LLM Mart Basic
@llm-mart · Joined Jun 2026
Orchestrates deployment pipelines using the Argo Workflows Engine API and Argo CD ApplicationSet controller. Implements progressive delivery with Argo Rollouts canary and blue-green strategies.
Lints and validates Argo Workflows templates using the argo CLI and Argo Server REST API. Detects DAG dependency cycles, invalid artifact references, and parameter type mismatches across workflow steps.
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.
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.
Use MCP Inspector to connect to local or remote servers, inspect capabilities, call tools, read resources, test prompts, and diagnose failures before release.
/sonar
sonar
SonarQube 정적분석 실행 및 결과 조회. 코드 품질·보안 핫스팟·커버리지 확인 시 사용.
/fix-issue
fix-issue
GitHub 이슈 #$ARGUMENTS 를 처리한다(이슈 우선 워크플로):
/sdlc-cycle
sdlc-cycle
이슈/기획서 기준 SDLC 한 사이클(이슈→개발→테스트→검증→PR)을 사람 개입 없이 자동 실행.
/fix-issue
fix-issue
GitLab 이슈 #$ARGUMENTS 를 처리한다(이슈 우선 워크플로):
/sdlc-cycle
sdlc-cycle
이슈/기획서 기준 SDLC 한 사이클(이슈→개발→테스트→검증→MR)을 사람 개입 없이 자동 실행.
/README
README
Invoke a repeated task with `/name`. File name = command name (`fix-issue.md` → `/fix-issue`).
/fix-issue
fix-issue
Handle issue #$ARGUMENTS (issue-first workflow):
/knowledge-graph
Knowledge graph
Renders the connection structure of the AGENTS.md ecosystem
/sdlc-cycle
sdlc-cycle
Automatically runs one SDLC cycle (issue → development → testing → verification → PR/MR) based on an issue or spec, without human intervention.
/sonar
sonar
Run SonarQube static analysis and check the results. Use to check code quality, security hotspots, or coverage.
/fix-issue
fix-issue
Handle GitHub issue #$ARGUMENTS (issue-first workflow):
/sdlc-cycle
sdlc-cycle
Automatically runs one SDLC cycle (issue → development → testing → verification → PR) based on an issue or spec, without human intervention.
/fix-issue
fix-issue
Handle GitLab issue #$ARGUMENTS (issue-first workflow):
/sdlc-cycle
sdlc-cycle
Automatically runs one SDLC cycle (issue → development → testing → verification → MR) based on an issue or spec, without human intervention.
/plan-status
Plan status
Show Hermes planning-with-files status for the current project.
/plan
Plan
Start Hermes planning-with-files workflow in the current project.
/plan-ar
Plan ar
بدء تخطيط الملفات بنمط Manus. إنشاء task_plan.md و findings.md و progress.md للمهام المعقدة.
/plan-attest
Plan attest
Lock the current task_plan.md content with a SHA-256 attestation. Hooks then refuse to inject plan content if the file diverges from the attested hash, blocking silent tampering. Use --show to print the stored hash, --clear to remove the attestation. Available since v2.37.0.
/plan-de
Plan de
Starte Manus-artige Dateiplanung. Erstelle task_plan.md, findings.md, progress.md für komplexe Aufgaben.
/plan-doctor
Plan doctor
Self-check for the planning-with-files mechanisms that fail silently: plan resolution, hook injection, canonicalizer path shape, attestation state, install surfaces, and per-fire hook latency. Run it whenever hooks seem quiet or after installing on a new machine. Available since v3.6.0.
Ultra-lightweight, open-source, self-hosted personal AI agent framework in Python with WebUI, tools, memory, MCP, multi-agent workflows, automation, and chat ap…
29 views 0 likesGovernance framework for AI coding agents. It runs them through a five-step workflow (plan, build, review, test, ship) where no step counts as done without evid…
17 views 0 likesUltimate Multi-Agent OS for Autonomous AI NPCs 2026
15 views 0 likesPersonal AI Agent Hub 2026 — Build Your 24/7 Autonomous Assistant
26 views 0 likesProven 2026 Multi-Agent AI Review System – Verdict-Driven Quality Control
29 views 0 likesSlash API Batch: Cut AI Costs by 50% in 2026
16 views 0 likesWeb dashboard for Hermes Agent — multi-platform AI chat, session management, scheduled jobs, usage analytics
19 views 0 likesAgent Skills for Solopreneurs
31 views 0 likesAirLLM dramatically reduces inference memory usage, letting 70B large language models run on a single 4GB GPU card
121 views 0 likesZero, your trustworthy AI teammate for real work.
16 views 0 likes一套 DSH runtime,Desktop、Web 与 TUI 三种开发体验。
12 views 0 likesOpen-source operational advisor for ClickHouse — real-time monitoring plus AI-driven index/partition/materialized-view recommendations.
17 views 0 likes⚙️ TypeScript Style Guide and Agent Skill. A concise set of conventions and best practices for consistent, maintainable code.
28 views 0 likesFramework for AI agents to build and maintain a digital brain through Obsidian wiki
17 views 0 likesApache Maka (Incubating) is a local-first AI agent workspace. Model messages, tool calls, tool results, permission decisions, and termination events are recorde…
25 views 0 likesNeo.mjs is a self-evolving software organism: a professional end-to-end AI engineering team whose cross-model swarm inhabits live apps via Neural Link, Active H…
25 views 0 likesAgentic development harness for Claude Code — SPEC-driven plan/run/sync, TRUST 5 quality gates, model+effort routing, and Claude×GLM multi-LLM cost control. Sin…
19 views 0 likesNocoBase is an open-source AI + no-code platform for building business systems fast. Instead of generating everything from scratch, AI works on top of productio…
27 views 0 likesAn open-source AI coding agent that lives in your terminal.
29 views 0 likesPawWork — free, open-source desktop AI agent for macOS and Windows. Alternative to Codex App and Claude Cowork. BYOK with 75+ providers, ChatGPT OAuth, local mo…
15 views 0 likes