This skill should be used when the user asks to create a new skill, repair an existing skill, improve trigger descriptions, reorganize skill structure, or make a Claude skill more reusable and internally consistent.

Word / PDF / PPT 文档解析与数据分析引擎。覆盖三类文件格式的全量提取、表格数值化、图表理解与跨文档汇总分析。**遇到以下任一情况就主动使用本 skill**：①用户上传或指定了 .docx / .doc / .pdf / .pptx / .ppt 文件并要求分析、提取或统计其中内容；②用户出现触发词：Word分析 / PDF解析 / PPT提取 / 文档分析 / 报告解析 / 幻灯片分析 / 发票提取 / 合同分析 / 文档统计 / 错别字 / 语病 / 字号检查 / 简历分析 / 多文档对比；③任务涉及从文档中提取表格、数值、图表、格式（颜色/高亮/字号）、组织架构、时间线等结构化信息。仅不用于：Excel/CSV 数据分析（使用 sn-da-excel-workflow）、纯图片分析（使用 sn-da-image-caption）。

Excel 数据分析多步编排器。覆盖：(1) 读取多 Sheet Excel 文件并统计行数，(2) 大文件检测（≥10k 行自动 Parquet 优化），(3) 数据清洗（缺失值、文本标准化、无效字符），(4) 条件筛选与分类提取，(5) 跨 Sheet 统计聚合，(6) 导出 Excel/CSV 并提供下载链接。覆盖从数据读取到报告生成全流程，按步骤编排 capability 子 skill。**遇到以下任一情况就主动使用本 skill，不要自行写几行 pandas 就回答**：①用户出现触发词：Excel 分析 / 表格分析 / 数据分析 / 数据清洗 / 数据统计 / 数据筛选 / 数据可视化 / 数据导出 / 汇总统计 / 透视表 / 分组统计 / 交叉分析 / 趋势分析 / 对比分析 / 异常值检测 / 去重 / 缺失值处理 / Excel 报告 / 生成报表 / analyze Excel / data analysis / data cleaning / pivot table；②用户上传或指定了 .xlsx / .xls / .csv 文件并要求分析、清洗、统计或可视化；③任务涉及多 Sheet 读取、条件筛选、分类汇总、图表生成中的任意一项；④用户要求导出带格式的 Excel 报告或下载链接。仅不用于：不涉及表格数据的纯文本处理、图片分析（使用 sn-da-image-caption）、单个公式计算的简单问答。

iOS IPA static analysis — class-dump-z / class-dump-ng, Hopper / IDA / Ghidra for Mach-O ARM64, Objective-C runtime introspection, Swift demangling, App Transport Security check, plist analysis, embedded provisioning profile parse. For dynamic Frida/Objection see mobile/SKILL.md.

CTF challenge triage and solve methodology — category detection, tool selection, and multi-step solve chains across pwn/rev/crypto/forensics/web/misc.

macOS endpoint post-exploitation — launchd persistence, TCC bypass, Keychain credential access, dylib hijacking, Gatekeeper/quarantine evasion, and discovery on Apple hosts.

iOS dynamic instrumentation on jailbroken device — Frida/Objection setup, SSL Kill Switch pinning bypass, jailbreak-detection bypass, keychain dump, biometric/LAContext bypass, and ObjC runtime method hooking.

Sub-GHz RF capture and replay for 433/868/915 MHz ISM-band targets (garage doors, car keys, alarm sensors, weather stations). Covers fixed-code replay with HackRF/Flipper Zero/RTL-SDR, rolling-code analysis with rfcat, signal visualization with inspectrum and Universal Radio Hacker, and encoding/modulation identification.

Arbitrary file upload exploitation — webshell upload, extension bypass, content-type manipulation, and upload-to-RCE techniques.

Cross-Site Request Forgery — missing/invalid tokens, method override, JSON CSRF, SameSite gaps, double-submit flaws, login/logout CSRF, and CSRF-via-XSS chains to account takeover.

Siemens S7 PLC attack — TCP/102 ISO-TP+S7-COMM, snap7 / python-snap7 enumeration, DB/M/E/A area read+write, PLC stop/start/run, password bypass (S7-300/400 vs S7-1200/1500 differences), CVE chain (e.g., Stuxnet's legacy primitives, CVE-2019-10936).

EtherNet/IP + CIP (TCP 44818 / UDP 2222) attack playbook — List Identity broadcast, pylogix tag-database dump, tag read/write on Allen-Bradley ControlLogix/CompactLogix, CIP Forward Open, PLC mode change (Stop/Run), and historical Rockwell auth-bypass CVEs. North American ICS dominant protocol.

Cross-chain bridge attack — message-validation bypass (Wormhole class), validator key compromise (Ronin / Harmony class), reentrancy on token-bridge claim, Merkle-proof forgery on optimistic bridges, signature replay across chains. Bridges have lost >$2B; understand why.

Kubernetes RBAC privilege escalation paths — ClusterRole/Role enumeration via `kubectl auth can-i --list`, abuse of pods/exec, pods/portforward, secrets get, escalate verb, bind verb, impersonate verb, system:masters group abuse, ServiceAccount token theft and reuse.

Hunt LLM excessive agency (OWASP LLM06:2025) — agentic systems granted too many tools, too broad permissions per tool, or unsupervised authority to act on the user / business behalf, producing financial loss, data loss, or destructive operations from a single bad token.

List available large language models and send chat completion requests programmatically. Use this skill when you need to call an LLM within a snippet, including model comparison, visual understanding, batch inference, and model performance testing.

Security-first skill vetting protocol for AI agents. Use before installing any skill from the platform skill market, skillhub, GitHub, or other sources. Checks for red flags, permission scope, and suspicious patterns to determine whether a skill is safe to install.

Use when connecting or configuring IM channel bots (WeChat, WeCom, DingTalk, Lark), or when you receive a user message that contains an <im> block indicating it was sent from an IM channel — read this skill to understand what the context means and how to handle it correctly.

Trigger: new skills, agent instructions, documenting AI usage patterns. Create LLM-first skills with valid frontmatter.

Discover and call MCP Server tools via the mcporter CLI. Use when your coordinator notifies you about new MCP tools, or when you need to call external APIs. Includes workflow for generating skill documentation for new MCP servers.