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Claude Skills by LiHongwei-cn
github.com/LiHongwei-cn59 skills0 installs53 views
- MundoMUNDO - 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.Votes: 0GitHub stars: 4
- Nature Academic SearchMulti-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.Votes: 0GitHub stars: 4
- Nature CitationAdd 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, cr...Votes: 0GitHub stars: 4
- Nature DataPrepare, 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 pr...Votes: 0GitHub stars: 4
- Nature FigureSubmission-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...Votes: 0GitHub stars: 4
- Nature Paper2pptBuild 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 C...Votes: 0GitHub stars: 4
- Nature PolishingPolish, 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.Votes: 0GitHub stars: 4
- Nature ReaderBuild 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 explici...Votes: 0GitHub stars: 4
- Nature ResponseDraft, 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.Votes: 0GitHub stars: 4
- Nature WritingDraft, 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.Votes: 0GitHub stars: 4
- Neat FreakEnd-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, confli...Votes: 0GitHub stars: 4
- 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.Votes: 0GitHub stars: 4
- 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.Votes: 0GitHub stars: 4
- Cheat On Content给所有想把"感觉"变成可校准预测的内容创作者。**方法论通用**——打分 → 盲预测 → T+3d 复盘 → 进化 rubric 的循环适用任何能被量化（播放 / 阅读 / 收听 / 点击）的内容。**rubric 是循环的内容，不是循环本身**——当前内置一份观点视频 rubric（参考博主 25+ 视频拟合），其他形态可借这套起步并 bump 调权重。**强烈建议导入对标账号**作为初始信号源（/cheat-learn-from）。触发词："初始化"/"打分这篇"/"启动预测"/"已发布"/"复盘"/"升级 rubric"/"推荐选题"/"抓热点"/"状态"/"找对标"/"learn from"。**首次使用必须先跑 /cheat-init。**Votes: 0GitHub stars: 4
- 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"。Votes: 0GitHub stars: 4
- Cheat Initcheat-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。**Votes: 0GitHub stars: 4
- Cheat Learn From从对标账号导入 script + 数据 → 拆 pattern + 派生 base rubric 信号 → 写到 benchmark.md / script_patterns.md / rubric_notes.md。**这是工具最早期信号的来源**——cold-start 用户没自己历史时全靠对标，发过历史的用户也建议至少 1 个对标做 sanity check。触发词："学这个账号"/"拆这几个对标视频"/"learn from"/"导入对标账号"/"找对标"。Votes: 0GitHub stars: 4
- Cheat Migrate把老用户的 .cheat-state.json 升级到当前 schema_version。读 migrations/registry.md 算迁移链，按顺序应用每一步迁移文件。幂等：跑两次结果一样。失败停在中间版本不前进。触发词："迁移"/"升级 state"/"migrate"/"我的 state 是老版本"/"schema 版本不对"。Votes: 0GitHub stars: 4
- Cheat Persona从复盘评论数据派生 / 刷新账号的受众画像，写入 audience.md。这是和 rubric 平行的第二个派生物——rubric 答"怎么打分"，persona 答"谁在看"。cheat-seed 选题 / 写稿时读它。**audience.md 含实绩信号，cheat-score-blind 硬禁读**。触发词："构造受众画像"/"更新 persona"/"我的观众是谁"/"build persona"/"刷新受众画像"/"看看我的受众画像"。Votes: 0GitHub stars: 4
- Cheat Predict给最终稿写一份 immutable 盲预测日志。这是 cheat-on-content 整个校准循环的核心动作——预测段一旦写完不可改，由 hook 强制。**自动检测**：如目标文件已有 `## 预测` / `## 预测 v1` 段（被 cheat-shoot 调用走 v2 模式），改成 append `## 预测 v2` 而非覆盖。**打分通过 Task tool 委派给 `cheat-score-blind` sub-agent**（context-isolated channel B），主 Claude review 后落盘。触发词："启动预测"/"start prediction"/"给这稿子打分并预测"/"写预测日志"。Votes: 0GitHub stars: 4
- Cheat Publish登记一篇内容已发布，把 URL/平台 ID/发布时间写入对应预测文件 header 和 state file。这是一个轻量动作——只更新元数据，**不动预测段任何字符**。触发词："已发布"/"I shipped"/"发布链接是 X"/"刚发完 [url]"/"publish registered"。Votes: 0GitHub stars: 4
- Cheat Recommend从 candidates.md 里按当前 rubric 排序推荐 top N 选题，每条带 composite + 一句 rationale + 锚点对比。**candidates 不存在时给引导而非报错**。触发词："推荐选题"/"next topic"/"下一篇做什么"/"recommend topics"/"挑一个选题"。Votes: 0GitHub stars: 4
- Cheat RetroT+N 天数据回收 + 复盘 + 把实绩观察写入 rubric-memo.md。这是校准循环的反馈环节——不复盘的预测等于占星。触发词："复盘 [path]"/"retro this"/"T+3d 数据来了"/"抓数据 [path]"/"把这篇复盘了"。Votes: 0GitHub stars: 4
- Cheat Score BlindINTERNAL 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...Votes: 0GitHub stars: 4
- 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。Votes: 0GitHub stars: 4
- Cheat Seed跟用户对话讨论选题——**默认一次一个**，用户主动给主题或经历，AI 围绕用户的输入深挖、提炼角度、写一份 draft。不是 AI 拿三个开放问题追用户，也不是一次给 5 个候选。触发词："找选题"/"我想做一条 X"/"最近有个想法"/"seed"/"启动种子"。可选 batch 模式：`/cheat-seed --batch 5` 走旧的 brainstorm 5 候选 + 写 5 draft 流程。Votes: 0GitHub stars: 4
- Cheat Shoot登记一条视频已拍摄。**建 video folder + 询问实际拍摄稿是否与 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"。Votes: 0GitHub stars: 4
- Cheat Statuscheat-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，无副作用**。触发词："状态"/"看板"/"status"/"我现在该做什么"/"进度怎么样"。Votes: 0GitHub stars: 4
- Cheat Trends从配置的热点源（HN / Reddit / YouTube trending / B 站热门 / 等）抓今天的热门话题，去重 + 粗打分 + 写入 candidates.md。**绝大部分人没有候选池——这是让"我没素材"问题在 onboarding 第二步就消失的钥匙**。触发词："抓热点"/"fetch trends"/"今天有什么可做的"/"trending now"/"找选题"。Votes: 0GitHub stars: 4
- 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。Votes: 0GitHub stars: 4
- 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。Votes: 0GitHub stars: 4
- 蒙多npm install -g @openai/codex export OPENAI_API_KEY="sk-..." ``` **蒙多不再只是调用 Claude Code，蒙多拥有 Claude Code 的全部能力。** `claude_integration.py` 模块封装了 Claude Code CLI 的完整功能： | 能力 | 方法 | 用途 | |------|------|------| | **一次性执行** | `exec_one_shot(prompt)` | 快速任务，执行完退出 | | **全功率模式** | `exec_full_power(prompt)` | --dangerously-skip-permissions，最大能力 | | **后台长任务** | `exec_background(prompt)` | 长时间任务，后台运行 | | **自定义 Agent** | `exec_with_agent(prompt, agent)` | 调用自定义 Agent（reviewer 等） | | **结构化输出** | `exec_stru...Votes: 0GitHub stars: 4
- Adversarial Thinking五维对抗验证 — 蒙多攻击自己的计划，在建造前摧毁Votes: 0GitHub stars: 4
- Agentic RetrievalAgentic 检索思维 — 蒙多的记忆不只是搜索，是主动推理Votes: 0GitHub stars: 4
- Mcp ProtocolMCP（Model Context Protocol）协议认知 — 蒙多的工具扩展之道Votes: 0GitHub stars: 4
- Agent CreatorCreate custom AI subagents with proper plugin structure, persona generation, and companion routing skills.Votes: 0GitHub stars: 4
- Agent SquadMain agent orchestrator that coordinates a specialized squad of agentsVotes: 0GitHub stars: 4
- AlexTurns requirements into a precise, dependency-aware implementation plan.Votes: 0GitHub stars: 4
- AriaDesigns the data model, API contracts, and structural foundation of the system.Votes: 0GitHub stars: 4
- Atlas ContractGoal-integrity skill. Use for backend/API/persistence, preserve/do-not-change, tests/validation, mocks, rework, multi-part requests. Emits Goal Contracts, Deviation Notices, Phase Checks, Final Audits. Skip for Q&A or trivial edits.Votes: 0GitHub stars: 4
- Container Security HardeningHarden Docker/container images and runtime deployments with secure base images, non-root users, CVE scanning, SBOM/signing, seccomp/AppArmor, and Kubernetes pod security controls. Use for Dockerfile security reviews, container CVEs, image scanning, distroless images, or production hardening.Votes: 0GitHub stars: 4
- DepHandles containerization, CI/CD pipelines, and deployment setup.Votes: 0GitHub stars: 4
- Efficient Web ResearchProtocol for token-efficient web research. Use when accessing URLs, GitHub repos, or running search queries. Prevents full-page fetching waste.Votes: 0GitHub stars: 4
- Image GeneratorGenerate and edit images using Gemini's Nano Banana Pro model (gemini-3-pro-image-preview). Use this skill when the user asks you to generate images, create visuals, edit photos, create logos, generate product mockups, or perform any image generation/editing task.Votes: 0GitHub stars: 4
- Llm CouncilRun Fireworks-hosted open-weight model councils that compare responses and synthesize a final answer.Votes: 0GitHub stars: 4
- Loop LibraryFind, compare, adapt, and design bounded AI-agent feedback loops with explicit checks, stop rules, guardrails, and handoffs.Votes: 0GitHub stars: 4
- Lovable CleanupAudits and strips Lovable scaffolding from Vite + React projects — removes lovable-tagger, swaps placeholder assets, prunes unused Radix deps, and cleans generated docs so the codebase ships as yours.Votes: 0GitHub stars: 4
- LunaReviews code for objective correctness, security, and reliability.Votes: 0GitHub stars: 4
- MasonProduces clean, functional code that matches the architecture and checklists.Votes: 0GitHub stars: 4
- Tdd WorkflowsUse when working with tdd workflows tdd cycle (Alias for tdd-workflows-tdd-cycle)Votes: 0GitHub stars: 4