LLM Mart Basic

Derive a full UI colour palette algorithmically from one or two brand colours. Darker and lighter variants for interactive states, desaturated greys from the brand hue for borders and backgrounds, and semantic colours that feel coherent with the brand rather than generic. Use whe

The persistent shell around an application — the top bar, the app launcher, the tenant and environment cue, and in heavy tools a status bar. In an estate of several applications the shell belongs to the estate rather than to any one app, and it is what carries a user between tool

Product visuals — hero shots, demos, screenshots, landing-page panels — must reproduce the real product, not a stylised poster of it. Design with real content and real data, mirror the actual output the product generates, keep every label and number truthful, and refuse fabricate

A brand's visual tone — playful or serious, rounded or angular — should be consistent across all UI elements. Shape language in typography, border-radius, and iconography communicates personality before a single word is read. Use when establishing a design system, choosing icon l

Every interactive element needs a complete set of visual states — rest, hover, active/pressed, focus, disabled, and loading. States should be derived algorithmically from the base colour, not chosen arbitrarily. Use when designing buttons, links, inputs, or any clickable componen

Choose light, dark, or combined color mode deliberately based on brand tone and user context. Offer a theme selector only when user control genuinely matters — enterprise tools, data-heavy UIs, or extended-use applications. Use when defining the base color palette, designing a de

Buttons, inputs, pills, badges, calendars, and other interactive components form a visual family — they share the same border-radius, colour logic, shadow scale, border style, and spacing rhythm. Inconsistency between them breaks the sense of a coherent product. Use when building

When data has both a tabular/list representation and a visual representation, show both simultaneously and keep them synchronized. Clicking a row highlights the corresponding element in the visual view, and vice versa. Applies to maps, diagrams, timelines, and charts that accompa

Complex data deserves multiple view modes — grid, list, table — chosen by the user based on their task. Row and item selection should use large hit areas (the whole row or card, not just a checkbox). Selected state is communicated through a subtle background colour shift. Mass ac

Orchestrator for the full dembrandt UX pipeline. Routes a UI/UX task through six ordered stages — brand foundation → design tokens → layout → components → UX polish → accessibility gate — loading the right sub-skill at each stage. Use when the task spans multiple design concerns:

Configuration UIs for domain experts — users who understand their field deeply but are not software developers — require domain language, sensible defaults, and grouping by professional concept rather than technical parameter. Use when designing settings panels, solver or algorit

Elevation — subtle shadows and layering — communicates visual hierarchy by lifting elements above the surface. Combined with border-radius, it creates the tactile quality of cards, modals, and interactive surfaces. Use when designing cards, dropdowns, modals, tooltips, or any flo

Extract a complete design system — colors, typography, spacing, components, shadows, and W3C design tokens — from any live website using Dembrandt. Runs a headless browser against the URL and returns real computed values from the DOM. Use when you need a site's actual design toke

Forms have three layers of guidance: helper text below the input explains what to enter, placeholder shows the expected format, and validation confirms correctness. Real-time validation for complex inputs. Submit enables only when the form is valid. Use when designing or reviewin

Pipeline skill — turns a URL or DESIGN.md into a concrete UI structure with decisions already made. Extracts live design tokens, normalizes them into a semantic system, applies UX principles, and outputs an actionable UI spec. Use when building UI for an existing brand from scrat

UI layout and grouping should follow Gestalt principles so users immediately understand which controls, commands, and elements belong together. Use when designing or reviewing component layout, navigation, toolbars, forms, dashboards, or any UI where visual grouping communicates

Quick global settings — currency, language, region, units — belong in a persistent, low-profile location such as a header toolbar or footer. These controls are frequent but not primary, so they use small typography and stay out of the main content hierarchy. Use when designing gl

In large applications, information architecture determines whether users can find, understand, and act on data. Naming matters. The UI should mirror the data model and signal how data can be transformed. Dangerous or irreversible changes always require a confirm dialog. Use when

A layout is not a neutral container — choosing the right layout paradigm (feed, board, table, canvas, master-detail, dashboard, gallery, timeline, map, single-focus, narrative long-scroll) is a design decision that shapes how content is understood. Landing and marketing pages get

Manage user expectations during wait times with appropriate loading states — from simple spinners to complex skeleton screens and staggered animations. Perceived performance is often more important than actual load time. Use when designing data-heavy components, handling API call

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.

"Tiered plugin quality review: branch (quick gates),

Check GitHub Discussions for highly voted learnings and promote them to Issues.

Evaluate Claude Code rules in .claude/rules/ directories for quality

Audit skill quality, frontmatter compliance, token efficiency, and activation reliability. Recommends improvements.

Test Claude Code skills using RED/GREEN/REFACTOR TDD phases in fresh subagents to prevent priming bias.

Validate hooks for security, performance, and SDK compliance

Validate plugin structure, schema, and naming. Use for plugin creation, debugging, or verification.

Initialize projects with architecture-aware templates using paradigm research and selection guidance for the target domain.

Generate an implementation plan with system architecture design and dependency-ordered task breakdown from a specification.

Guide project ideation through Socratic questioning to generate briefs with validated approaches and decision rationale.

Execute implementation plan systematically with progress tracking and checkpoint validation

Run full attune lifecycle as a mission with state detection and phase routing

Initialize a new project with git setup, CI/CD workflows, pre-commit hooks, Makefiles, and language-specific tooling.

Build a project skill library under .claude/skills/ as a resumable mission: discover, author in parallel, review adversarially.

Create specs from project briefs with acceptance criteria and testable requirements

Update existing project configurations to current best practices with selective component upgrades

Validate project structure and configurations against best practices with detailed issue reporting

Convene a multi-LLM expert panel to pressure-test strategic decisions with adversarial review and reversibility assessment.

Generate visual diagrams of codebase structure using Mermaid Chart MCP rendering.

Audit codebase for AI-generated code quality issues (vibe coding, Tab bloat, slop)

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-…