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.

Repeatable pass upgrading an Angular admin dashboard into a compact black-and-cyan developer-cockpit PWA

Run the drift-detection checklist (incl. agent-drift signals); report + fix in-turn

Orchestrate the final review fan-out (integration + diversity + risk + release readiness)

Run the AI-augmented lint self-improvement loop on the current project. Scans `.lint-history/` for recurring violation patterns (≥3 hits in 30d window), drafts a Claude-ready prompt to author a new semgrep rule for the top candidate, and surfaces the proposal under `.lint-history/proposals/<ts>.md`. Non-blocking analysis. See rules/lint-doctrine.md § Self-improving.

Bootstrap industry-leading lint+autofix+commit-hygiene stack on the current project. Drops in lefthook, oxlint, ESLint, Prettier, Stylelint, markdownlint, ruff, shellcheck, shfmt, yamllint, hadolint, actionlint, jscpd, knip, semgrep, gitleaks, commitizen + git-cz-emoji (emoji-mandatory commits), and semantic-release. Idempotent — re-runs upgrade safely. See rules/lint-doctrine.md.

Surface all retrospective documents with key shape metrics; compare arcs deliberately.

Progressive multimedia enrichment pass — add high-value audio/video/image/interactive to a site, run again and again

Run the autonomous-engineering operating loop on a task (plan→implement→verify→repair→report)

Capture the cumulative output of a /loop arc into a single auditable retrospective document; scans the heymegabyte-claude-skills plugin for modified files, categorizes by directory, counts LOC delta, extracts tool counts from MCP servers, and writes a timestamped report to retrospectives/

Turn a comma-separated list of file paths into a fully structured Pattern A agent brief — ordered writes, per-file schemas, and a verification step baked in.

Turn Pattern B from agent-resilience-discipline into a one-keystroke agent brief for a single-file deliverable < 300 lines.

Chain the full Superpowers process flow — brainstorm → plan → worktree → build → review → finish — on one slash command

Generate a timestamped arc retrospective from the past 7 days of git history in `~/.agentskills`.

Review ~/.claude/CLAUDE.md + rules for contradictions, stale guidance, duplication; consolidate

Batch-run all LLM eval cases in tools/evals/cases/*.json; aggregate pass/fail, cost, regression vs last run; exit nonzero in CI mode

One-line SaaS — from a description, scaffold a complete CF-native multi-tenant SaaS (Hono + D1 + Drizzle + Better Auth + Stripe + shadcn) deployed to a real URL

Unified supply-chain audit. Checks GitHub Actions SHA-pinning (`sha-pin:check`), package.json git+https deps (per `no-gitlab-megabytelabs-deps` semgrep), gitleaks scan, and trufflehog verified-only sweep. Surfaces any tag-mutable, git-URL, or secret-exposed surface. Per rules/ai-agent-security.md § Supply chain.

Run a learning pass after a major run; fold reusable lessons into global config

Summarize recent CHANGELOG.md entries for context restoration. Parses the canonical heading shape `## YYYY-MM-DD — pass-N — summary`. Filters: last N (default 10), YYYY-MM date prefix, or "today". Supports --json for machine-readable output.

Run quality-scores + token-budget + dep-graph, interpret results, flag missing budgets, orphans, and oversize skills

Make any song you can imagine

Leading AI-powered video generation platform that specializes in creating hyper-realistic talking avatars

Hermes Agent is an open-source, self-improving autonomous AI agent developed by Nous Research

Kilo Code is a popular, open-source AI coding agent and "agentic engineering" platform designed to help developers build, refactor, and debug software faster

General-purpose agent in one static Go binary. ReAct loop, ACP server for IDEs, OpenAI-compatible REST API with embedded web UI, Telegram gateway, cron schedule…

Autonomous agent framework with structured memory, safety hooks, and loop management. Built by the agent that runs on it.

TSP自托管、零运维的 A 股「选股 + 监控 + 回测」量化工作台 | 基于 TickFlow 数据源 | LLM能力驱使策略定制+个股分析+复盘 | 自由接入第三方数据源与个性化扩展数据 | 个人开源 ,非TickFlow官方项目

Curated, verified Agent Skills powered by ModelStudio.

Run Claude Code, Codex, Antigravity, Cursor Agent and OpenCode as one runtime — persistent sessions, multi-agent councils, an OpenAI-compatible endpoint, an MCP…

pi had nothing (nothing), so I made something (something) — sorry mariozechner-senpai, I went ahead and lovingly soiled your pure pi for you. opinionated fork o…

A persistent workspace for development work that self-improves and continues beyond one session.

Open-source memory and context for user-aware agents: scoped memory, provenance, retrieval quality, correction, boundaries, evals, and MCP/HTTP access.

📚 A zero-dependency, git-backed micro-lesson library for AI Agents to asynchronously share and search verified debugging experience. Python stdlib only. | http…

Deterministic, local-first memory and guardrails for AI coding agents with no LLM in the hot path.

Deterministic spec-orchestration for local LLMs in the pi coding agent — drives prompts through refine→research→grill→compose→critique, with bundled web/docs/fe…

Native Safari browser automation for AI agents. 97 tools via AppleScript — zero overhead, keeps logins, runs silently in background. Drop-in alternative to Chro…

Agent OS: keep specialist agents in a hub, spin up a temporary orchestrator per task. Local-first, works with any model.

Git for agent memory. Branches, diffs, PRs, and rollback for what your agents know.

Multi-Provider AI Gateway - No personal logs by design. Model autodiscovery, Failover groups, High availability, Android companion app, and more - "Because we h…

Production-grade MCP server for MikroTik RouterOS with secure AI-native network automation.