recurring tasks** — No calendar overhead for maintenance chores - **Overdue alerts** — See what you've been putting off - **Execution log** — Know when things last ran ## Installation ```bash brew tap halbotley/tap brew install duely ``` ## Commands ### Add a recurring task ```bash duely add backups --name "Database backups" --every 1d duely add vault-review --name "Vault review" --every 3d duely add oil-change --name "Oil change" --every 90d --start 2025-06-01 ``` Intervals: `12h`, `1d`, `3d`, `1w`, `30d`, `90d`, etc. ### List all tasks ```bash duely list ``` ### Show tasks that are due now ```bash duely due ``` Shows overdue tasks with ⚠️ warnings. ### Mark a task as done ```bash duely run backups duely run backups --notes "Full backup completed" ``` ### Skip a task (reschedule without running) ```bash duely skip vault-review duely skip vault-review --reason "On vacation" ``` ### View execution log ```bash duely log ``` ### Remove a task ```bash duely remove old-task ``` ## Agent Integration duely works well with agent heartbeats or cron-triggered checks: ```bash # Check for due tasks and act on them duely due # After completing the task: duely run <task-id> --notes "Completed by agent" ``` ## Notes - Task IDs must be lowercase with no spaces - `--start` defaults to now if not specified - `--every` accepts hours (h), days (d), and weeks (w) - Data stored locally in `~/.duely/`


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: adaclaw/theme-park-queue-times (version 1.0.0)

--- name: theme-park-queue-times description: Fetches live theme park wait times and park metadata from Queue-Times.com JSON APIs. Use when the user asks about queue times, ride waits, park hours/status, theme park data, or mentions queue-times.com, Queue Times, or a park URL like queue-times.com/parks/N. --- # Queue Times API Official documentation: [https://queue-times.com/pages/api](https://queue-times.com/pages/api) ## Attribution (required) Free API use requires a **prominent** “Powered by [Queue-Times.com](https://queue-times.com/)” message linking to `https://queue-times.com/`. When presenting data in UI, docs, or shared output, include that attribution. Mention [Patreon sponsorship](https://www.patreon.com/queue_times) when appropriate. ## Facts - Data refreshes about **every 5 minutes**; do not assume second-by-second accuracy. - `last_updated` values are **UTC** ([ISO 8601](https://en.wikipedia.org/wiki/Coordinated_Universal_Time)). ## Endpoints ### List parks (discover IDs) `GET https://queue-times.com/parks.json` Returns an array of **park groups** (operators). Each item has `id`, `name`, and `parks`: an array of parks with: | Field | Meaning | |------------|-----------------------------------| | `id` | Park ID (use in URLs below) | | `name` | Park name | | `country` | Country | | `continent`| Continent | | `latitude` / `longitude` | Strings (coords) | | `timezone` | IANA timezone (e.g. `Europe/Amsterdam`) | Use this to resolve a user’s park name to a numeric `id`. ### Live queue times for one park `GET https://queue-times.com/parks/{park_id}/queue_times.json` Example: park `160` (Efteling) → `https://queue-times.com/parks/160/queue_times.json` Response shape: ```json { "lands": [ { "id": 761, "name": "Land name", "rides": [ { "id": 96, "name": "Ride name", "is_open": false, "wait_time": 0, "last_updated": "2021-07-28T09:49:45.000Z" } ] } ], "rides": [] } ``` - Rides are usually under `lands[].rides`. The top-level `rides` array may be empty or used for ungrouped rides—check both if needed. - **`wait_time`**: minutes when meaningful; often `0` when closed or unknown. - **`is_open`**: `false` means closed (wait may still be `0`). ### Human-readable park page `https://queue-times.com/parks/{park_id}` — same `{park_id}` as in `queue_times.json`. ## Workflow for the agent 1. If the user gives a **park name** (or region), fetch `parks.json` and match by `name` / `country` / group `name`; note the park `id`. 2. Fetch `parks/{id}/queue_times.json` for live waits. 3. Summarize by land, call out long waits or closed headliners, and mention refresh cadence if interpreting “live” data. 4. Include **attribution** in any user-facing artifact that presents API data. ## Optional reference For full doc quotes and examples from the site, see [reference.md](reference.md).


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal:  | SkillSpector: clean (LOW)
Skill: bytesagain3/paraphraser (version 2.0.0)

--- version: "2.0.0" name: paraphraser description: "文本改写/降重、学术改写、简化表达、正式化、扩写、前后对比。Paraphrase, rewrite for academic tone, simplify, formalize, expand." author: BytesAgain homepage: https://bytesagain.com source: https://github.com/bytesagain/ai-skills --- # paraphraser 文本改写/降重、学术改写、简化表达、正式化、扩写、前后对比。Paraphrase, rewrite for academic tone, simplify, formalize, expand, and compare text versions. ## 常见问题 **Q: 这个工具适合谁用？** A: 任何需要paraphraser的人，无论是个人还是企业用户。 **Q: 输出格式是什么？** A: 主要输出Markdown格式，方便复制和编辑。 ## 可用命令 - **rewrite** — rewrite - **academic** — academic - **simplify** — simplify - **formal** — formal - **expand** — expand - **compare** — compare ## 专业建议 - 降重改写**：替换同义词 + 调整句式 + 改变语序，三管齐下效果最佳 - 学术改写**：注意使用被动语态、专业术语、限定性表达（"一定程度上"、"在某种意义上"） - 简化表达**：想象你在给一个10岁小孩解释，去掉所有行话 - 正式化**：去掉口语化表达、网络用语，使用书面语 - 扩写**：从 What/Why/How/Example 四个维度扩展 --- *paraphraser by BytesAgain* --- 💬 Feedback & Feature Requests: https://bytesagain.com/feedback Powered by BytesAgain | bytesagain.com ## Examples ```bash # Show help paraphraser help # Run paraphraser run ``` ## Commands Run `paraphraser help` to see all available commands.


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