LLM Mart Basic

Manages ArgoCD application deployments via the ArgoCD REST API and argocd CLI. Configures GitOps sync policies, automated rollbacks, and multi-cluster application sets with generator templates.

Diagnoses ArgoCD application sync failures and degraded states using the ArgoCD REST API and argocd CLI. Queries /api/v1/applications/{name} for sync status, resource health, and operation state. Provides automated remediation steps for OutOfSync, Degraded, and Missing resource c

Manages ArgoCD application synchronization using the ArgoCD REST API and argocd CLI. Handles sync waves, hooks, and health assessments for GitOps-driven Kubernetes deployments.

Monitors ArgoCD application sync status via the ArgoCD REST API and argocd CLI. Detects OutOfSync conditions, tracks sync wave progress, and alerts on failed sync operations with detailed resource diff analysis using argocd app diff.

Monitors ArgoCD application deployments using the ArgoCD REST API and gRPC interface. Tracks sync status, health checks, and rollback history across Kubernetes namespaces.

Manages GitOps deployments using ArgoCD API, argocd CLI, and Kustomize overlays. Automates sync operations, rollback procedures, and application health monitoring.

Manages GitOps deployments via the ArgoCD REST API and argocd CLI. Triggers application syncs through /api/v1/applications/{name}/sync, monitors health status via /api/v1/applications/{name}, and manages rollbacks using /api/v1/applications/{name}/rollback for Kubernetes workload

Automates ArgoCD application synchronization using the ArgoCD gRPC/REST API and argocd-autopilot CLI. Manages ApplicationSets, sync waves, and health assessments for Kubernetes deployments.

Manages ArgoCD Application and ApplicationSet resources for Kubernetes GitOps deployments. Uses the ArgoCD REST API and argocd CLI to automate sync waves, health checks, and progressive rollout configurations.

Manages ArgoCD application sync operations with intelligent drift detection and rollback strategies. Uses the ArgoCD gRPC API and ApplicationSet CRD for multi-cluster GitOps deployments.

Monitors ArgoCD application sync status using the ArgoCD REST API /api/v1/applications endpoint. Detects drift between Git manifests and live Kubernetes cluster state via the Kubernetes API.

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.

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 ranked improvement ideas by scanning the codebase, divergent ideation, adversarial critique, and impact ranking

Full autonomous engineering workflow (plan, build, review, ship)

Transform feature descriptions into well-structured project plans following conventions

Report a bug in the whetstone plugin

Reproduce a GitHub issue bug with visual evidence (browser screenshots, log analysis). Takes a GitHub issue number. For non-issue bug validation, use the bug-reproduction-validator agent.

Resolve PR review comments with cluster analysis and parallel agents. Use when bulk-fixing PR comments after triage.

Perform exhaustive code reviews using multi-agent analysis, ultra-thinking, and worktrees

Diagnose the whetstone environment and configure review agents. Checks CLI dependencies and plugin version, then runs the review-agent wizard that writes whetstone.local.md. Use when onboarding a project, troubleshooting missing tools, or configuring review agents.

Run browser tests on pages affected by current PR or branch

Run pre-PR verification chain: build, types, lint, tests, security scan, diff review

Execute work plans efficiently while maintaining quality and finishing features

Run a dry run first:

Run:

Run:

Create or update an OpenCode skill using the bundled skill-creator workflow

Rebuild the OpenCode skill registry for the current project and installed skills

Session-2 fix loop for Agentation — read structured annotations from the dev overlay and apply targeted UI fixes.

Consume the project's design contract — a .design file or DESIGN.md — and thread its tokens through UI code (CSS, Tailwind, or design-system components).

Fork pov.md for installer taste, or append a one-liner to gotchas.md after a real agent failure.

Audit animation timing, easing, springs, and transitions — decide first whether motion should exist, then apply the motion cluster.

Open-source MCP servers for Latin American commerce — Pix, NF-e, banking, fiscal, logistics, and messaging across Brazil, Mexico, Argentina, Colombia, Chile, an…

pi coding agent in a technicolor web trenchcoat

Open-source AI Search Intelligence Platform — track, analyze, and improve AI visibility, citations, prompts, competitors, and content opportunities across ChatG…

Open-source toolkit for the QVeris capability routing network: CLI, MCP server, Python SDK, skills, and REST API docs for agents to discover, inspect, call, and…

⚡ The Complete X/Twitter Automation Toolkit — Scrapers, MCP server for AI agents (Claude/GPT), CLI, browser scripts. No API fees. Open source. Unfollow people w…

The AI agent that interacts with you in the real world.

Offline Codex Desktop migration for Windows and macOS.

LLM 驱动的多市场股票智能分析系统：多源行情、实时新闻、决策看板与自动推送，支持零成本定时运行。 LLM-powered multi-market stock analysis system with multi-source market data, real-time news, decision dashbo…

Your smart, reliable, and friendly personal AI assistant.

The LLM Anti-Framework

A general-purpose AIGC video engine: script to finished film in one pipeline — dramas, ads, product videos, otome games, and more. | 通用 AIGC 视频引擎 —— 从剧本到成片一条流水线…

GTM agent for technical founders. Pay-per-result. Signed receipts. Two surfaces: terminal CLI + local web dashboard.

Desktop automation MCP server — computer use for any AI agent: control screen, windows, mouse/keyboard, and Chrome via Model Context Protocol (stdio)

DeepSeek Harness (dsh) Windows desktop client - bundled Node.js + dsh CLI, one-click launch

Open-source, real-time collaborative AI canvas - notes, mini-apps, and agents on one infinite board.

MCPSafari: Native Safari MCP Server for AI Agents

197 bioinformatics & life science skills for Claude Code and AI agents — BixBench 92.0% accuracy. RNA-seq, single-cell, drug discovery, proteomics, and more. Po…

The AI agent with a wallet — spends USDC autonomously to get real work done. Apache-2.0, TypeScript.

The fastest browser for AI agents to run browser automation, built for sharing your logged-in browser state with your AI agents, like Codex or Claude Code, with…

Ouroboros — self-creating AI agent. Born Feb 16, 2026.