LLM Mart Basic

多商品批量生图流水线。商品清单 CSV → 整批统一视觉的商拍图，带并发、重试、断点续跑、成本熔断与挑图联系表。当用户说「批量生图」「一批商品」「跑整个 SKU 表」「几百个商品出图」时使用。

店铺品牌视觉锁定。一份 brand.yaml 定义模特、色温、构图、留白与文案语气，所有生图技能读它，保证跨 SKU 视觉统一。当用户说「统一风格」「同一个模特」「店铺调性」「品牌规范」「几百个 SKU 看起来像一家店」时使用。

服装工艺细节放大图。服装图 → 面料纹理、走线、织法的微距特写。当用户说「细节图」「特写」「面料放大」「工艺展示」「近景细节」时使用。

从任意图提取干净商品平铺图。真人图 / 街拍图 → 白底平铺商品图。当用户说「提取衣服」「扒图」「转平铺」「抠成商品图」「从买家秀提取」时使用。

同款穿搭换模特换场景做种草图。穿搭图 → 社交平台风格的种草图。当用户说「种草图」「小红书风格」「换场景发帖」「达人图」时使用。

从零创意生图，也可定向改模特、姿势、搭配。一句描述（可选参考图）→ 图。当用户说「创意生图」「生成一张」「改个姿势」「换模板」「随便来张图」时使用。

跨境一套素材多区域本地化。一套素材 → 多语言文案、尺码换算表、区域合规标识。当用户说「跨境本地化」「多语言」「翻译上架」「海外版本」「英文版主图」时使用。

投前 AI 图真实性质检。待检图 → 风险等级 + 8 项逐条判定 + 可直接追加到 prompt 的修正句，可自动重跑直到达标。当用户说「投前检测」「图片质检」「检查有没有崩」「上架前把关」「这图能不能用」时使用。

一键替换服装面料。版式图 + 面料图 → 换上新面料的样衣图，垂坠与光泽随材质变。当用户说「换面料」「换材质」「试布料」「面料上身」「同款不同料」时使用。

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。

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.

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

Periodic multi-reviewer sweep of the whole codebase — surfaces a triaged checkpoint report.

Sanctioned lane for non-behavioral work — docs-only edits, dependency bumps, reverts. Type-scaled gates; no TDD demanded of prose.

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Show the codeArbiter command catalog — the public command list and what each routes to.

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Stop everything and surface a rule conflict — persona vs. docs vs. code. Present both sides and the conflict-hierarchy level; the user resolves. No silent reconciliation.

{{SKILL_ENTRY:context-check}}

{{SKILL_ENTRY:context-creation}}

{{SKILL_ENTRY:debug}}

{{SKILL_ENTRY:decompose}}

Verify the active host install, package, command ownership, enforcement{{IF:pi}}, wrapper self-test, and active-dispatch coverage gap{{ELSE}}, and harmless live-fire probe{{END}}. Read-only.

Start a feature: brainstorm a spec, get it approved, then drive it test-first through the pipeline. The one entry to implementation.

Fix a confirmed bug: a failing regression test first, then a minimal fix, then the rest of the tdd gates.

Opt this repo into codeArbiter — scaffold the root-level .codearbiter/ state store.

Read-only 3-metric governance glance — override rate, small-lane rate, sprint low-confidence ratio — each with a trend arrow vs. the prior 20-commit window.

Sanctioned, logged bypass of a gate or hard rule — one audit line, then proceed.

{{SKILL_ENTRY:finishing-a-development-branch}}

Zero-onboarding, read-only dry-run of the reviewer fleet against the current uncommitted diff. Predicts reviewers, runs the state-free secret scan, writes nothing.

Trim transcript clutter to extend session lifetime — analyze, prune a copy, or toggle the after-each-turn service. Dry-run by default; gains land at resume/compaction, not the current turn.

{{SKILL_ENTRY:decision-variance}}

Persistent session memory for AI coding agents — local-first, with on-device inference, associative recall, and drift detection. Works with Claude Code, Cursor,…

Run Hermes Agent and OpenClaw on the same WeChat account

An AI co-scientist running on your desktop. Claude Science but better.

Emotion Ball 是一套面向 AI 助手的表情引擎:32 种状态表情全部由纯 SVG 与原生 JavaScript 实时驱动,零框架、零图片资源。AI 侧只需输出一个 emotionId,小球即可切换到对应表情,可直接用作聊天机器人、桌面宠物、悬浮助手的情绪表达层。

Agent communication SDK. The open-source agent communication layer for AI agents — email, WhatsApp, Slack, Discord, Telegram, SMS. Python & TypeScript.

The micro-VM for AI agents — light enough to embed on your laptop, elastic enough to power an agentic cloud.

Give each AI agent its own isolated machine with root, Docker, and systemd. Active defense detects and stops threats automatically.

Webhook integration skills for AI coding agents (Claude Code, Cursor, Copilot). Step-by-step guidance for setting up webhook receivers, signature verification,…

Token burn reducer and focus keeper for Claude Code, Codex, Copilot, Gemini CLI, and more: surgical read hints, PDF/Office/CSV/markdown file interception, 160+…

RuvNet Brain — a downloadable, source-grounded brain for Claude Code over Reuven Cohen's (rUv's) RuvNet stack: RuVector/RVF, Ruflo, AgentDB, RuLake, SPARC + 21…

💼 One MCP server to search job boards and company career sites

C++ MCP SDK - build Model Context Protocol (MCP) servers and clients in C++ / CPP. Enterprise-grade security, observability, connectivity. Stdio, HTTP+SSE, Stre…

Open-Source AI Presentation Generator and API (Gamma, Canva, Beautiful AI, Decktopus, Presentations AI Alternative)

Secure, Fast, and Extensible Sandbox runtime for AI agents.

Give your AI agent eyes to see the entire internet. Read & search Twitter, Reddit, YouTube, GitHub, Bilibili, XiaoHongShu — one CLI, zero API fees.

Browser Harness | Self-healing harness that enables LLMs to complete any task.

The World's First Agentic IDE. Visual dashboard: live sessions, task management, code editor, terminal. Epic Swarm parallel workflows. Auto-proceed rules. Autom…

Agenta is a workspace where you and your team build agents and automations.

Terminal Director. One lightweight app, eight features, your whole dev workflow in a single window.

AI turns documents or topics into real, native PowerPoint decks—with native shapes, transitions and animations, data-backed charts and tables on demand, audio n…