LLM Mart Basic

为现有前端项目幂等接入 Lovinsp 并验证点击定位源码能力。支持明确输入与结果回读。Use to integrate Lovinsp

Create a @deepseek-ai/dsh-* plugin package end-to-end — choose the extension point or capability seam, scaffold the package, implement the tool/hook/service, and run the repo gates. 触发：新增插件 / 加工具 / 开发 capability。

Publish a validated DSH plugin package (`@deepseek-ai/dsh-*` or `@lovstudio/dsh-*`) to npm, git, or tarball channels and verify it loads in the DeepSeek Harness. Use when the user asks to publish, release, or ship a plugin. 触发：发布插件 / 上架插件 / release dsh 插件。

清理冗余 CSS 并在现有 Tailwind 项目中重构样式。支持明确输入与结果回读。Use to refactor CSS and Tailwind

依据 README 更新 GitHub 仓库描述、主题标签及已核实的官网链接。支持明确输入与结果回读。Use to update a GitHub

分析任意语言项目的目录职责并渐进调整文件结构和引用。支持明确输入与结果回读。Use to improve a project directory

依据项目代码完善 README、安装说明、使用示例与真实品牌资产。支持明确输入与结果回读。Use to create or improve

检查 Next.js 页面元数据、索引规则、站点地图与分享展示。支持明确输入与结果回读。Use to review and improve

配置并备份 Agent 状态栏，支持列出历史版本和恢复。支持明确输入与结果回读。Use to update an agent status

汇总 Git 与项目日志中的检查点、时间范围和演进记录。支持明确输入与结果回读。Use to list a project checkpoint

根据当前 Git 差异和历史记录保存项目里程碑及后续事项。支持明确输入与结果回读。Use to create a project checkpoint.

Write, review, and maintain architecture decision records with clear context, alternatives, consequences, confirmation links, and lifecycle governance. Use when a consequential technical decision or its enforceable architectural constraint must remain understandable. Do not use f

Run a structured multi-agent debate by spawning a panel of expert agents on any question, with convergence-aware iteration and typed synthesis output via the `agent-council` CLI. Use when a decision has genuine tradeoffs, high stakes, or hidden assumptions worth adversarial colla

Design, run, review, or release framework- and vendor-neutral evaluations and observability for AI agents. Use when defining agent evals, datasets, graders, trajectory review, regression analysis, release gates, production traces, or privacy-aware telemetry. Covers task and traje

Operate an evaluated agent with tools and authority in production through a runtime control plane covering versioning, staged rollout, fallback, cost and latency budgets, tool health, human escalation, disablement, and trace-to-eval feedback. Do not use for building agents, desig

Use this skill when creating, reviewing, or editing Agent Skills-format skills, or when implementing skill discovery and loading in an agent client. It covers directory structure, SKILL.md metadata, progressive disclosure, evals, and repository conventions. Do not use this skill

Design and operate an organization's AI governance system: define governance principles, operating models and decision rights, risk frameworks, lifecycle gates, and fairness, transparency, privacy, security, regulatory, and board-oversight controls. Use when standing up a governa

Use when deciding whether an AI-enabled workflow should be adopted, scaled, constrained, redesigned, or retired, and the decision must connect business outcomes, worker or user effects, quality guardrails, full operating cost, telemetry, uncertainty, and accountable governance. D

Use this skill to create subject-neutral images and videos in an analog occultism / industrial CRT noir aesthetic: near-monochrome archival technical atmosphere, severe low-key lighting, tactile signal degradation, industrial geometry, and quiet unresolved tension. Use for portra

Convert Word (.doc/.docx/.docm), PowerPoint (.ppt/.pps/.pot/.pptx/.pptm/.ppsx/.ppsm), Excel (.xls/.xlsx/.xlsm/.xlsb), OpenDocument (.odt/.ods/.odp), RTF, EPUB, CSV, and PDF documents to clean GitHub-Flavored Markdown locally with the Any Doc CLI (npx -y @firecrawl/anydoc@0.2.4):

Fourteen posts of being wrong in production, compressed to checkboxes

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.

Generate a detailed summary of a Liongard environment

Check Liongard connectivity and return system health summary

Audit MFA enrollment across all M365 users, highlighting accounts with no MFA

Look up a Microsoft 365 user by name or email, showing account status, licenses, MFA, and last sign-in

Show Microsoft 365 license inventory - available SKUs, consumed seats, and optimization opportunities

Run the complete M365 offboarding workflow for a departing user - revoke access, handle mailbox, transfer data

Create a Mailprotector block rule for a sender address or domain at a chosen scope

Review the Mailprotector quarantine at any scope and summarize held messages

Onboard a new customer onto Mailprotector - customer, domain, user group, services, users

Release one or more quarantined Mailprotector messages to their recipients

Locate a Meraki device by serial, name, or MAC across an organization's networks

Pull and summarize a Meraki network's L3 firewall rules and flag overly-permissive (any/any allow) rules

Sweep an organization's networks, devices, and appliance VPN status for a site-health overview

Run a read-only Microsoft Entra identity hygiene audit via the Graph Enterprise MCP — inactive user accounts, admins without MFA registered, unassigned/wasted licenses, and a guest user inventory

Conversational Microsoft Entra directory reporting via the Graph Enterprise MCP — license usage, user and group counts, application inventory, and directory composition, formatted for client check-ins and QBRs

Check Mimecast email delivery queue status and identify stuck or deferred messages

Review Mimecast TTP threat logs for URL clicks, malicious attachments, and impersonation attempts

Trace an email through Mimecast by sender, recipient, subject, or date range

Inventory devices for an N-central customer or site with class, warranty, and monitor-health breakdown

Sweep active issues across N-central customers, grouped by severity and probable root cause

Open-source super AI assistant & Agent Harness. Plans tasks, runs tools and skills, self-evolves with memory and knowledge. Multi-model, multi-channel. Lightwei…

Open-source AI browser agent for web automation: a web browsing agent and computer-use agent in plain English. Browser MCP for Claude Code and Gemini CLI.

Agent-native trading terminal built on DeepSeek Harness. Crypto, US, CN and HK in one three-column GUI, 19+ hot-swappable connectors, dry-run by default with hu…

Open-source desktop and web coding agent with a first-party host and harness, durable sessions, model connections, streaming chat, and workspace tools.

OrcaReplay — Time travel for AI agents. Record, replay, fork, and debug any agent run with any model. Built by the OrcaRouter.ai team.

A complete toolkit for connecting R and LLMs

OpenSRE — the memory-first AI SRE. Self-hosted incident investigation with episodic memory, knowledge graph, web console, Slack & Teams. opensre.in

A desktop AI coding assistant that works with your local projects. Ally helps you understand code, edit files, search a workspace, manage tasks, and complete de…

【在线免费使用】 简单快速将SQL或DBML转换为美观的ER图（支持 Agent Skill）/ The best SQL to ER Diagram converter (Support Agent Skill).

Operation-bound protection for autonomous AI agents: contain and verify operations before committing changes, understand intent and risk across long-running wor…

Local-first AI coding agent desktop: Electron + Rust host core + pi Agent Harness + user-installable plugins

Local-only Go static analysis engine with a built-in MCP server. Gives AI coding agents deterministic structural awareness: call graphs, impact analysis, symbol…

Self-hosted AI agent workspace with tool calling, MCP, multi-model routing, sandboxed execution, multi-agent workflows, and LLM-authored 3D character animation…

Automated TDD enforcement for Claude Code

High-performance platform for building websites, e-commerce, and web applications—with Native AI, JavaScript development, and a marketplace for portable sites a…

Autonomous AI-agent orchestration engine for job discovery with decision traces, tool adapters, and production-grade run control.

Token efficient Claude Code full Python rebuild. AI Coding Agent in 310K LoC Python.

OPC — One Person Company. A full team in a single Claude Code skill. Adaptive agent orchestrator with 21 built-in roles, 6 flow templates, and adversarial quali…

Open-source, secure environment with real-world tools for enterprise-grade agents.

MCP server for AI-powered GitHub project management — agent orchestration, PRD-to-issues pipeline, sprint planning, and multi-agent swarm coordination