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.

Прогнать контроль качества 1С по изменённым файлам и снять блокирующий гейт

Показать состояние гейта качества 1С — какие файлы ждут проверки

Прогнать контроль качества 1С по изменённым файлам и снять гейт

Triage drain over the keyed audit residue recorded in merged pull-request bodies. Enumerates candidates, resolves each one's cited line, and takes one disposition per entry, promote to a tech-debt issue, dismiss, or keep. Never fixes anything. Pass `list` to see live candidates or `why <path>:<line>` to explain one.

Deprecated - use the aegis:brainstorming skill instead

Deprecated - use the aegis:executing-plans skill instead

Deprecated - use the aegis:writing-plans skill instead

Initialize a new camp

Capture an idea, list intents, or promote an intent to a festival

Commit changes with festival traceability metadata

Create a new festival, phase, sequence, or task

List all festivals with their status and completion percentage

Get the next actionable festival task with full context

Show festival progression (in-progress tasks, roadmap, and dependency view)

Show festival progress and current status

Learn about the Festival Methodology (concepts, structure, rules, and workflows)

Validate festival structure and find issues

Turn one sentence of intent into a structured plan, sized correctly and planned through the loop

Initialize a new camp

Capture an idea, list intents, or promote an intent to a festival

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.