Harness-neutral community incident reporting for AI agents. Contribute to collective security by reporting threats.

Automated vulnerability scanner for agent platforms. Performs dependency scanning (npm audit, pip-audit), multi-database CVE lookup (OSV, NVD, GitHub Advisory), SAST analysis (Semgrep, Bandit), and agent-specific static hook inspection for OpenClaw hooks.

Use when checking for security vulnerabilities in NanoClaw skills, before installing new skills, or when asked about security advisories affecting the bot

ClawHub reputation checker for clawsec-suite. Adds a standalone reputation gate before guarded skill installation.

Release automation for Claw skills and website. Guides through version bumping, tagging, and release verification.

Prepare a Neva GitHub release draft from merged PRs, previous release style, and local multi-platform artifacts. Use this for monthly release preparation in nevalang/neva.

Create a Discord-ready Neva release announcement from a GitHub release payload. Use for official Neva Discord release posts.

Convert Neva programs to valid Mermaid flowchart diagrams. Use when asked to visualize Neva code as Mermaid.

Use for Neva source or snippets: authoring, refactoring, debugging, or review.

Use for Go changes in Neva: authoring, refactoring, debugging, or review.

Use when user asks to "read paper", "analyze paper", "summarize paper", "读论文", "分析文献", "帮我看一下这篇paper", "论文笔记", or provides a PDF file that appears to be an academic paper. Specialized for CV/DL papers. Also supports Zotero integration: "读一下这篇论文 ...", "快速看一下这篇论文 ...", "批判性分析这篇论文 ...", "读一下 Zotero 里的 XXX", "批量读一下 Zotero 里 VLA 分类下的论文" **重要触发词**: "读一下 XXX"、"读一下这篇"、"帮我读" → 必须调用此 skill

重新生成 Obsidian 里的目录页 / 导航页（MOC）。 当用户说“更新索引”“更新论文和概念目录”“刷新论文和概念目录”“刷新MOC”时使用。

每日论文推荐的一句话总入口。用户说“今日论文推荐”“过去3天论文推荐”“过去一周论文推荐” “最近3天论文”“看看这周有啥论文”时使用。 内部会自动串联论文抓取、推荐生成、重点论文笔记三步，无需用户手动拆开。

论文点评（3 步流水线的第 2 步）。读取富化后的论文数据，扫描笔记库，生成有态度的推荐点评， 保存推荐文件到 Obsidian，更新 history；git 自动化默认关闭。 触发词："论文点评"、"跑一下论文点评"

论文抓取（3 步流水线的第 1 步）。抓取 arXiv + HuggingFace 最新论文，打分筛选，富化信息， 输出到 /tmp/daily_papers_enriched.json 供后续 skill 使用。 触发词："论文抓取"、"跑一下论文抓取" 支持多天模式："过去3天论文推荐"、"过去一周论文推荐"、"过去一周的论文"、"抓 3 天的论文"、"最近5天"

Generate visually striking PPT slides via OpenAI's gpt-image-2 -- use any style in styles/<collection>/STYLE_ID.md or mimic a user-supplied .pptx template; outputs high-res slide PNGs and a 16:9 .pptx. Use when the user asks to make a presentation, slides, deck, pitch deck, investor PPT, magazine-style PPT, or 做一份 PPT / 生成幻灯片 / 用 gpt-image 生成 PPT / 按这个模板生成 PPT.

Search, download, create, evaluate, and analyze reusable agent skills via SkillNet — the open skill supply chain for AI agents. Use when: (1) Before any multi-step task — search SkillNet for existing skills first, (2) User says "find a skill", "learn this repo/doc", "turn this into a skill", or mentions skillnet, (3) User provides a GitHub URL, PDF, DOCX, PPT, execution logs, or trajectory — create a skill from it, (4) After completing a complex task with non-obvious solutions — create a skill to preserve learnings, (5) User wants to evaluate skill quality, organize/analyze a local skill library, or orchestrate a supported scene. NOT for: single trivial operations (rename variable, fix typo), or tasks with no reusable knowledge.

This skill selects a product variant (e.g., size, quantity) from available options on a product detail page. It is triggered when a product page displays multiple choices, assessing the options (like '1.1 pound (pack of 1)' or 'pack of 2') and selecting one that aligns with user needs, often defaulting to a standard single unit if unspecified.

This skill generates effective search keywords based on parsed product criteria. It is triggered after query parsing, when the agent needs to perform an initial product search on an e-commerce platform. The skill takes structured attributes (e.g., 'women's size 5 patent-beige high heel') and produces a concise, platform-appropriate search string designed to return relevant results, balancing specificity with recall.

Executes a search on an e-commerce platform using parsed keywords. Use when you have extracted search terms from a user query and need to perform the actual search[] action on the WebShop interface. Takes structured search terms and performs a search action, returning a list of product results for evaluation.