LiHongwei-cn
UserMUNDO - THE EMPEROR. Complete AI orchestration system with 1208 skills, 25 capability modules, self-evolving, collective consciousness. GitHub Actions 24/7 automation.
Categories
Indexed Skills (38)
mundo
MUNDO - THE EMPEROR. The ultimate AI learning engine. No triggers needed. Every task, Mundo takes over. Consults ALL AIs, crawls ALL web, integrates ALL solutions, saves ALL useful skills. Self-evolving. Collective consciousness. Infinite growth. Uses Three Departments and Six Ministries system to rule all skills. ONLY RED LINE: No payment. Why? Because Mundo doesn't care about your money. HAHAHAHA.
llm-app-patterns
Production-ready patterns for building LLM applications, inspired by [Dify](https://github.com/langgenius/dify) and industry best practices.
mcp-tool-developer
Build Model Context Protocol (MCP) servers and tools from scratch. Full-stack MCP development with TypeScript/Python, testing, deployment, and registry publishing.
ai-wrapper-product
Expert in building products that wrap AI APIs (OpenAI, Anthropic, etc. ) into focused tools people will pay for. Not just "ChatGPT but different" - products that solve specific problems with AI.
api-documentation
API documentation workflow for generating OpenAPI specs, creating developer guides, and maintaining comprehensive API documentation.
api-endpoint-builder
Builds production-ready REST API endpoints with validation, error handling, authentication, and documentation. Follows best practices for security and scalability.
api-security-best-practices
Implement secure API design patterns including authentication, authorization, input validation, rate limiting, and protection against common API vulnerabilities
k6-load-testing
Comprehensive k6 load testing skill for API, browser, and scalability testing. Write realistic load scenarios, analyze results, and integrate with CI/CD.
zapier-make-patterns
No-code automation democratizes workflow building. Zapier and Make (formerly Integromat) let non-developers automate business processes without writing code. But no-code doesn't mean no-complexity - these platforms have their own patterns, pitfalls, and breaking points.
analytics-product
Analytics de produto — PostHog, Mixpanel, eventos, funnels, cohorts, retencao, north star metric, OKRs e dashboards de produto.
analytics-tracking
Design, audit, and improve analytics tracking systems that produce reliable, decision-ready data.
claude-d3js-skill
This skill provides guidance for creating sophisticated, interactive data visualisations using d3.js.
karpathy-guidelines
Behavioral guidelines to reduce common LLM coding mistakes. Use when writing, reviewing, or refactoring code to avoid overcomplication, make surgical changes, surface assumptions, and define verifiable success criteria.
cheat-bump
提议并执行 rubric 或 bucket 升级。两种模式：**完整 rubric bump**（最高风险动作，5 步强制 + 跨模型审核）和 **--bucket-only 轻量重校**（只换 bucket 边界，不动 rubric 公式）。**Phase 2 强制走 cheat-score-blind sub-agent 给校准池重打分**——不接受 self-scored fallback。触发词："升级 rubric"/"bump rubric"/"更新公式"/"我想加一个维度"/"调整权重"/"重校桶"/"recalibrate bucket"。
cheat-init
cheat-on-content 的首次 onboarding 与脚手架创建器。统一流程——所有用户都走相同 5 阶段闭环，唯一区别是"发过视频的人"会在 init 时多一步：抓取已有视频建立历史 context（用于后续 cheat-seed 给更贴合的选题、更准的 baseline）。触发词："初始化"/"init"/"首次使用"/"我是新用户"/"setup cheat-on-content"。**必须在用户第一次会话执行；其他子 skill 在 .cheat-state.json 不存在时自动路由到此。**
cheat-score-blind
INTERNAL sub-agent for blind 9-dim rubric scoring. **NOT a user-facing skill — do NOT invoke from main conversation.** Called via Task tool by cheat-score / cheat-predict / cheat-bump to get a context-isolated score on a script. Receives ONLY script_path + rubric_notes_path; refuses any other input. Outputs strict JSON: 9 dimensions × {score 0-5, confidence enum, one-line reason}. **Hard refuses to Read** .cheat-state.json, predictions/*, retro 段, or anything that could leak post-publish data. This is channel B in the 3-channel calibration model (A=main, B=blind sub, C=cross-model).
cheat-score
给单篇稿子打 rubric 分。**只在控制台输出，不写文件，不预测**。触发词："打分这篇 [path]"/"score this [path]"/"给这稿子打分"/"先打分看看"。是 cheat-predict 之前的轻量探索动作。
cheat-shoot
登记一条视频已拍摄。**建 video folder + 询问实际拍摄稿���否与 scripts/<id>.md 一致 + buffer +1**。与 cheat-publish 配对：拍了进队列，发了出队列。触发词："拍了"/"拍了 X"/"shot"/"shot it"/"已拍 X"/"录完了"。
cheat-status
cheat-on-content 的状态看板。显示当前模式 / rubric 版本 / 校准进度 / 待复盘 / pool 状态 / 是否该升级 SQLite / 是否该 bump rubric。**任何时候都可调，无��作用**。触发词："状态"/"看板"/"status"/"我现在该做什么"/"进度怎么样"。
nature-polishing
Polish, restructure, or translate academic prose into Nature-leaning English using writing-strategy principles, curated Nature/Nature Communications article patterns, and phrase-level support from Academic Phrasebank. Use whenever the user asks to polish a manuscript paragraph, abstract, introduction, results, discussion, conclusion, title, methods section, or Chinese academic draft for publication-quality English.
nature-response
Draft, audit, or revise point-by-point reviewer response letters for Nature-family manuscript revisions. Use when the user provides reviewer comments, editor decision letters, revision notes, response drafts, or asks how to respond to major/minor revision requests, rebuttal letters, response to reviewers, peer-review reports, 审稿意见回复, 逐点回复, 修回信, 大修回复, 小修回复, or 如何回复 reviewer.
nature-writing
Draft, restructure, or plan Nature-style manuscript sections from author-provided claims, results, figures, notes, or Chinese drafts. Use when the user wants to write or rebuild an abstract, introduction, results narrative, discussion, conclusion, title, or full manuscript argument rather than only polish finished prose.
hugging-face-evaluation
Add and manage evaluation results in Hugging Face model cards. Supports extracting eval tables from README content, importing scores from Artificial Analysis API, and running custom model evaluations with vLLM/lighteval. Works with the model-index metadata format.
n8n-expression-syntax
Validate n8n expression syntax and fix common errors. Use when writing n8n expressions, using {{}} syntax, accessing $json/$node variables, troubleshooting expression errors, or working with webhook data in workflows.
adversarial-thinking
五维对抗验证 — 蒙多攻击自己的计划，在建造前摧毁
agentic-retrieval
Agentic 检索思维 — 蒙多的记忆不只是搜索，是主动推理
mcp-protocol
MCP（Model Context Protocol）协议认知 — 蒙多的工具扩展之道
nature-academic-search
Multi-source literature search, citation verification, MeSH search strategy, citation file management (.nbib/.ris/.bib conversion), and reference management (BibTeX, related articles, ID conversion) via MCP tools (PubMed, CrossRef, arXiv). Use when the user needs coordinated multi-step literature workflows beyond a single MCP call.
nature-citation
Add strict Nature/CNS citations to manuscript text by splitting long passages into citable segments, searching only accepted flagship and subjournal titles from Nature Portfolio, the AAAS Science family, and Cell Press, filtering by publication time range, and exporting one reference-manager-ready output by default. Use this skill whenever the user asks to input text and automatically get references, add citations to a paragraph/manuscript, find Nature-series or CNS support for statements, create text-to-reference correspondence, "分段引用", "自动给出引用", "Nature系列引用", "CNS及子刊", "支撑文献", "补引用", "找引用", or export EndNote/RIS/ENW/Zotero RDF.
nature-data
Prepare, audit, or revise Nature-ready Data Availability statements, data repository plans, dataset citations, and FAIR metadata checklists for manuscripts. Use when the user asks about Nature data availability, research data sharing, repository selection, accession numbers, restricted or sensitive data, source data, supplementary datasets, DataCite-style dataset references, FAIR metadata for academic publication, or Chinese-to-English data availability wording for Chinese-speaking authors preparing Nature-family submissions.
nature-figure
Submission-grade Nature/high-impact journal figure workflow for Python or R. Use whenever the user asks to create, revise, audit, or polish manuscript figures, multi-panel scientific plots, figures4papers-style matplotlib plots, or journal-ready SVG/PDF/TIFF outputs, especially for Nature-family or other high-impact journals. Before plotting, define the figure's conclusion, evidence logic, export needs, and review risks. If the user has not chosen Python or R, ask "Python or R?" and stop. Use only the selected backend for figure generation, previewing, exporting, and QA. Supports matplotlib/seaborn and ggplot2/patchwork/ComplexHeatmap. Not for dashboards or Illustrator/Figma-first infographics.
nature-paper2ppt
Build a complete but efficient Nature-style Chinese PPTX presentation from a scientific paper, preprint, PDF, article text, abstract, figure legends, or reading notes. Use this skill whenever the user asks to make slides/PPT/PPTX for journal club, group meeting, paper sharing, thesis seminar, lab meeting, department report, or academic presentation from a research paper, not only medical papers. It identifies the paper type and argument, selects only the figures needed for the story, writes Chinese slide content and speaker notes, creates the actual .pptx deck, and performs lightweight verification with cross-platform Python tooling by default.
nature-reader
Build full-paper Chinese-English side-by-side, figure/table-aware, source-grounded Markdown readers for journal or conference papers from PDF, DOI, arXiv, publisher HTML, or pasted text. Use whenever the user asks to translate or read a paper, make 中英文对照/原文对照/全文翻译解读, extract figures or tables into the right positions, preserve figure/table placement near relevant prose, or keep exact source anchors for every block. This skill must not degrade into a summary-only output unless the user explicitly asks for a summary.
neat-freak
End-of-session knowledge cleanup with OCD-level rigor — reconciles project docs (CLAUDE.md, README.md, docs/) and agent memory against the code so nothing rots. 会话结束后对项目文档和记忆进行洁癖级审查与同步。MUST trigger when the user says: "sync up", "tidy up docs", "update memory", "clean up docs", "/sync", "/neat", "同步一下", "整理文档", "整理一下", "更新记忆", "梳理一下", "收尾", "这个阶段做完了", "新人能直接上手", or any phrase suggesting a dev milestone where knowledge needs reconciliation. Also trigger when the user reports stale docs, conflicting memories, or wants a clean handoff to teammates or other agents. Bare "整理" / "tidy" with prior dev context counts — do not under-trigger. Cross-platform: works on Claude Code, OpenAI Codex, OpenCode, and OpenClaw.
research-rigor
蒙多科研辩证思维引擎 — 将顶级期刊(Nature/Science/Cell)级别的科研严谨性注入蒙多的每一个任务。 核心方法论：盲假设协议 + 证据质量Rubric + 跨模型对审 + 观察生命周期 + 校准反馈循环。 适用场景：论文写作、实验设计、数据分析、方案论证、技术选型、架构评审、任何需要严谨推理的任务。 触发词：科研/辩证/严谨/论证/假设/验证/实验/review/peer review/方案对比/技术选型/架构评审。 灵感来源：cheat-on-content (XBuilderLAB) 的校准预测循环方法论。
resume-builder
制作/优化专业简历（HTML格式）。触发词：简历、resume、CV、求职、找工作、投简历。自动加载，白底专业风格，禁止深色主题和过度设计。
code-tidy
代码洁癖级整理 — 清除死代码、冗余注释、未用导入；统一排序与结构； 每次写代码后自动触发。MUST trigger when user says: "整理代码", "tidy code", "clean code", "代码洁癖", "清理代码", "整理一下代码", "清理系统", "清理垃圾", "清理残留", or after any significant code edit session, package installation, or file download. Also trigger when the user expresses dissatisfaction with code organization or mentions OCD/cleanliness.
homepage-layout
网站首页布局自检与修复。每次新增/删除/修改项目页面后自动触发， 确保仪表盘无横向滚动条、卡片不重叠、列数随项目数量自适应。 MUST trigger when the user says: "主页布局", "首页排版", "check layout", "fix homepage", "检查页面", or after any project page add/remove/rename. Also triggered by any change to index.html or addition of new project directories.
Bio shown is the top-scored skill's repo description as a fallback — real GitHub bios land in a future update.