LLM Mart Basic

一张商品图裂变成整套素材。商品图 + 卖点 → 多角度多场景成套图，够铺满一屏。当用户说「裂变套图」「一张变一屏」「凑够详情页」「出一套图」时使用。

服装平铺图一键上身试穿。服装平铺图 + 姿势参考图 → 模特上身商拍图，款式、颜色、织法、版型保持不变。当用户说「平铺图转模特图」「衣服上身」「虚拟试穿」「AI 试衣」「让模特穿上」时使用。

多单品融合成一整套 Look。最多 8 张单品图 → 同一模特身上的完整搭配商拍图，每件单品保真。当用户说「多件搭配」「融图」「组一套 look」「搭配图」「几件衣服合成一张」时使用。

商品换背景。白底商品图 → 逼真场景图，光影与投影匹配新环境。当用户说「换背景」「加场景」「白底转场景」「放到桌面上」时使用。

生成带中文排版的详情页模块。商品图 + 卖点 → 可直接上架的详情页图文模块。当用户说「详情页」「做详情图」「商品描述图」「详情页模块」时使用。

商品精修、去褶皱。随手拍的商品图 → 可直接上架的精修图。当用户说「精修」「去褶皱」「修图」「拍得不好看」「整理一下」时使用。

商品图生成带文案排版的转化主图。商品图 + 卖点 → 带中文文案的电商主图。当用户说「主图」「加卖点文案」「转化图」「促销图」「主图文案」时使用。

主图 A/B 组与转化复盘。商品图 + 卖点 → 多组对照主图 + 每组的差异假设 + 复盘模板。当用户说「A/B 测试」「主图优化」「提点击率」「哪版更好」「换个版本试试」时使用。

静态主图转主图视频。一张商品图 → 3–5 秒可上架的主图短视频。当用户说「主图视频」「图转视频」「让图动起来」「加个视频」时使用。

材质质感增强与纹理重建。糊掉的图 + 高清商品图 → 纹理清晰可信的图。当用户说「增强质感」「图糊了」「补纹理」「提清晰度」时使用。

已有模特图换模特、换背景。一张模特图 → 多人群多场景版本，商品本身不变。当用户说「换模特」「换背景」「换人种」「一图多版」「同一件衣服换个人」时使用。

上架前平台合规校验与自动修复。待上架图 → Amazon / TikTok Shop / Temu / Shopee / 淘宝 各平台的通过或驳回风险报告，可一键修成合规图。当用户说「会不会被驳回」「合规检查」「白底不达标」「主图规格」「传上去被拒」时使用。

商品短视频广告。卖点 → 分镜脚本 → 分段生成 → 拼接加字幕成片。当用户说「做条广告」「短视频」「投流素材」「分镜脚本」「带货视频」时使用。

去水印去文字。带水印 / 文字 / logo 的图 → 干净图，背景纹理自然补全。当用户说「去水印」「去文字」「擦掉 logo」「把字去了」时使用。

平铺图转隐形模特立体图。平铺图 → 有体积感与版型的立体展示图。当用户说「转 3D」「立体图」「隐形模特」「把衣服撑起来」时使用。

UGC 口播种草视频。商品 + 人设 → 口播脚本与成片，达人自拍质感。当用户说「口播视频」「种草视频」「达人风格」「UGC」「真人推荐」时使用。

鞋包配饰真人穿戴图。商品图 + 模特参考图 → 真人佩戴图，落位、透视与阴影自然。当用户说「鞋包上脚」「配饰上身」「墨镜戴上」「首饰佩戴图」「包包上身」时使用。

Apply WIT (Writing Is Thinking) as a human–LLM collaborative scientific reasoning skill for scientific question formulation, finding-driven research planning, next-experiment selection, Results or Discussion review, claim–evidence and reviewer stress tests, manuscript logic audit

Use when creating skill repositories, standardizing or validating skill repo structure, setting up composer/release workflows, configuring split licensing (MIT + CC-BY-SA-4.0), fixing plugin.json / SKILL.md validation or version-parity errors, or releasing a skill version (versio

Conversational design workshop for substantial work. Interviews the human one question at a time, explores 2-3 approaches with trade-offs, and presents the design section by section for approval before writing only design.md, then stops. Combines requirements discovery with codeb

Healthy nodes, a quiet network, 300 restarts in three days, and a latency budget measured in milliseconds

Discovery worked. Ping worked. Every TCP connection timed out, and later the tunnel only worked when someone had a terminal open.

Every VM came back. The cluster did not. Declarative systems converge on config, and the datapath isn't config.

A surprising share of AI-in-the-terminal failures aren't the AI. They're zsh, and a version of bash from 2006.

A Claude Code plugin turns standalone project configuration into a namespaced, installable extension that teams and communities can update as one unit.

None of the safety came from the model. It came from six boring habits.

Skills package instructions and references. Subagents run work in a separate context and return results. They solve different problems and can be composed deliberately.

Six hours in, one step left, everything green, and the incident that didn't happen

CLAUDE.md carries persistent project context. Skills load reusable procedures when relevant. Separating stable facts from task-specific workflows keeps both easier to maintain.

Twenty minutes recovering secrets that never existed, and the one sentence from a human that ended it

An API request routing a model's tool call through an approval gate to a remote MCP server

31 config keys, two audits, and why the first one was wrong in both directions

The official MCP Registry stores standardized server metadata rather than package code. Publishers verify a namespace, describe installation or remote access, and submit immutable versions.

Everyone looks at the Dockerfile. The file that actually leaked the key was the project file.

Remote MCP authorization uses established OAuth standards, but secure integration still requires issuer validation, least-privilege scopes, protected token handling, and server-side enforcement.

"Copy it over and switch the reference" is two steps, and the outage lives in the one nobody checks

stdio fits local processes and prototypes. Streamable HTTP fits hosted services and shared integrations. The right choice follows where the capability runs and who must reach it.

The most important rule wasn't about what I could change. It was about what I was allowed to display.

Tools perform operations, resources expose readable context, and prompts provide reusable templates. Choosing the correct primitive makes an MCP server easier to understand and govern.

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

Analyze Python async code for correctness, patterns, and potential issues.

Profile Python code for performance bottlenecks using cProfile, memory_profiler, or py-spy.

Evaluate public API surfaces against guidelines and exemplars.

Principal-level architecture assessment against ADRs and design patterns.

Systematic bug detection with language-specific expertise.

Run a detailed review that picks its dimensions from what the codebase and diff contain.

Active security hardening of the existing codebase, with a report and concrete proposals to apply.

Audit Makefiles for best practices and portability.

Intensive mathematical analysis for numerical stability and correctness.

Static-analysis hot-spot review for time and space complexity.

Analyze code quality across 6 dimensions (duplication, algorithms, clean code, architecture, errors, style) and apply fixes.

Expert-level Rust audits for safety and correctness.

Audit shell scripts for correctness, safety, and portability.

View recent skill executions with full context and error details.

Analyze skill execution metrics and identify unstable or underperforming skills.

Evaluate and upgrade test suites with TDD/BDD rigor.

Run a computer use task on the desktop via Claude's vision and action API

Stage changes, generate conventional commit message, commit, and push to current branch. One-shot git add-commit-push.

Draft a Conventional Commit message for staged changes. Analyzes diffs, classifies change type, and formats scope/body.

Create git release tags from merged PRs or version args. Pushes a v-prefixed tag to trigger the release pipeline, then confirms the run started.

MCP server for reusable prompt templates, multi-step workflow chains, and quality gates. Compose agentic workflows with an operator syntax; export as native ski…

中国股票数据基础设施，覆盖行情、研报、资金面、筹码、公告、龙虎榜、ETF/期权、舆情互动、基本面、行业板块、宏观与风险事件等核心数据。42+A股数据集，日更、自托管、MCP 原生，零注册、零 API Token

OKF (Open Knowledge Format): Durable, structured memory for AI agents. Author, validate, consume, and maintain portable knowledge bundles through an ecosystem o…

토스증권을 AI 에이전트와 터미널에서 다루는 도구. CLI 와 MCP 서버로 계좌·시세·주문은 물론 웹앱 전용 기능(수급·AI 시그널·스크리너·배당)까지, JSON·CSV 구조화 출력으로 AI 도구·자동화에 바로 연동.

Claude skills for LinkedIn. 11 Claude Code and Codex skills that write human-sounding LinkedIn posts, craft comments that get noticed, analyze your feed, and bu…

MCP server connecting AI agents to ITASCA engines (PFC, FLAC, 3DEC, MPoint, MassFlow) — run geotechnical & geomechanics simulations through natural conversation

A curated list of amazingly awesome articles, people, applications, software libraries and projects related to the knowledge management space

One local dashboard for every Claude Code, Codex, Cursor, Antigravity, and Kilo Code session on your Mac. Spawn in parallel, ship in parallel. Open source, MIT.

Building blocks for frontier OpenAI agents in Rust. Nanocodex empowers you with Codex-level performance anywhere.

The AI agent that lives in your framework/browser

Self-Programming AI Assistant. Capture, automate, and refine all your workflows.

Consider it done. The open-source AI agent that works out of the box · 想到，就能做到。开源、开箱即用的 AI Agent。

Make Any Website into CLI & Use your logged-in browser by AI agent.

ISO 24495 Plain Language skills and Claude Code plugin

Deterministic, fail-open tool routing for Hermes Agent with an optional local-model fallback.

1인 사업가 생산성 키트 — 직원 없이 49개를 자동화했고, 그중 바로 쓸 수 있는 AI 에이전트 스킬 26개(+실행 스크립트)를 공개합니다

AI Agents & MCPs & AI Workflow Automation • (~400 MCP servers for AI agents) • AI Automation / AI Agent with MCPs • AI Workflows & AI Agents • MCPs for AI Agent…

The open-source, self-hosted video conferencing software. Scalable, customizable, and with a powerful AI Meeting Agent.

Business operating system for Claude Code — 57 skills, 21 agents, smart daemon. Unified inbox (WhatsApp/Email/Slack/Telegram), autonomous PR merge, full-AWS mon…

A local-first, cross-platform Electron desktop workspace for Pi Coding Agent, with sessions, project files, browser tools, skills, plugins, and messaging integr…