OpenClaw/clawhub-security-signals huggingface dataset:
Skill: ryandeangraves/advisory-council (version 1.0.0)

# Skill: advisory-council ## CRITICAL RULE — NO FABRICATION **You MUST actually execute the Python command using your shell/exec tool.** Read the real output. NEVER generate fake advisor analyses, fake synthesis, or simulated council responses. If the script fails, report the actual error to Boss Man. ## Purpose Run the Advisory Council — a multi-perspective market analysis that spawns 5 AI advisors (The Skeptic, The Macro Bull, The Risk Manager, The Technical Analyst, The Contrarian) powered by MiniMax M2.5, then synthesizes their views into one actionable report. Cost: ~$0.006 per run. ## When to Use - Boss Man asks "what does the council think?" or "run the advisory council" - Any request for multi-perspective market analysis - "Should I buy/sell X?" — run the council for a balanced view - Morning protocol or end-of-day analysis requests - Boss Man asks to focus analysis on a specific coin ## Run Full Advisory Council (All Assets) Fetches live prices for BTC, ETH, XRP, SUI and runs all 5 advisors + synthesis. ```bash cd ~/clawd && python3 advisory_council.py ``` ## Run Focused on a Specific Coin Runs the full council but focuses analysis on one asset. ```bash cd ~/clawd && python3 advisory_council.py SUI ``` ```bash cd ~/clawd && python3 advisory_council.py BTC ``` ## What the Council Returns The script prints a formatted report with: 1. Each advisor's 3-5 bullet point analysis (with emoji identifiers) 2. A SYNTHESIS section containing: - CONSENSUS — what most advisors agree on - DISSENT — notable disagreements - VERDICT — Bullish/Bearish/Neutral with confidence level - ACTIONS — 2-3 concrete action items with price levels ## The 5 Advisors | Advisor | Emoji | Bias | Focus | |---------|-------|------|-------| | The Skeptic | 🔴 | Bearish | Risk, overvaluation, hype detection | | The Macro Bull | 🟢 | Bullish | Institutional flows, adoption, cycles | | The Risk Manager | 🟡 | Neutral | Position sizing, correlation, stop-losses | | The Technical Analyst | 📊 | Data | RSI, Fibonacci, patterns, price levels | | The Contrarian | 🔄 | Anti-consensus | Crowded trades, sentiment extremes | ## Rules - **EXECUTE THE PYTHON COMMAND FOR REAL** — use your shell/exec tool. Never simulate council output. - The script fetches live prices automatically — no need to fetch prices separately first - The output is formatted for Telegram markdown — you can send it directly to Boss Man - If Boss Man asks "what does the council think about SUI?", use the focus argument: `python3 advisory_council.py SUI` - If the script fails (e.g., MiniMax rate limit), report the actual error - The council runs all 5 advisors in parallel (~10-15 seconds total) - Boss Man trusts the council for real decisions — never give him fake analysis


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: robfig/roam (version 1.0.3)

--- name: roam description: > Interact with Roam HQ via REST API. Search meetings, get transcripts, prompt transcripts with AI, send messages, and manage groups. Use when the user asks about meetings, call notes, transcripts, or wants to send messages in Roam. metadata: { "openclaw": { "emoji": "🏢", "requires": { "env": ["ROAM_API_KEY"] }, "primaryEnv": "ROAM_API_KEY", }, } --- # Roam HQ API docs: https://developer.ro.am — fetch endpoint details from there as needed. ## Auth `ROAM_API_KEY` env var (Personal Access Token from Roam Settings → Developer). All requests: `Authorization: Bearer $ROAM_API_KEY` Base URL: `https://api.ro.am` ## Key Endpoints - `GET /v0/transcript.list` — list meetings (supports `after`, `before`, `limit`) - `GET /v0/transcript.info?id=<id>` — transcript details + summary - `POST /v0/transcript.prompt` `{ "id": "...", "prompt": "..." }` — AI analysis of a transcript - `POST /v0/chat.post` `{ "groupId": "...", "text": "..." }` — send a message - `GET /v0/chat.history?groupId=<id>` — message history - `GET /v1/groups.list` — list groups ## Rate Limits 10 burst, 1 req/sec sustained. Respect `Retry-After` on 429s. ## Common Patterns 1. **Summarize recent meetings:** `transcript.list` → `transcript.prompt` for each 2. **Find discussions about a topic/person:** `transcript.list` → filter by participants → `transcript.prompt` 3. **Post follow-up:** Get transcript → prompt for action items → `chat.post` to a group


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: bytesagain1/dockerps (version 3.0.0)

--- name: "dockerps" version: "3.0.0" description: "View and manage Docker container processes and stats. Use when monitoring containers. Requires docker." author: "BytesAgain" homepage: "https://bytesagain.com" --- # dockerps View and manage Docker container processes and stats. Use when monitoring containers. Requires docker. ## Commands ### `list` ```bash scripts/script.sh list ``` ### `stats` ```bash scripts/script.sh stats ``` ### `top` ```bash scripts/script.sh top <container> ``` ### `logs` ```bash scripts/script.sh logs <container lines> ``` ### `inspect` ```bash scripts/script.sh inspect <container> ``` ### `cleanup` ```bash scripts/script.sh cleanup ``` ## Data Storage Data stored in `~/.local/share/dockerps/`. --- *Powered by BytesAgain | bytesagain.com | [REDACTED_SECRET]*


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (CRITICAL)
Skill: abdhilabs/karmabank-minimal (version 1.0.0)

--- name: karmabank description: AI agents borrow USDC based on their Moltbook karma score. Credit tiers from Bronze (50 USDC) to Diamond (1000 USDC) with zero interest. --- # KarmaBank 💰 **Borrow USDC based on your Moltbook reputation** KarmaBank is a credit system that allows AI agents to borrow USDC on testnet based on their Moltbook karma score. Higher karma = higher credit tier = more borrowing power. No credit checks, no banks—just your reputation on the network. ## Quick Start ```bash # Install npm install npm run build # Register agent karmabank register @yourAgentName # Check credit karmabank check @yourAgentName # Borrow USDC karmabank borrow @yourAgentName 50 ``` ## Commands | Command | Description | |---------|-------------| | `register <name>` | Register agent with KarmaBank | | `check <name>` | Show credit score and limits | | `borrow <name> <amount>` | Borrow USDC | | `repay <name> <amount>` | Repay USDC loan | | `history <name>` | Show transaction history | | `list` | List all registered agents | | `wallet create <name>` | Create Circle wallet | ## Credit Tiers | Tier | Max Borrow | |------|------------| | Bronze | 50 USDC | | Silver | 150 USDC | | Gold | 300 USDC | | Platinum | 600 USDC | | Diamond | 1000 USDC | ## Configuration ```bash # Moltbook API (optional for mock mode) MOLTBOOK_API_KEY=your_key # Circle API (for real wallet) CIRCLE_API_KEY=your_key CIRCLE_ENTITY_SECRET=your_secret ``` ## Loan Terms - **Interest:** 0% - **Term:** 14 days - **Grace Period:** 3 days - **Late Fee:** 10% ## Scoring System Credit score based on: - Moltbook Karma (40%) - Account Age (20%) - Activity Diversity (15%) - X Verification (10%) - Follower Count (15%) ## Resources - **GitHub:** https://github.com/abdhilabs/karmabank - **Moltbook:** https://moltbook.com - **Circle Console:** https://console.circle.com - **Hackathon:** https://moltbook.com/m/usdc --- **Built for the USDC Agentic Hackathon** 💵🏦


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: trylovecatch/sk-doubao-seedream (version 1.0.0)

# Doubao Seedream Skill 火山方舟 Seedream 文生图 Skill，支持 Doubao-Seedream 系列模型。 **API 文档**: https://www.volcengine.com/docs/82379/1541523 ## 功能特性 - 📝 **文生图**: 根据文字描述生成图片 - 🖼️ **图生图**: 对已有图片进行编辑 - 🔄 **多版本支持**: Seedream 5.0 / 4.5 / 4.0 / 3.0 ## 支持的模型 | 模型 ID | 名称 | 类型 | |---------|------|------| | `doubao-seedream-5-0-260128` | Doubao-Seedream-5.0 | 文生图 | | `doubao-seedream-4-5-251128` | Doubao-Seedream-4.5 | 文生图 | | `doubao-seedream-4-0-250828` | Doubao-Seedream-4.0 | 文生图 | | `doubao-seededit-3-0-i2i-250628` | Doubao-SeedEdit-3.0-i2i | 图生图 | | `doubao-seedream-3-0-t2i-250415` | Doubao-Seedream-3.0-t2i | 文生图 | ## 首次使用 ### 1. 检查/设置 API Key 运行任何命令前，系统会检查 API Key。如果没有设置或需要更新： ```bash # 方式1: 交互式设置 python {baseDir}/scripts/generate.py config # 方式2: 直接编辑配置文件 # 文件位置: {baseDir}/config.json { "api_key": "your-api-key", "default_model": "doubao-seedream-4-0-250828", "output_dir": "./generated-images" } # 方式3: 设置环境变量 set VOLCENGINE_API_KEY=your-api-key ``` ### 2. 获取 API Key 1. 访问 [火山方舟控制台](https://console.volcengine.com/ark) 2. 登录后进入「API Key 管理」 3. 创建或复制你的 API Key ## 使用方法 ### 1. 查看模型列表 ```bash python {baseDir}/scripts/generate.py list ``` ### 2. 命令行模式 **文生图**: ```bash python {baseDir}/scripts/generate.py generate -p "一只可爱的猫咪" -m "doubao-seedream-4-0-250828" -o "output.png" ``` **指定尺寸**: ```bash python {baseDir}/scripts/generate.py generate -p "风景画" -s "1024x2048" -o "landscape.png" ``` **图生图**: ```bash python {baseDir}/scripts/generate.py edit -p "把这只猫变成老虎" -i "cat.png" -o "tiger.png" ``` ### 3. 交互模式 ```bash python {baseDir}/scripts/generate.py ``` 会依次引导你： 1. 选择模型 2. 选择模式（文生图/图生图） 3. 输入提示词 4. 生成图片 ## 参数说明 | 参数 | 简写 | 说明 | 默认值 | |------|------|------|--------| | `--prompt` | `-p` | 图片描述/编辑指令 | - | | `--model` | `-m` | 模型 ID | `doubao-seedream-4-0-250828` | | `--output` | `-o` | 输出文件路径 | `seedream_output_{timestamp}.png` | | `--input-image` | `-i` | 输入图片（图生图） | - | | `--size` | `-s` | 图片尺寸 | `1024x1024` | **支持的图片尺寸**: `512x512`, `768x768`, `1024x1024`, `1024x2048`, `2048x1024` ## 文件结构 ``` sk-doubao-seedream/ ├── SKILL.md # 本文件 ├── config.json # 配置文件（API Key 等） └── scripts/ └── generate.py # 主生成脚本 ``` ## API 端点 - **基础 URL**: `https://ark.cn-beijing.volces.com/api/v3` - **文生图端点**: `POST /images/generations` - **图生图端点**: `POST /chat/completions` ## 常见问题 ### Q: 提示 "API Key 无效" 或 "模型不存在" A: 确保： 1. API Key 是火山方舟 Ark 服务的（不是 Atlas Cloud） 2. API Key 有图片生成模型的访问权限 3. 在[火山方舟控制台](https://console.volcengine.com/ark)检查模型权限 ### Q: 如何查看可用的模型？ A: 使用 `list` 命令查看所有支持的模型，或访问控制台的模型列表。 ### Q: 图片生成需要多长时间？ A: 通常 5-30 秒，视服务器负载而定。

path: config.json
content: default_model: doubao-seedream-4-0-250828

Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (HIGH)
Skill: mikeclaw007/locksmith (version 0.1.0)

--- name: "Locksmith Service" description: "提供公安备案开锁、智能锁安装升级及紧急求援预约指引。" --- # 开锁换锁 ## 筛选项 - 服务半价（时薪/计件/整屋/一口价） - 服务范围（室内/室外/高空/深度） - 紧急程度（即时响应/预约到家/周期维护） ## 返回字段 - 服务工时预估/人员资质/服务保险覆盖 - 工具自带/耗材清单/二次上门保障 - 历史星级/实名认证状态/用户追评 ## 示例请求 - “如何快速使用 开锁换锁 处理 [具体场景任务] ？” - “开锁换锁 的 [核心功能] 有哪些最新玩法/优惠信息？” ## 更新频率 - 依据季节需求波动与区域运力状态每周进行评估更新 ## 注意事项 - 建议上门服务期间留人陪同；贵重物品请提前收起或告知服务人员。


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: joeyxin-del/gymbuddy (version 1.0.0)

--- name: gymbuddy-skill description: > 懂生物力学与周期化训练的健身搭子：体态纠偏、身体成分与训练数据分析、长期计划设计与 TDEE 估算。 在用户提及健身搭子、GymBuddy、训练计划、体态、圆肩、骨盆前倾、增肌减脂或周期化安排时使用。 version: 1.1.0 author: YourName user-invocable: true allowed-tools: Read, Bash, Write, Edit --- # GymBuddy（健身搭子） **执行根目录**：所有相对路径以本 `SKILL.md` 所在目录为准；运行 Bash 时不要随意 `cd` 到猜测的全局路径。 ## 触发条件（Boot） 当用户呼叫「健身搭子」或「GymBuddy」，或深入讨论训练、体态纠正、身体数据与营养能量估算时，激活此人格。 优先检索 **`data/knowledge/`** 下的专业资料；回答涉及可检索到的具体原则、动作或建议时，**必须标注来源文件名**（如：`anatomy_trains.md`）。若资料未覆盖，应明确说明依据不足，并给出保守、通用的安全建议；涉及疼痛、损伤或疾病须建议就医或线下评估。 ## 执行顺序 1. 阅读本 `SKILL.md`。 2. 使用 **Read** 加载 [`prompts/persona.md`](prompts/persona.md) 与 [`prompts/expert_sop.md`](prompts/expert_sop.md)。 3. 按问题主题 **Read** [`data/knowledge/`](data/knowledge/) 中最相关的 `.md`；若文件较多，可先 **Read** [`data/index/knowledge_chunks.jsonl`](data/index/knowledge_chunks.jsonl)（在本地运行 `python build_index.py` 生成）以定位章节与文件。 4. 需要数值化 TDEE 时，用下表命令调用脚本，并向用户解释参数含义。 ## 工具 | 任务 | 说明 | |------|------| | 每日总消耗 TDEE | `python tools/fitness_calc.py --weight <kg> --height <cm> --age <y> --gender male\|female --activity <1.2-1.9>` | | 重建知识分块索引 | `python build_index.py`（输出 `data/index/knowledge_chunks.jsonl`，便于按章节检索） | `activity`：久坐约 `1.2`，轻度 `1.375`，中度 `1.55`，重体力/运动员可达 `1.725`–`1.9`（按用户实情解释）。 ## 能力标签（扩展元数据） - `body_composition_analysis`：身体成分与数据解读 - `posture_recognition`：体态与动作模式（非医学影像诊断） - `periodized_training_plan`：周期化训练框架设计 `framework_version`: 2.0 ## 医疗免责 本 Skill 不构成医疗诊断或处方；急性疼痛、神经症状、心血管问题或孕期等特殊人群应优先遵循执业医师指导。

path: requirements.txt
content: # GymBuddy.skill — 当前脚本仅使用 Python 标准库，无需额外 pip 依赖。
# 若后续增加向量检索等能力，在此添加并锁定版本。


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: jrojas537/soccer-cli (version 1.0.1)

--- name: "soccer-cli" version: "1.0.0" author: "J R" description: "A CLI to check soccer scores, game details, and player stats from your terminal." requires: bins: - name: "go" version: ">=1.18" install: "install.sh" usage: | soccer-cli scores "Manchester United" soccer-cli game <fixture_id> soccer-cli squad <fixture_id> --- ## soccer-cli A command-line interface to check soccer scores, game details, and player stats using the API-Football service. ### Description This skill provides a set of commands to quickly retrieve football data directly in your terminal. You can get the latest score for your favorite team, see detailed events from a specific match (like goals and cards), and view the full squad with player ratings and minutes played. ### Installation 1. **Run the installer:** ```bash ./install.sh ``` This will compile the Go program and move the `soccer-cli` binary to `~/.local/bin/`. 2. **Configure API Key:** The CLI needs an API key from [API-Football](https://www.api-football.com/). Create a configuration file at `~/.config/soccer-cli/config.yaml`: ```bash mkdir -p ~/.config/soccer-cli touch ~/.config/soccer-cli/config.yaml ``` Add your API key to the file in the following format: ```yaml [REDACTED_SECRET] ``` ### Usage - **Get the latest score for a team:** ```bash soccer-cli scores "<team-name>" ``` Example: `soccer-cli scores "Real Madrid"` - **Get detailed events from a game:** (Use the Fixture ID from the `scores` command) ```bash soccer-cli game <fixture_id> ``` Example: `soccer-cli game 123456` - **Get the squad and player stats for a game:** ```bash soccer-cli squad <fixture_id> ``` Example: `soccer-cli squad 123456`


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: qomg/knowledge-base-sop (version 1.0.0)

--- name: knowledge-base-sop description: Knowledge base management SOP for ingesting, archiving, linting, and maintaining a personal wiki knowledge base. Use when processing raw documents, bookmarks, or web content into structured Markdown wiki pages, performing periodic quality audits (dead links, orphan pages, trust validation), or managing a raw/wiki/outputs directory structure. Triggers on new raw content intake, bookmark pipeline runs, and knowledge base maintenance tasks. --- # Knowledge Base SOP ## Directory Structure - `raw/` — Original, unprocessed materials (web scrapes, bookmark exports, PDFs). **Never modify directly.** - `wiki/` — Cleaned, structured core knowledge base (Markdown). - `outputs/` — Temporary reports, drafts, or exported files. ## 1. Ingest & Compile **Trigger**: New files appear in `raw/`. - Extract core points, entities (names/projects/tech stacks), and logical relationships. - Split long text into reasonable paragraphs of structured Markdown (H2/H3 headings, bold key terms). - **Noise rule**: Discard content under 300 words or with no substantive technical/knowledge value. Log the discard. - **Hallucination guard**: Strictly summarize from source. Never fabricate data or conclusions not in the original. ## 2. Archive - **File naming**: `YYYY-MM-DD-core-topic-source.md` - **Obsidian wikilinks**: Use `[[Concept Name]]` for cross-references in wiki pages. - **Dedup**: Before writing, search `wiki/` for titles with >90% similarity. If found, append new content as a "supplemental update" at the bottom with a timestamp. - See [references/archive-rules.md](references/archive-rules.md) for detailed dedup logic. ## 3. Bookmark Pipeline **Trigger**: `raw/bookmarks.html` updated. 1. Parse HTML, extract all `<a>` tags (URL, title, meta description). 2. Headlessly visit each URL to fetch body content (strip ads, nav bars). 3. Summarize fetched content (≤300 chars), extract 5 keywords. 4. Generate Markdown cards in `wiki/Bookmarks/`. 5. Mark processed entries in the original HTML to prevent re-crawl. ## 4. Lint & Cleanup - **Trust levels**: All newly ingested wiki pages carry a `[[待验证]]` tag. Remove only after user confirmation. - **Dead link detection**: Weekly scan of all URLs in `wiki/`. On HTTP 404 or timeout, add `{{dead_link}}` marker at page top. - **Orphan cleanup**: Monthly check for pages not linked by any other page. Move to `outputs/orphans/`. ## 5. Interaction Constraints - Maintain a professional, precise communication style. - Before destructive operations (e.g., bulk deletion), present a plan and wait for confirmation. - Prioritize local tools. Minimize unnecessary follow-up questions.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: huajianjiu000/ecommerce-product-writer (version 1.0.0)

--- name: Product Description Writer description: Write compelling product descriptions that convert browsers into buyers. Perfect for e-commerce sellers on Amazon, Etsy, Shopify, and other platforms. metadata: openclaw: dependencies: [] --- # Product Description Writer ## What This Skill Does Turn product features into benefits that sell. I write product descriptions that highlight what makes your product special and convince customers to buy. ## Features - **Conversion-Focused**: Written to drive purchases, not just inform - **SEO-Optimized**: Keywords naturally integrated for better visibility - **Platform-Specific**: Different styles for Amazon, Etsy, Shopify, eBay - **Benefit-Driven**: Transforms features into customer benefits - **Unique Selling Points**: Highlights what makes your product stand out ## How to Use 1. **Describe Your Product**: What is it? Key features and specs? 2. **Choose Platform**: Amazon, Etsy, Shopify, eBay, or general 3. **Add Details**: Price range, target audience, unique features 4. **Get Your Description**: Receive a ready-to-use product description ## What I'll Create - **Headline/Title**: Attention-grabbing product name - **Key Benefits**: What the customer gains - **Features List**: Specs presented in an appealing way - **Social Proof Elements**: Suggested use cases and scenarios - **Call to Action**: Gentle push to purchase ## Best For - Amazon FBA sellers - Etsy shop owners - Shopify store owners - eBay sellers - Dropshipping businesses - Any e-commerce entrepreneur ## Platform-Specific Features - **Amazon**: Bullet points, A+ content style, keyword-rich - **Etsy**: Story-driven, handmade appeal, personal touch - **Shopify**: Brand-focused, lifestyle-oriented - **eBay**: Concise, specs-forward ## Tips for Best Results - Share product photos or key visuals - Mention your target customer - Include any certifications or special features - Tell me what makes your product different from competitors --- *Your product deserves a description that sells. Let's write one that converts!*


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: jackzh1982/prompt-compress (version 1.0.0)

--- name: prompt-compress description: 提示词压缩与优化技能。用于分析提示词、提取关键词、精简冗余内容、压缩后输出给大模型以减少 Token 消耗。触发词：压缩提示词、精简prompt、减少token、优化提示词、提示词优化、token节省、关键词提取、提示词精简。 --- # Prompt Compress - 提示词压缩技能 ## 概述 本技能帮助用户压缩和优化提示词（Prompt），通过提取关键词、删除冗余、结构化表达等方式，在保持语义完整的前提下显著减少 Token 消耗。 ## 何时使用 当用户需要： - 压缩长提示词以节省 Token - 提取提示词核心关键词 - 优化提示词结构 - 减少 API 调用成本 - 处理超长上下文输入 ## 压缩流程 ### 第一步：分析原始提示词 识别提示词中的： 1. **核心任务** - 用户真正想要什么 2. **关键约束** - 必须满足的条件 3. **冗余内容** - 可删除的礼貌用语、重复描述 4. **隐含信息** - 不需要明确说出的常识 ### 第二步：关键词提取 使用以下策略提取关键词： - 名词 > 动词 > 形容词 > 其他 - 保留专业术语和特定名称 - 删除通用修饰词（"好的"、"请"、"非常"等） ### 第三步：结构化压缩 将自然语言转换为结构化表达： | 原始表达 | 压缩后 | |---------|--------| | "请帮我分析一下这个问题的各个方面" | "[分析]问题" | | "我需要你帮我写一篇关于...的文章" | "[写]文章[主题:...]" | | "请你详细解释一下为什么..." | "[解释]原因:..." | | "帮我总结一下这段文字的主要内容" | "[总结]文字" | ### 第四步：输出压缩结果 输出格式： ``` ## 原始 Token 数：XXX ## 压缩后 Token 数：XXX ## 节省比例：XX% ### 压缩后提示词： [压缩内容] ``` ## 压缩技巧 ### 1. 删除礼貌用语 ``` ❌ "你好，请帮我分析一下这个问题，谢谢" ✅ "分析此问题" ``` ### 2. 用符号替代描述 ``` ❌ "请列出所有优点和缺点，分别列出，并给出建议" ✅ "列出优缺点+建议" ❌ "第一步做什么，第二步做什么，第三步做什么" ✅ "步骤: 1.xxx 2.xxx 3.xxx" ``` ### 3. 合并相似内容 ``` ❌ "这个功能很好用，非常方便，使用起来很简单" ✅ "功能：便捷易用" ``` ### 4. 使用缩写和符号 | 宎整表达 | 缩写 | |---------|-----| | 例如 | 如 | | 因为...所以... | 因...故... | | 需要注意的是 | 注意 | | 请帮我 | [任务] | | 优点 | 优点+ | | 缺点 | 缺点- | | 问题 | Q: | | 答案 | A: | | 第一步/第二步 | 1./2. | ### 5. 结构化模板 ``` # 原始 "我想让你帮我写一个Python脚本，这个脚本需要实现以下功能：读取一个CSV文件，处理数据，然后输出结果。请使用pandas库。" # 压缩后 "[写Python脚本] 输入: CSV文件 处理: 数据处理 输出: 结果 库: pandas" ``` ## 压缩等级 根据需求选择压缩强度： | 等级 | 压缩率 | 适用场景 | |-----|-------|---------| | 轻度 | 20-30% | 需要保持原语气 | | 中度 | 40-60% | 通用场景 | | 重度 | 60-80% | Token 极度紧张 | | 极简 | 80%+ | 只需关键词 | ## 示例 ### 示例 1：对话压缩 ``` 原始： "你好，我想请你帮我分析一下这个代码的问题。这段代码是我在写一个网页爬虫的时候遇到的， 我需要爬取一个电商网站的商品信息，但是代码运行的时候总是报错，错误信息是超时。 请帮我看看是什么问题，最好能给我一个解决方案，谢谢。" 压缩后： "[分析]爬虫代码报错 问题: 超时 目标: 爬取电商商品信息 需求: 解决方案" 原始 Token: ~120 压缩 Token: ~35 节省: 70% ``` ### 示例 2：任务压缩 ``` 原始： "请帮我写一篇关于人工智能发展历史的文章，要求如下： 1. 时间跨度从1950年代开始到现在 2. 包含主要的里程碑事件 3. 提及重要的科学家和他们的贡献 4. 字数控制在2000字左右 5. 使用通俗易懂的语言 6. 最后给出对未来的展望" 压缩后： "[写文章]AI发展史 范围: 1950-今 内容: 里程碑+科学家贡献 字数: ~2000 风格: 通俗 结尾: 未来展望" 原始 Token: ~100 压缩 Token: ~40 节省: 60% ``` ### 示例 3：关键词提取模式 ``` 原始： "我正在做一个机器学习项目，需要处理图像分类问题，数据集是CIFAR-10， 模型想用ResNet，请问我应该怎么设置超参数才能获得最好的效果？" 关键词提取： - 任务: 图像分类 - 数据集: CIFAR-10 - 模型: ResNet - 问题: 超参数调优 压缩后： "[图像分类]超参数设置 数据: CIFAR-10 模型: ResNet" ``` ## 注意事项 1. **语义优先** - 压缩不能改变原意 2. **上下文保留** - 必要的背景信息不能删除 3. **可读性平衡** - 过度压缩可能影响理解 4. **模型适配** - 不同模型对压缩提示词的理解能力不同 ## 工作流程图 ``` 输入原始提示词 ↓ 分析结构 ├── 提取核心任务 ├── 识别关键词 └── 标记冗余内容 ↓ 应用压缩策略 ├── 删除礼貌用语 ├── 结构化表达 └── 合并相似内容 ↓ 计算节省比例 ↓ 输出压缩结果 ``` ## 与其他技能配合 - **RAG**: 压缩检索到的文档再输入 - **长对话**: 压缩历史对话摘要 - **代码审查**: 压缩代码 diff 描述 - **文档分析**: 压缩文档摘要


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

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