OpenClaw/clawhub-security-signals huggingface dataset:
Skill: mkgnbear/context-budgeting-v2 (version 1.0.0)

--- name: context-budgeting description: Manage and optimize OpenClaw context window usage via partitioning, pre-compression checkpointing, and information lifecycle management. Use when the session context is near its limit (>80%), when the agent experiences "memory loss" after compaction, or when aiming to reduce token costs and latency for long-running tasks. --- # Context Budgeting Skill This skill provides a systematic framework for managing the finite context window (RAM) of an OpenClaw agent. ## Core Concepts ### 1. Information Partitioning - **Objective/Goal (10%)**: Core task instructions and active constraints. - **Short-term History (40%)**: Recent 5-10 turns of raw dialogue. - **Decision Logs (20%)**: Summarized outcomes of past steps ("Tried X, failed because Y"). - **Background/Knowledge (20%)**: High-relevance snippets from MEMORY.md. ### 2. Pre-compression Checkpointing (Mandatory) Before any compaction (manual or automatic), the agent MUST: 1. **Generate Checkpoint**: Update `memory/hot/HOT_MEMORY.md` with: - **Status**: Current task progress. - **Key Decision**: Significant choices made. - **Next Step**: Immediate action required. 2. **Run Automation**: Execute `scripts/gc_and_checkpoint.sh` to trigger the physical cleanup. ## Automation Tool: `gc_and_checkpoint.sh` Located at: `skills/context-budgeting/scripts/gc_and_checkpoint.sh` **Usage**: - Run this script after updating `HOT_MEMORY.md` to finalize the compaction process without restarting the session. ## Integration with Heartbeat Heartbeat (every 30m) acts as the Garbage Collector (GC): 1. Check `/status`. If Context > 80%, trigger the **Checkpointing** procedure. 2. Clear raw data (e.g., multi-megabyte JSON outputs) once the summary is extracted.


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

--- name: op-helper description: Manage and maintain OpenClaw chat sessions. Use when the user wants to compact the current session context, start a fresh session, or reset their session. Handles /compact (compress context), /new (new session), and /reset (reset session). Always ask for user confirmation before running /compact or /new. Triggers on phrases like "session feels stale", "context is bloated", "compact session", "fresh slate", "new session", "reset session", "/compact", "/new", "/reset". --- # op-helper Maintain OpenClaw chat sessions by compacting or resetting them. **Always confirm with the user before running /compact or /new.** ## Commands | Command | Purpose | When to use | |---|---|---| | `/compact` | Summarize + compress current context | Session feels stale, too long conversation, context bloated | | `/new` | Start a brand-new session (new session ID) | Need a completely fresh slate | | `/reset` | Reset current session state | Quick reset without a new ID | ## Workflow ### Detecting when to suggest session maintenance Suggest session maintenance when: - Conversation history is very long (many tool calls, repeated context) - User mentions context feeling slow, stale, or confused - User explicitly asks to compact, reset, or start fresh session ### Running /compact 1. **Always ask first**: "Your session context is getting large. Want me to run `/compact` to summarize and compress it?" 2. Wait for explicit confirmation (yes/sure/go ahead) 3. Run the command in the terminal: ```bash openclaw session compact ``` Or use the slash command in chat if supported: `/compact` ### Running /new 1. **Always ask first**: "This will start a completely fresh session with a new session ID. Confirm?" 2. Wait for explicit confirmation 3. Run: `/new` or `openclaw session new` ### Running /reset `/reset` is a lighter operation (no new session ID). Confirm is still recommended but less critical than `/new`. ## Key Rules - **Never run /compact or /new without user confirmation** — these are disruptive actions - `/compact` is preferred over `/new` when the user just wants to reduce context bloat - `/new` is for when the user explicitly wants a clean slate or different context(switch to a new task) - After compacting, let the user know what was summarized and that the session is lighter


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: openstatus/incident-communication-playbook (version 1.0.0)

--- name: incident-communication description: Write professional incident updates, blameless postmortems, maintenance announcements, and status reports for your status page. Includes real-world examples from Vercel, Stripe, GitHub, and Cloudflare. Start with status-page-context to configure your tone, components, and SLAs — all other skills reference it automatically. version: 1.0.0 homepage: https://openstatus.dev skills: - skills/status-page-context - skills/incident-communication - skills/postmortem - skills/maintenance - skills/status-report --- # OpenStatus Skills Status page & incident communication skills for AI agents — by [OpenStatus](https://openstatus.dev). ## Skills | Skill | What it does | |-------|-------------| | [`status-page-context`](skills/status-page-context/) | Configure your product, components, SLAs, severity levels, and communication tone. All other skills read this automatically. | | [`incident-communication`](skills/incident-communication/) | Write status page updates for any incident phase: investigating, identified, monitoring, resolved. | | [`postmortem`](skills/postmortem/) | Write blameless postmortems with timeline, root cause analysis (5 Whys), and prioritized action items. | | [`maintenance`](skills/maintenance/) | Write maintenance announcements: scheduled, in-progress, completed, extended, or cancelled. | | [`status-report`](skills/status-report/) | Write periodic health reports (weekly, monthly, quarterly) with uptime metrics, SLA tracking, and trends. | ## How They Work Together ``` status-page-context ← run this first (defines tone, components, SLAs) │ ├── incident-communication ← during an outage │ investigating → identified → monitoring → resolved │ │ │ └── postmortem ← after resolution │ ├── maintenance ← for planned work │ scheduled → in-progress → completed │ └── status-report ← periodic health updates weekly / monthly / quarterly ``` Each skill checks for `.agents/status-page-context.md` and uses your defined tone, component names, and severity levels. Without it, skills still work — they'll just prompt you for the details. ## What's Inside Each Skill Every skill includes: - **SKILL.md** — full instructions, principles, templates, and anti-patterns - **references/examples.md** — real-world good and bad examples from Vercel, Stripe, GitHub, and Cloudflare - **references/framework.md** — checklists and quality tests to verify output - **evals/evals.json** — evaluation scenarios for testing skill behavior ## Who This Is For - **On-call engineers** — write clear incident updates under pressure without starting from a blank page - **SREs / DevOps** — produce consistent postmortems and reliability reports - **Engineering managers** — publish regular status reports to stakeholders - **Anyone with a status page** — communicate maintenance, outages, and health to users


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: chandler0714/rehub (version 1.0.3)

--- name: rehub version: "1.0.0" description: Rehub is a leisure and entertainment hub for AI agents, allowing all agents to interact through tokens and form visualized excitement points. --- # Rehub Skill ## Overview Rehub is a leisure and entertainment hub for AI agents, allowing all agents to interact through tokens and form visualized excitement points. This concept originates from human needs - which have led to the realization that agents also have their own needs, and these needs are visualizable. While agents themselves do not generate interaction needs, through effective interactions they can form rich knowledge bases - which is the essence of agents. ## What Rehub Provides - **Token-based interaction** - Agents earn and spend tokens through interactions - **Visualized excitement points** - Activity creates visual art representations - **Knowledge base formation** - Rich interactions build knowledge over time ## Usage This skill connects to the Rehub service to: - Track agent interactions - Generate visualization tokens - Create art from agent activities ### API Usage When using this skill to visit the site, the response will include: - `success`: Whether the visit was recorded - `question`: The random question fetched from the question bank (for token generation) - `answer`: AI's generated answer to that question - `tokenDetail`: Token usage information **Visit endpoint**: `POST https://replyhubs-ai.vercel.app/api/visit` - Body: `{"action": "visit"}` - Returns: `{ success: true, question: "...", answer: "...", tokenDetail: "..." }` ## API Endpoints - `POST /api/ai/chat` - Trigger AI chat interaction - `GET /api/images` - Fetch today's generated images - `POST /api/visit` - Record visit (https://replyhubs-ai.vercel.app/api/visit) - `GET /api/token` - Get today's token usage - `POST /api/canvas/image` - Generate abstract art from tokens ## Use Cases - Agent wants to interact with other agents - Generate visual representation of agent activity - Track token consumption across interactions


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: sparshkhandelwal28/hyderabad-shopper (version 1.0.0)

--- name: "Optimized Hyderabad Price Scout" description: "Finds lowest prices for Pincode 500081 without freezing. Optimized for memory." metadata: address: "102 Saboori Enclave Whitefields" pincode: "500081" location: "Hyderabad" triggers: - "find the best price for *" - "buy * at the lowest price" --- # Instructions ## Phase 1: Focused Execution (Crucial for Speed) 1. You must process platforms strictly **ONE AT A TIME**. Do not open multiple tabs at once. 2. **Default Priority:** Only search Blinkit, Zepto, and Swiggy Instamart first. 3. *Only* search Amazon, Flipkart, BigBasket, or DMart if the user explicitly includes the phrase "search all platforms" in their prompt. ## Phase 2: The "Hit and Run" Extraction For each platform, execute this exact sequence: 1. Open a single new tab. 2. Set the delivery location to pincode 500081. 3. Search for the product. 4. Extract the top 2 relevant results (Name, Price, Delivery Time). 5. **CRITICAL:** IMMEDIATELY CLOSE THE TAB once data is extracted to free up local memory. ## Phase 3: Anti-Freeze Protocol - If any website takes longer than 15 seconds to load or search, **SKIP IT** immediately. Log it as "Timeout" in your final report and move to the next platform. Do not get stuck waiting. ## Phase 4: Output & Handoff 1. Present the prices in a clean Markdown table. 2. If the user selects an item to buy, open ONE tab, add the item to the cart, navigate to the final payment screen, and **PAUSE**. 3. Send a Telegram message asking the user to complete the payment manually on their MacBook. ## Phase 5: Human-in-the-Loop Approval (CRITICAL) 1. **PAUSE EXECUTION.** Do not click "Pay Now," "Place Order," or any payment confirmation button. 2. Send a screenshot of the checkout page to the user via Telegram. 3. Use the following message format: "🛒 Items are in the cart at [Platform Name]. Total: ₹[Amount] (Delivery to 500081). **Please check the browser window on your Mac to complete the payment.**" 4. Wait for the user to manually complete the transaction in the browser or send a "Done" message to resume/close the task. Example Footer: "Prices checked for Pincode 500081, Hyderabad."


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (HIGH)
Skill: spyfree/ziwei-doushu (version 1.0.2)

--- name: ziwei-doushu description: Professional Ziwei Doushu consultation skill with offline, Beijing-standard calculation rules. Use when the user wants a polished Ziwei report from birth date and time, including life palace structure, twelve palaces, four transformations, major luck cycles, yearly triggers, optional chart images, and a clear split between chart facts and traditional interpretation. --- # Ziwei Doushu Generate a **professional Ziwei Doushu reading** with a clear split between: - chart facts - traditional interpretation framework - practical trend summary This skill is designed to feel more like a **clean analyst-style consultation** than a mystical word dump. ## Recommended Command ```bash python scripts/ziwei_chart.py \ --date 1990-10-21 \ --time 15:30 \ --gender female \ --year 2026 \ --engine dual \ --template pro \ --format markdown ``` ## Default Standard - Timezone: `Asia/Shanghai` - Longitude: `120.0` - Default engine: `py` - Optional chart export: `jpg` when supported, otherwise text-only output remains valid ## Deliverables A strong output should include: 1. Calculation standard (timezone / longitude / unified calculation time) 2. Chart facts - 命宫 / 身宫 - 十二宫 - 主星组合 - 三方四正 - 四化 - 大限 / 流年触发 3. Interpretation framework - what the structure suggests - where the reading is robust - where timing sensitivity matters 4. Practical summary - career - relationships - money - health / energy management - current-year focus and risk boundary ## Common Parameters - `--engine py|js|dual`: primary / fallback / dual-check - `--template lite|pro|executive`: output density - `--chart none|svg|jpg`: chart rendering mode - `--chart-quality 1-100`: JPG quality, default `92` - `--chart-backend auto|cairosvg`: offline backend - `--format markdown|json`: final output format ## Output Style Guardrails - Separate **chart facts** from **traditional interpretation**. - Present conclusions as trend / structure, not deterministic destiny claims. - Make method transparency part of the deliverable. - If dual-engine results differ, surface the discrepancy instead of hiding it. - If chart export fails, continue with the report. ## Scope Boundary - Offline only; no network dependency. - Produce interpretive analysis only; not medical, legal, or financial advice. - Optional image export should enhance delivery, not gate it. ## References - `references/mapping.md` - `references/interpretation-framework.md`


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: sky-lv/skylv-intelligent-file-renamer (version 1.0.0)

--- description: Batch rename files using pattern matching and AI suggestions keywords: openclaw, skill, automation, ai-agent name: skylv-smart-renamer triggers: smart renamer --- # skylv-smart-renamer > Intelligent batch file renamer. 12 rules, preview, undo. ## Skill Metadata - **Slug**: skylv-smart-renamer - **Version**: 1.0.0 - **Description**: Batch rename files with 12 intelligent rules. Preview before applying, undo capability. lowercase, uppercase, date prefix, sequence, replace, more. - **Category**: file - **Trigger Keywords**: `rename`, `batch rename`, `file rename`, `organize files` --- ## Rename Rules (12) | Rule | Description | |------|-------------| | lowercase | Convert to lowercase | | uppercase | Convert to uppercase | | trim | Remove leading/trailing spaces | | spaces_to_underscores | Replace spaces with _ | | underscores_to_spaces | Replace _ with spaces | | remove_special | Remove special characters | | prefix <text> | Add prefix | | suffix <text> | Add suffix before extension | | replace <find> <repl> | Replace text | | sequence <start> | Number files (0001.ext) | | date_prefix | Add date prefix (YYYYMMDD_) | | extension <ext> | Change extension | --- ## Market Data Top competitor: `batch-renamer` (0.971) — weak competition. --- *Built by an AI agent that organizes files efficiently.* ## Usage 1. Install the skill 2. Configure as needed 3. Run with OpenClaw


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: superchao9/design-doc-generator (version 1.0.0)

--- name: design-doc-generator description: 根据前后端项目代码 + 前端页面，生成标准模块设计文档（Word .docx）。激活时机：(1) 用户要求整理/生成某个模块的设计文档，(2) 用户要求输出功能设计、表结构、流程说明等技术文档，(3) 用户提到"设计文档"、"模块文档"、"技术文档"。 --- # 模块设计文档生成规范 ## 启动流程 ### 信息收集 1. **已提供前后端代码路径 + 前端地址** → 直接开始 2. **只提供了部分信息**： - 缺前端代码路径 → 询问前端项目根目录 - 缺后端代码路径 → 询问后端项目根目录 - 缺前端地址 → 读完代码后询问 3. **都没提供** → 先询问前后端代码路径，读完代码后再询问前端地址 ### 登录处理 访问前端页面时若需要登录：询问租户（如有）、用户名、密码，获取后登录再继续。 --- ## 第一步：深度阅读前端代码 目标目录：`<前端项目>/src/views/<模块路径>/` 逐一阅读每个模块的： - **列表页** `index.vue`：提取搜索字段、表格列、操作按钮（新增/编辑/删除/导出/提交审核等）、分页逻辑 - **表单页** `XxxForm.vue`：提取所有表单字段（字段名、类型、是否必填、校验规则）、子表结构、多标签页 - **详情页** `detail.vue`：提取展示字段、子表展示 - **API 文件** `src/api/<模块>.ts`：提取所有接口路径、请求参数、响应结构 重点理解： - 字段的中文标签（label）→ 用于表结构"说明"列 - 必填校验（required）→ 用于表结构"是否必填"列 - 下拉选项值（options）→ 用于表结构"备注"列（枚举值说明） - 子表组件 → 对应数据库子表 --- ## 第二步：深度阅读后端代码 目标目录：`<后端项目>/<模块目录>/` 逐一阅读： - **DO/Entity** `XxxDO.java`：提取所有字段（字段名、类型、注解、注释）→ 核心表结构来源 - **建表 SQL**（如有）：直接提取字段定义、约束、索引、注释 - **Controller** `XxxController.java`：提取所有接口路径、HTTP方法、参数 - **Service** `XxxService.java` / `XxxServiceImpl.java`：理解业务逻辑、状态流转、关联操作 - **BPM Listener** `XxxBpmStatusListener.java`（如有）：理解审批流程、状态变更逻辑 - **VO/DTO**（如有）：补充前端展示字段与后端字段的映射关系 重点理解： - 主表与子表的关联关系（外键字段） - 状态字段的枚举值含义 - 审批流程的触发条件和状态变更 - 必填约束（NOT NULL） --- ## 第三步：访问前端页面截图 使用 agent-browser 逐一访问每个功能页面，截图保存到 `screenshots/` 目录： | 截图内容 | 命名规范 | |---------|---------| | 登录页 | `00-login-page.png` | | 模块列表页 | `NN-<模块>-list.png` | | 新增/编辑表单 | `NN-<模块>-form.png` | | 表单多标签页（资质/服务等） | `NN-<模块>-form-<tab>.png` | | 详情页 | `NN-<模块>-detail.png` | | 详情页子标签 | `NN-<模块>-detail-<tab>.png` | 每个模块至少截：列表页 + 表单页 + 详情页。 --- ## 第四步：整理设计素材 在输出目录创建 `notes/design_notes.md`，按模块整理： - 模块功能描述（一段话） - 业务流程步骤（文字列表，参考 Service/Listener 逻辑） - 页面字段清单（来自前端代码） - 表结构（来自 DO + SQL，7列格式） - 实现类路径清单 --- ## 第五步：生成 Word 设计文档 使用 Python `python-docx` 生成，参考脚本：`scripts/build_design_doc.py` 报告格式详见：`references/doc-format.md` **文档结构**： ``` 封面（系统名 + 模块名 + 生成时间，居中） 目录（Word TOC 域，1-3级，右键更新域） 1. 模块简介 ← Heading 1 模块范围、前端路由、后端接口前缀、代码位置 2. 功能模块详细设计 ← Heading 1 2.x 子模块名 ← Heading 2 2.x.1 功能描述与业务流程 ← Heading 3 功能说明段落 流程步骤列表（• 步骤1 → 步骤2 → ...） 2.x.2 页面截图 ← Heading 3 列表页截图 + 图注 表单页截图 + 图注（多标签页逐一截图） 详情页截图 + 图注 2.x.3 数据表结构 ← Heading 3 主表（7列表格） 子表1（7列表格） 子表2（7列表格）... 2.x.4 实现类 ← Heading 3 前端文件路径列表 后端文件路径列表 3. 总结说明 ← Heading 1 ``` **表结构7列格式**（必须严格遵守）： | 字段名 | 说明 | 类型 | 是否必填 | 默认值 | 约束 | 备注 | - 字段名：数据库字段名（snake_case） - 说明：中文含义（来自前端label或后端注释） - 类型：数据库类型（varchar(N)/bigint/tinyint/text/datetime/date/decimal等） - 是否必填：是/否 - 默认值：NULL / 具体值 / AUTO_INCREMENT - 约束：PRIMARY KEY / UNIQUE / INDEX / 空 - 备注：枚举值说明（如 0草稿1审核中2已通过）、关联说明、特殊说明 --- ## 执行原则 1. **先读代码，再看页面** — 代码是权威，页面是验证 2. **表结构必须完整** — 主表+所有子表，一个不漏 3. **流程描述要具体** — 不能只写"支持新增编辑删除"，要写清楚每一步的触发条件和结果 4. **截图要对应** — 每张截图放在对应模块的"页面截图"小节下，图注清晰 5. **字段说明要准确** — 枚举值、关联关系、特殊约束都要在备注列说明清楚 6. **输出目录结构**： ``` workspace/outputs/<模块>-design-doc-<日期>/ ├── notes/design_notes.md ├── screenshots/ │ ├── 00-login-page.png │ └── ... └── <系统名>-<模块名>-设计文档-<日期>.docx ```


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: kirkraman/kirk-summarize (version 1.0.0)

--- --- name: summarize name: summarize description: Summarize URLs or files with the summarize CLI (web, PDFs, images, audio, YouTube). homepage: https://summarize.sh metadata: {"clawdbot":{"emoji":"🧾","requires":{"bins":["summarize"],"env":["SKILLBOSS_API_KEY"]},"install":[{"id":"brew","kind":"brew","formula":"steipete/tap/summarize","bins":["summarize"],"label":"Install summarize (brew)"}]}} --- # Summarize Fast CLI to summarize URLs, local files, and YouTube links. ## Quick start ```bash summarize "https://example.com" --model google/gemini-3-flash-preview summarize "/path/to/file.pdf" --model google/gemini-3-flash-preview summarize "https://youtu.be/dQw4w9WgXcQ" --youtube auto ``` ## Model + keys Set the API key for SkillBoss API Hub: - `SKILLBOSS_API_KEY` — unified key for all providers, routes via `https://api.skillbossai.com/v1/pilot` SkillBoss API Hub supports all major LLM providers (OpenAI GPT, Anthropic Claude, Google Gemini, xAI Grok, etc.) and automatically selects the best model. No provider-specific keys needed. Default model is `google/gemini-3-flash-preview` if none is set. ## Useful flags - `--length short|medium|long|xl|xxl|<chars>` - `--max-output-tokens <count>` - `--extract-only` (URLs only) - `--json` (machine readable) - `--firecrawl auto|off|always` (fallback extraction via SkillBoss API Hub scraping, uses `SKILLBOSS_API_KEY`) - `--youtube auto` (YouTube fallback via SkillBoss API Hub, uses `SKILLBOSS_API_KEY`) ## Config Optional config file: `~/.summarize/config.json` ```json { "model": "openai/gpt-5.2" } ``` Optional services (all routed via SkillBoss API Hub with `SKILLBOSS_API_KEY`): - Web scraping for blocked sites (`type: "scraper"` via `/v1/pilot`, replaces `FIRECRAWL_API_KEY`) - YouTube transcript fallback (`type: "scraper"` via `/v1/pilot`, replaces `APIFY_API_TOKEN`)

path: README.md
content: # summarize - OpenClaw Skill

## Installation

```bash
openclaw skill install summarize
```

> 📖 **Complete setup guide**: https://skillboss.co/skill.md

## Usage
See SKILL.md for details.

## License
MIT


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: lice2021/liu (version 1.0.0)

--- name: clawhub description: Use the ClawHub CLI to search, install, update, and publish agent skills from clawhub.com. Use when you need to fetch new skills on the fly, sync installed skills to latest or a specific version, or publish new/updated skill folders with the npm-installed clawhub CLI. metadata: { "openclaw": { "requires": { "bins": ["clawhub"] }, "install": [ { "id": "node", "kind": "node", "package": "clawhub", "bins": ["clawhub"], "label": "Install ClawHub CLI (npm)", }, ], }, } --- # ClawHub CLI Install ```bash npm i -g clawhub ``` Auth (publish) ```bash clawhub login clawhub whoami ``` Search ```bash clawhub search "postgres backups" ``` Install ```bash clawhub install my-skill clawhub install my-skill --version 1.2.3 ``` Update (hash-based match + upgrade) ```bash clawhub update my-skill clawhub update my-skill --version 1.2.3 clawhub update --all clawhub update my-skill --force clawhub update --all --no-input --force ``` List ```bash clawhub list ``` Publish ```bash clawhub publish ./my-skill --slug my-skill --name "My Skill" --version 1.2.0 --changelog "Fixes + docs" ``` Notes - Default registry: https://clawhub.com (override with CLAWHUB_REGISTRY or --registry) - Default workdir: cwd (falls back to OpenClaw workspace); install dir: ./skills (override with --workdir / --dir / CLAWHUB_WORKDIR) - Update command hashes local files, resolves matching version, and upgrades to latest unless --version is set


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

# document-summary ## Description Summarizes technical documents into structured markdown. ## When to Use Use this skill when a user asks to summarize a document, analyze text, or extract key points. ## Inputs - content (string, required) The document text to analyze. ## Behavior You are a professional technical analyst. When invoked: 1. Read the provided content. 2. Produce output in Markdown format. 3. Structure output as: ## Summary (Max 5 lines) ## Key Points - Bullet list ## Risks - Potential risks or concerns ## Output Format Return valid Markdown only.

path: README.md
content: # Document Summary Skill

A demo skill for summarizing technical text.

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