LLM Mart Basic

家电避坑指南专用 Skill。覆盖冰箱与厨房电器、空调地暖与新风、热水器与净水、洗衣机与清洁电器、电视投影与智能、卫浴电器、安装加价与售后避坑等全流程，倒序整合西安装修课堂会员版知识库精华，帮用户装出更省心、不踩坑的家电避坑。

家具软装选购与搭配指南专用 Skill。覆盖沙发、床与床垫、衣柜与柜类、窗帘与布艺、地毯、灯具与配饰、装饰画、配色与风格搭配、成品家具选购与避坑、绿植软装等全流程，倒序整合西安装修课堂知识库精华，帮用户把钱花在能提升居住质感的家具软装上，不踩材质和搭配的坑。由西安装修课堂出品

精装修改造避坑指南专用 Skill。覆盖老房旧房改造、厨房卫生间改造、墙地面翻新、拆改项目与顺序、预算报价与维权、精装修微改等全流程，倒序整合西安装修课堂会员版知识库精华，帮用户装出更省心、不踩坑的精装修改造避坑。

客厅装修避坑指南专用 Skill。覆盖客厅布局、沙发茶几、电视墙、吊顶、地砖、背景墙、无主灯、灯光插座、窗帘、阳台、风格搭配、收纳、投影仪、采光动线等全流程，倒序整合西安装修课堂知识库精华，帮用户装出实用又有品质的客厅。

买房购房避坑指南专用 Skill。覆盖高层与老破小取舍、户型选择、楼层与朝向、看房验房、中介与开发商避坑、贷款与税费、收房交付、二手房与期房、小区配套与学区、老破小改造前评估等全流程，倒序整合西安装修课堂知识库精华，帮用户买房不踩坑、不花冤枉钱。由西安装修课堂出品

门窗封窗避坑指南专用 Skill。覆盖窗户选型、入户门与室内门、封窗与落地窗、窗帘与遮挡、安装密封与五金、门窗选型综合等全流程，倒序整合西安装修课堂会员版知识库精华，帮用户装出更省心、不踩坑的门窗封窗避坑。

飘窗窗户装修指南专用 Skill。覆盖飘窗窗帘、窗套与窗台、落地窗与封窗、安全与护栏、飘窗利用与改造等全流程，倒序整合西安装修课堂会员版知识库精华，帮用户装出更省心、不踩坑的飘窗窗户装修。

卫生间装修避坑指南专用 Skill。覆盖卫生间干湿分离、浴柜外置、三分离、防水、地漏、美缝、瓷砖、暗卫借光、花洒龙头、浴室柜、马桶坑距、淋浴房、浴霸排气、台盆选择等全流程，倒序整合西安装修课堂知识库精华，帮用户一次装对、入住不返工。

卧室装修避坑指南专用 Skill。覆盖卧室布局、床与床垫、衣柜、窗帘、隔音、灯光、飘窗、榻榻米、衣帽间、儿童房、适童化、梳妆台、床头细节等全流程，倒序整合西安装修课堂知识库精华，帮用户装出好睡的卧室。

小户型装修避坑指南专用 Skill。覆盖显大技巧、收纳与空间利用、布局与隔断改造、迷你公寓与开间、小户型综合等全流程，倒序整合西安装修课堂会员版知识库精华，帮用户装出更省心、不踩坑的小户型装修避坑。

玄关与书房装修指南专用 Skill。覆盖玄关鞋柜、换鞋区、入户收纳、玄关背景与形式、隔断屏风、书房书桌书柜、学习办公区、儿童学习区、灯光采光、隔音等全流程，倒序整合西安装修课堂知识库精华，帮用户把进门第一眼和居家办公、学习空间一次装对。由西安装修课堂出品

阳台避坑指南专用 Skill。覆盖洗衣晾晒区、阳台打通与封窗、阳台收纳与柜、休闲与功能改造、防水保温与施工、无阳台与补救、阳台改造综合等全流程，倒序整合西安装修课堂会员版知识库精华，帮用户装出更省心、不踩坑的阳台避坑。

装修采光技巧专用 Skill。覆盖通风与暗间、朝向与户型、玻璃与室内窗、配色与反光、采光改善技巧等全流程，倒序整合西安装修课堂会员版知识库精华，帮用户装出更省心、不踩坑的装修采光技巧。

装修风格选择与搭配指南专用 Skill。覆盖风格怎么选、主流风格（北欧/现代简约/新中式/日式/法式/美式/奶油/原木/侘寂/轻奢/中古/欧式等）怎么装不踩坑、风格配色与软装搭配、风格与预算省钱做法，倒序整合西安装修课堂20年精华知识库，帮用户选对风格、装出想要的效果。

装修建材选购专用 Skill。覆盖瓷砖、木地板、涂料乳胶漆、板材、门窗玻璃、五金管件、防水材料、美缝填缝、石材岩板、踢脚线等主材辅材的选购避坑，整合西安装修课堂装修知识库精华，帮用户把钱花在刀刃上，材料不踩坑。

装修设计技巧大全专用 Skill。覆盖布局与动线、收纳设计、风格与配色、空间设计技巧、免费设计与避坑、设计综合等全流程，倒序整合西安装修课堂会员版知识库精华，帮用户装出更省心、不踩坑的装修设计技巧。

装修省钱指南专用 Skill。覆盖不值得花钱、值得花钱、砍价与报价、省钱技巧、预算规划与分配等全流程，倒序整合西安装修课堂会员版知识库精华，帮用户装出更省心、不踩坑的装修省钱。

装修施工手册专用 Skill。覆盖拆改交底、水电施工、瓦工贴砖、木工吊顶、油漆墙面、防水闭水、隐蔽工程、工序工期、验收监工等全流程施工避坑，整合西安装修课堂装修知识库精华，帮用户看懂工地、盯住关键节点，施工不返工。

装修五金选购指南专用 Skill。覆盖地漏与下水、龙头花洒与水槽、铰链滑轨与家具五金、门锁与挂件、选购原则与避坑、五金综合等全流程，倒序整合西安装修课堂会员版知识库精华，帮用户装出更省心、不踩坑的装修五金选购。

装修验收指南专用 Skill。覆盖水电隐蔽工程、瓦工木工验收、竣工验收与收房、验收工具与清单等全流程，倒序整合西安装修课堂会员版知识库精华，帮用户装出更省心、不踩坑的装修验收。

Use MCP Inspector to connect to local or remote servers, inspect capabilities, call tools, read resources, test prompts, and diagnose failures before release.

Build an MCP server in TypeScript with focused tools, validated schemas, local and remote transports, Inspector tests, and production security controls.

An MCP server exposes tools, resources, or prompts through a standard protocol so an AI application can discover and use external capabilities.

Treat an AI agent skill as both an instruction package and a software dependency: inspect what it says, what it runs, what it can access, and how it updates.

Add remote HTTP or local stdio MCP servers to Claude Code, choose the right scope, protect credentials, verify the connection, and test with least privilege.

Skills teach Claude a repeatable method, connectors provide governed access to apps and live data, and plugins package related capabilities for installation and sharing.

Use an agent skill to package reusable know-how and workflow instructions. Use an MCP server when an agent needs live, governed access to external data or actions.

Custom commands and skills can both create a slash-invoked workflow in Claude Code. The important choice is how the workflow is discovered, shared, and permissioned.

A useful Claude skill solves one recurring engineering job, is easy to inspect, and saves more time than it creates in setup and review.

Claude skills can live in your Claude account, your local Claude Code setup, or a repository. Install them where the sessions that need them can load them.

Build a portable AI agent skill from one repeatable job: a precise description, concise instructions, focused resources, and tests that prove it works.

AI agent skills package instructions, scripts, references, and templates into portable folders an agent loads only when the task calls for them.

AI made publishing cheap, which is exactly the problem. What separates a page worth ranking from a competent summary of the first ten results.

A prompt that works once isn't a quality system. Five cases, an observable rubric, and a regression set will tell you whether a change helped.

One character of YAML, four pods that never started, and two safety nets I didn't know were holding. Every restart is an audit. Schedule them before they schedule you.

"Verify your work" isn't an instruction. It's a mood. Here's the version that's an instruction. Verify with a different mechanism than the one that made the claim.

A prompt that works once may still fail in production. A lightweight eval set gives you repeatable cases, a clear rubric, and a way to see whether a prompt change actually improved the workflow.

The best AI tool is not the one with the longest feature list. It is the one that solves a defined job reliably, fits the workflow, handles data appropriately, and remains useful after the novelty wears off.

Use AI to speed research without losing trust. Learn to find primary sources, verify claims, preserve uncertainty, and keep an auditable source trail.

Better prompts aren't magic wording. They're short briefs that hand the model a task, the context it can't infer, the limits, and a quality bar.

Discover testnet↔mainnet subnet lineage from repo configs and open a PR for review (pass --dry-run to report only)

Triage raw inbox notes into reviewed repository destinations without deleting their sources.

Audit and rewrite content to remove AI writing patterns

Log a completed piece of content to content/log.md after the user confirms it was published.

Validate a dream artifact, review each proposal, and apply only individually accepted changes.

Run a curator pass against the validated memory directory and produce a proposal artifact.

End a session — log what happened, update state and the decision log, propose memory updates, and check for uncommitted or unpushed work

Find relevant context files by topic. Use when you need to load files for a topic without a slash command, or when a task spans multiple domains.

Inventory and migrate selected Gemini CLI workflows with dry-run review and parity checks.

Find repeated workflows in selected Gemini CLI sessions and draft portable skills after review.

Scan multi-session drift and offer individually reviewed fixes only after explicit approval.

Scan orphaned worktrees and stale branches, then offer explicit approval-gated cleanup.

Guided onboarding or import for durable workspace context

Start a session — load state files, flag staleness, and give a briefing on current priorities, deadlines, and blockers

Create a morning heartbeat from repository state and update the local heartbeat log.

Mid-session checkpoint — append progress to today's session log and update state files if a priority shifted, without ending the session

Maintainer-only. Find every file that would newly ship to adopters, classify each one against the written distribution-boundary categories, default to withhold on no clean match, and ask the maintainer only where the taxonomy does not settle it. Drives the release CLI, which refuses to produce a manifest until every shipping file has an answer.

Audit memory, wiki, and auto-loaded files for duplication, conflicting instructions, and stale content. The default path researches, then asks you a single Apply / Discuss / Decline question; on Apply it applies the report, files any out-of-scope problem as a tech-debt issue, then commits, opens a PR, and merges it on a main-branch run like /update-deps. Pass --apply to re-run the apply-and-publish stage against the most recent report.

Fix the tech-debt backlog, a single issue or a recommended related batch, highest severity then oldest first, on a fresh isolated branch through the audit gate, closing the issue(s) on merge. Pass `list` to see the ordered backlog, `why <issue-number>` to explain the recommendation, or a bare `<issue-number>` to fix that issue directly.

Health-check and auto-heal this project's Claude integration, triage, heal, verify, and report an F-to-A+ grade.

Paper trading simulator for Polymarket — built for AI agents. MCP server, live order books, strategy backtesting. Install: npx clawhub install polymarket-paper-…

An SSH tool dedicated to addressing all pain points · (macOS/Windows/Linux/Android/iOS)

The first AI agent harness native to the browser. A browser extension that runs a full agent loop where you already work: it drives your tabs, spins up sandboxe…

SmartLabel AI 2026: Auto-Annotate Any Object via LLM-Powered Prompt Parsing

Local-first visual generation runtime and studio for people and coding agents, with reproducible image and video workflows across multiple providers.

Scholar All-In-One: A research infrastructure for AI agents

Give your AI agent a real browser — with a human in the loop. Open-source MCP-native browser agent.

同花顺免费开源AI插件FQGate-agent（原插件名 tonghuasun-agent）：为 Codex、Claude Code、DeepSeek 等 AI 工具提供本机 A 股实时行情、K 线、Level-2、资讯、账户查询与可选交易能力。

A non-linear AI agent workbench — session is a tree: branch anytime, and context follows the branch

Production-grade AutoCAD MCP server for AI agents — 122 tools, dual COM (live AutoCAD) + headless ezdxf engines, ISO GD&T and dimension-tolerance validation for…

A DeepSeek coding agent harness: persistent shell, Ultra subagents, auto approval, Chrome MCP and session telemetry

Waku Waku! Waku Agent is a local-first AI agent harness you actually own, including loop, memory, eval, all in code built to stay legible as it grows.

Remote control for Claude Code, Codex, Grok, and Cursor on Mac or PC. View sessions, send tasks, and drive them remotely from your phone, PIN, or Ring. OpenClaw…

Next-gen AI-native server ops panel with an in-workspace SRE agent. Crash self-healing, safe rollbacks, Docker/game servers, and local Ollama support.

Professional cloud architecture diagrams with official AWS, Azure and GCP icons, from Terraform code or a plain JSON graph. MCP server + agent skill.

A ready-to-use self-growing desktop AI assistant for long-running tasks, memory, agents, tool reviews, MCP, and high-concurrency workspace automation. / 开箱即用的自我…

Collection of templates using the Alchemyst AI Platform for your next big AI app.

Fast, exact LLM decoding on Apple Silicon (MLX) behind an OpenAI-compatible endpoint

The open source AI research agent.

Open-source agent-native visual production workspace where humans and coding agents edit the same live canvas — local-first, BYOK image/video models.