LLM Mart Basic

端到端测试（生成或执行 E2E 用例）

全自动 PDLC 新功能开发（串联 PRD→设计→TDD→实现→评审→发布）

全自动 Bug 修复（定位→复现→修复→测试→文档）

国际化（i18n）

按设计文档和已有测试用例实现代码（带前置守卫、自检、handoff）

代码质量检查与自动修复

打印循环下一步应执行的命令（机器可读，供 loop 驱动）

收敛循环引擎（自动推进 tdd→implement→review 到 review_done 或 blocked）

新人引导 / 自动化生成用户手册

性能优化

创建 PRD 文档（自动化生成 + 自检 + handoff）

质量闸门——跑真实 check、对照质量目标、出可核对报告，由人签字放行

代码重构（保持外部行为不变，改善内部结构）

管理 feature 关系链（set/query/impact/orphans/rebuild/validate）

迭代复盘——读状态机历史出趋势报告

安全审计

交互式配置 PDLC（当前：状态栏 statusline 的启用/停用/展示项）

发布工作流（收评审通过的功能 → 跑测试 → bump VERSION → 更 CHANGELOG → tag）

管理 00_standards 规范型 surface 产物（add/edit/archive/index）

查看项目 PDLC 状态总览（读 docs/.pdlc-state/ 输出进度）

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.

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.

Art-direction photo pass over the site: add photography only where it earns its place

Audit consolidate or forget stale sensitive or superseded Tree Ring Memory entries

Capture a concise validated lesson decision warning or preference in Tree Ring Memory

Generate Tree Ring harness or recall-quality evidence without confusing it with the full framework release suite

Preview and synchronize DOX-style AGENTS.md guidance as source-linked Tree Ring memory

Recall durable Tree Ring Memory context before starting or resuming work

Check receipt-backed Tree Ring harness readiness without claiming configuration is activation

Запусти Яндекс Браузер с удаленной отладкой (Chrome DevTools Protocol) для отладки веб-приложений.

Проверь уникальность UUID в MDO-файлах 1С по указанному пути (или текущему проекту).

Конвертируй DOCX-файл в Markdown.

Перенеси проект в другую папку, сохранив память, сессии и планы Claude Code.

Command dispatcher for accept.

Command dispatcher for apply.

Command dispatcher for brainstorm.

Command dispatcher for change.

Command dispatcher for define.

Command dispatcher for design.

Command dispatcher for discover.

Command dispatcher for plan.

Command dispatcher for propose.

Conduit — native SwiftUI iOS client for Hermes Agent

一个现代化的可视化规则引擎平台，用于编排复杂的 AI 工作流。在无限画布上设计、测试和部署 AI 流程——无需编写代码。结合 flowgram.ai 的能力与 Java 服务端，提供生产级工作流管理。在此之上提供AI Agent / Copilot的助手编排能力。

Job application tracker and AI-powered job search assistant. Helps job seekers manage their search journey with AI resume review, job matching, task logging, an…

📝 Markdown and HTML renderer for Svelte 5 — built for streaming AI agent output from Claude Code, ChatGPT, and agentic workflows. XSS-safe defaults, token cach…

ServiceNow MCP server: 500+ tools and 26 AI capabilities for any AI (Claude, ChatGPT, Gemini, Cursor, Copilot). Multi-transport (stdio, SSE, HTTP), A2A, dynamic…

Free crypto news API - real-time aggregator for Bitcoin, Ethereum, DeFi, Solana & altcoins. No API key required. RSS/Atom feeds, JSON REST API, historical archi…

Build production-ready AI agents in both Python and Typescript.

From agent user to agent builder: build a Claude Code-style coding agent from scratch in Python: 8 articles, 4 videos, one codebase

🪁 A lightweight, modern Kubernetes dashboard that unifies multi-cluster and resource management, enterprise-grade user governance (OAuth, RBAC, and audit logs)…

Stateful runtime management for LLM agents—inject, manipulate, and retrieve Python objects across turns.

AgentCall lets AI Agents join meetings with voice, video & screen-share to build together. Supports Google Meet, Teams, Zoom (Beta)

Kition brings Markdown, DataTable, WhiteBoard, a tool-using AI agent, browser research, and visual workflows into one desktop workspace.

IntentKit is an open-source, self-hosted cloud agent cluster that manages a collaborative team of AI agents for you.

A powerful Model Context Protocol (MCP) server providing comprehensive Google Maps API integration with LLM processing capabilities.

Turn your Claude Pro/Max subscription into an OpenAI-compatible API for your IDEs and devices — LAN auth, per-key quotas, response cache, disciplined cli.js ali…

Paw Work - selection-first web agent for Chrome: select on the live page, describe the outcome, take away an editable office file. BYOK, sandboxed, no server.

基于 AI Agent + MCP 工具链 + 渗透 Skill 编排， 配合大语言模型， 自然语言输入 → 自动完成「信息收集 → 漏洞发现 → 漏洞利用 → 报告生成」全流程。

Lexora — Personal AI workspace built around Desktop / 以 Desktop 为核心的个人 AI 工作台

First AI Journey for DevOps - with comprehensive learning paths, practical tips, and enterprise guidelines

AI coding agent with one Python core and three front-ends — headless CLI, Textual TUI, and an Electron desktop. Works with any OpenAI-compatible API, with risk-…