微信小程序开发助手

编程专家综合技能套件，含17个子技能：软件项目总控、网站项目总控、API设计、Bug诊断、代码生成、代码审查、重构建议、测试用例生成、技术选型、文档生成、任务拆解与执行、Spec驱动开发、Karpathy编码规范、项目记忆管理、CMS二次开发、前端设计、MySQL数据库。按用户输入关键词路由到对应子技能模板执行。 关键词路由：软件项目总控(软件项目/API服务/后端服务/后台模块/CLI工具/数据脚本/自动化任务/插件项目/完整功能/项目交付/部署/发布/上线/回滚/运维/监控/告警/巡检)；网站项目总控(做网站/建站/企业官网/营销页/CMS网站/网站上线/网站交付)；API设计(RESTful/GraphQL/接口规范/AJAX防卡死/Init-Step-Poll/长任务接口/轮询接口)；Bug诊断(debug/异常堆栈/报错)；代码生成(写代码/实现功能)；代码审查(code review/安全漏洞/代码缺陷)；重构建议(重构/坏味道/代码异味/可维护性)；测试用例生成(单元测试/集成测试/安全测试/性能测试/长任务测试)；技术选型(技术栈/框架选型)；文档生成(API文档/README/技术文档/部署说明/回滚说明/运维文档)；任务拆解与执行(任务分解/Wave执行)；Spec驱动开发(spec/需求对齐/需求规格)；Karpathy编码规范(Karpathy/编码哲学/简洁优先)；项目记忆管理(项目记忆/跨会话/上下文沉淀)；CMS二次开发(CMS/帝国CMS/WordPress/ThinkPHP/PHP8兼容/二次开发/插件开发/模板开发/批量任务/导入导出/生成静态页)；前端设计(UI设计/UX/交互设计/响应式/设计系统/可访问性/页面视觉/浏览器验证/品牌设计/Banner/图标/社媒图/进度条/轮询状态)；MySQL数据库(MySQL/数据库设计/SQL/索引/事务/慢查询/EXPLAIN/DDL/迁移/表结构/SQL优化)。

Interact with GitHub using the `gh` CLI. Use `gh issue`, `gh pr`, `gh run`, and `gh api` for issues, PRs, CI runs, and advanced queries.

将 Excel、CSV、Word、PDF、JSON、TXT、ZIP、电子表单或已有 Python/Web 源码转换、升级或持续修改为可填写、查询、导入导出并可本地/局域网部署的中文业务系统。用于“根据附件生成系统”“把Excel做成系统”“升级或继续修改已有系统”“生成完整部署ZIP”“生成服务端及Windows/macOS填写客户端”等任务。保留3.0的Spec-first变更、影响分析、候选副本、E2E与回滚能力，并强制最终ZIP采用图1式六编号目录：服务端、Windows客户端、macOS客户端、原始资料、申请单模板、说明与版本记录，以及根目录成对启停和密码说明。生成的系统界面布局与功能模块必须参照点工系统的成熟范式（顶栏+左侧多视图导航+卡片+筛选+汇总卡片+表格+弹窗+明细录入+签字审核+看板+汇总导出+系统管理），见 references/ui-functional-patterns.md。

Use this skill when you develop, design, build, deploy, debug, migrate, or troubleshoot CloudBase (腾讯云开发, 云开发, TCB, 微信云开发) projects — Web, 微信小程序, 小程序, uni-app, mobile (iOS, Android, Flutter, React Native). Covers UI (页面, 界面, 表单, dashboard, prototype, 原型); auth (登录, 注册, OAuth, publishable key); databases (NoSQL 文档数据库, MySQL 关系型数据库, PostgreSQL/CloudBase PG, app.rdb(), queryPgDatabase/managePgDatabase, CRUD, security rules); 云函数/cloud functions (serverless, scf_bootstrap); CloudRun (云托管, Dockerfile); 云存储; built-in AI (内置大模型, AI 对话, streaming, 流式输出, 图片生成, generateText, streamText, createModel, generateImage, TokenHub, Hunyuan, DeepSeek, GLM, Kimi, Token Credits 资源包, 小程序成长计划); third-party/custom model onboarding (第三方大模型接入, 大模型调用, LLM API); AI agent (智能体, AG-UI, LangGraph); ops troubleshooting (巡检, 诊断, 日志); spec workflow (需求文档, 技术方案, requirements, tasks.md). Do NOT use for non-CloudBase projects, pure frontend without CloudBase, or self-hosted backends without CloudBase.

AI Agent专用GitHub CLI只读技能，内置缓存与字段裁剪，极致省Token。严禁写操作，支持跨平台与自动降级。

Use the mcporter CLI to list, configure, auth, and call MCP servers/tools directly (HTTP or stdio), including ad-hoc servers, config edits, and CLI/type generation.

YouTube Data API integration with managed OAuth. Search videos, manage playlists, access channel data, and interact with comments. Use this skill when users want to interact with YouTube. For other third party apps, use the api-gateway skill (https://clawhub.ai/byungkyu/api-gateway). Calls run through the `maton` CLI with OAuth login, or over raw HTTP with a Maton API key where the CLI cannot be installed. Every call is authenticated as the user's connection and reaches only what that connection's authorization allows, which the provider enforces on every request; the endpoints documented here are the ones this skill uses, and any other endpoint of this app needs the user to ask for it by name. Default to read and list calls, and confirm every write or new connection with the user. This file also documents the three constructs that turn a YouTube connection into automation, in the order they are used: the connection (the first step), a hosted function that runs a YouTube action through the Maton SDK, and a trigger that calls that function on a schedule or on an event. Those sections are the platform's own reference text, shared with the api-gateway skill, with YouTube examples; they add no YouTube capability - YouTube is not an event source, a trigger cannot read YouTube data, and the files under `references/<source>/triggers.md` are the platform's event catalogues for the sources Maton offers (time, Calendly, GitHub, Gmail, HubSpot, Linear, Notion, Slack, Stripe).

通过输入软件说明书或文本，自动深度解析架构意图，结构化抽取组件与层级，生成Mermaid架构代码，进行专业评审与补全，融合输出完整架构设计文档，并渲染高清架构图。适用于软件工程文档编写、架构评审、技术方案输出等场景。