LLM Mart Basic

Imported from agentskillexchange/skills/skills/argocd-mcp-server.

Monitors ArgoCD applications for configuration drift using the ArgoCD REST API and grpc-gateway. Compares live Kubernetes manifests against Git-declared state and generates remediation playbooks via kubectl diff.

Manages ArgoCD application syncs via the ArgoCD REST API /api/v1/applications/{name}/sync endpoint. Monitors sync status, handles rollback operations, and validates Kubernetes manifest health using argocd CLI diff commands.

Manages ArgoCD application syncs using the argocd CLI and the Argo CD REST API (v1alpha1). Supports progressive delivery with Argo Rollouts integration and automated health checks via Kubernetes readiness probes.

Monitors ArgoCD application sync status via the ArgoCD REST API and gRPC gateway. Detects drift between desired and live Kubernetes manifests and triggers Slack notifications through the Slack Bolt SDK.

Diagnoses ArgoCD application sync failures using the ArgoCD REST API and Kubernetes resource diff analysis. Identifies Helm value conflicts, Kustomize overlay errors, and resource health check failures.

Manages ArgoCD application sync waves and hooks using the ArgoCD API and argocd CLI. Coordinates multi-application deployment ordering with sync-wave annotations, health checks, and progressive rollout gates.

Manages ArgoCD Application sync waves and hooks through the ArgoCD REST API and Kubernetes custom resources. Uses kubectl diff and Helm template rendering to validate manifests before triggering progressive rollouts via Argo Rollouts.

Query Chinese A-share, ETF, index, financial statement, valuation, capital-flow, and technical-indicator data through the AShareHub Python SDK and hosted API. Use this skill when an agent needs structured China market data as pandas DataFrames.

Use apko to build small OCI images from declarative package manifests when supply-chain clarity and minimal contents matter more than a conventional Dockerfile flow.

Use DeepAgents to build long-running task agents with a batteries-included harness for planning, tools, and workflow structure.

Extract structured intelligence from audio using the AssemblyAI API with sentiment analysis, entity detection, topic modeling, and auto-chapter generation. Uses the assemblyai Python SDK for transcript processing pipelines.

Summarizes audio content using AssemblyAI's LeMUR (Large Language Model for Audio Understanding) API. Chains the /v2/transcript endpoint with /lemur/v3/generate/summary for contextual audio intelligence.

Streams audio from Twilio Media Streams over WebSocket to AssemblyAI real-time transcription, extracting speaker-diarized transcripts with word-level timestamps. Triggers entity detection and sentiment analysis via AssemblyAI LeMUR on completed call segments. Results are pushed t

Transcribes audio and generates auto-chapters with summaries using AssemblyAI's /v2/transcript endpoint with auto_chapters=true. Extracts key topics, sentiment analysis, and content safety labels via AssemblyAI SDK.

Use ast-grep (sg) to search, lint, and rewrite code across large codebases using AST pattern matching. A blazing-fast alternative to regex-based code transformations that understands syntax structure.

Astro is a modern web framework for building content-driven websites. It ships zero JavaScript by default, supports multiple UI frameworks (React, Vue, Svelte, Solid), and provides islands architecture for optimal performance.

Generates event-driven architecture documentation from AsyncAPI 3.0 specifications. Uses the AsyncAPI parser-js library to extract channels, message schemas, and server bindings for Kafka and RabbitMQ.

Parses AsyncAPI 2.x/3.x specifications to generate event-driven architecture catalogs using the AsyncAPI Generator. Produces channel documentation, message schema validators, and EventBridge rule templates.

mcp-atlassian is a Model Context Protocol server that connects AI assistants to Atlassian Jira and Confluence. It enables searching and managing Jira issues, reading and editing Confluence pages, and performing project management tasks through natural language via any MCP-compati

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.

Implement GraphQL API endpoints

Initialize new project with essential structure

Build reference documentation by creating markdown files and updating CLAUDE.md

Convert GitHub issues to Linear tasks

Triage and prioritize issues effectively

Convert Linear tasks to GitHub issues

READ the llms.txt file from https://raw.githubusercontent.com/ethpandaops/xatu-data/refs/heads/master/llms.txt via `curl`. Do nothing else and await further instructions.

Log work from orchestrated tasks to external project management tools like Linear, Obsidian, Jira, or GitHub Issues.

Model customer and market responses with segment analysis, behavioral prediction, and response optimization.

Clean and organize project memory

Create entity relationship diagrams using Mermaid from SQL/database files

Migrate JavaScript project to TypeScript

Assist with system migration planning

Create migration guides for updates

Track and monitor project milestone progress

Update and modernize project dependencies

Move tasks between status folders following the task management protocol.

Optimize build processes and speed

Reduce and optimize bundle sizes

Optimize database queries and performance

Offline-first Python AI agent that runs a tiny research business: quotes each job against its own costs, collects via Stripe, fulfils with NVIDIA Nemotron, pays…

DSH 插件 · 注入式优化器 0.8（主线）：你照常说话，它在你发送后,AI接收前把"这一轮到底要什么"理清楚，再把这份理解交给工作 AI(上下文注入) —— 原话不改写，条条带逐字依据。含控制界面（档位/权限/模型/上下文/只读工具）、拦截浮层（思维层+产出层）与真实 token 用量。可明显提升大多数模型的发挥稳…

Reliable AI Skill + MCP toolkit for agent-driven desktop CAD automation.

Curated real-world use cases for Hermes Agent — the self-improving AI agent from Nous Research. Backed by primary sources.

AI Agent 教学仓库 | 系统化 LangChain、RAG、LangGraph、MCP 全栈实战代码 | 万字博客详解 | 开源可运行示例 | 从零构建智能体

从 0 复刻 WorkBuddy-style 桌面 AI 助手 Harness：24 章 Python 教程，覆盖 Agent Loop、工具调用、记忆系统、Sidecar、沙盒审计、DeepSeek/OpenAI 评测轨迹

MCP server and CLI tools for web search and crawling, built on SearXNG and Crawl4AI

Delta MCP is a free app that sits between your AI apps and their MCP servers: one program per task instead of one tool call per step, up to 24.1× fewer tokens i…

Ava turns any Android 5+ device into a voice-first Home Assistant kiosk. Native C++ under the hood, so a 10-year-old tablet still listens, talks, and runs the h…

Roblox Studio macOS Window Capture Fix 2026: Real Screenshot Tool Instead of Magenta Playtest Glitch

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