LLM Mart Basic

Analyzes Argo Workflows DAG templates to identify parallelization opportunities. Uses the Argo Server API to fetch workflow execution history and critical path analysis.

Constructs Kubernetes-native workflow DAGs using Argo Workflows CRDs with configurable retry strategies, artifact passing via S3/MinIO, and template composition through WorkflowTemplates and ClusterWorkflowTemplates.

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.

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.

Add remote HTTP or local stdio MCP servers to Claude Code, choose the right scope, protect credentials, verify the connection, and test with least privilege.

Skills teach Claude a repeatable method, connectors provide governed access to apps and live data, and plugins package related capabilities for installation and sharing.

Use an agent skill to package reusable know-how and workflow instructions. Use an MCP server when an agent needs live, governed access to external data or actions.

Custom commands and skills can both create a slash-invoked workflow in Claude Code. The important choice is how the workflow is discovered, shared, and permissioned.

A useful Claude skill solves one recurring engineering job, is easy to inspect, and saves more time than it creates in setup and review.

Claude skills can live in your Claude account, your local Claude Code setup, or a repository. Install them where the sessions that need them can load them.

Build a portable AI agent skill from one repeatable job: a precise description, concise instructions, focused resources, and tests that prove it works.

AI agent skills package instructions, scripts, references, and templates into portable folders an agent loads only when the task calls for them.

AI made publishing cheap, which is exactly the problem. What separates a page worth ranking from a competent summary of the first ten results.

A prompt that works once isn't a quality system. Five cases, an observable rubric, and a regression set will tell you whether a change helped.

One character of YAML, four pods that never started, and two safety nets I didn't know were holding. Every restart is an audit. Schedule them before they schedule you.

"Verify your work" isn't an instruction. It's a mood. Here's the version that's an instruction. Verify with a different mechanism than the one that made the claim.

A prompt that works once may still fail in production. A lightweight eval set gives you repeatable cases, a clear rubric, and a way to see whether a prompt change actually improved the workflow.

The best AI tool is not the one with the longest feature list. It is the one that solves a defined job reliably, fits the workflow, handles data appropriately, and remains useful after the novelty wears off.

Use AI to speed research without losing trust. Learn to find primary sources, verify claims, preserve uncertainty, and keep an auditable source trail.

Better prompts aren't magic wording. They're short briefs that hand the model a task, the context it can't infer, the limits, and a quality bar.

A green PR, a controller reporting success, and not one line of the new code running

Discover testnet↔mainnet subnet lineage from repo configs and open a PR for review (pass --dry-run to report only)

Triage raw inbox notes into reviewed repository destinations without deleting their sources.

Audit and rewrite content to remove AI writing patterns

Log a completed piece of content to content/log.md after the user confirms it was published.

Validate a dream artifact, review each proposal, and apply only individually accepted changes.

Run a curator pass against the validated memory directory and produce a proposal artifact.

End a session — log what happened, update state and the decision log, propose memory updates, and check for uncommitted or unpushed work

Find relevant context files by topic. Use when you need to load files for a topic without a slash command, or when a task spans multiple domains.

Inventory and migrate selected Gemini CLI workflows with dry-run review and parity checks.

Find repeated workflows in selected Gemini CLI sessions and draft portable skills after review.

Scan multi-session drift and offer individually reviewed fixes only after explicit approval.

Scan orphaned worktrees and stale branches, then offer explicit approval-gated cleanup.

Guided onboarding or import for durable workspace context

Start a session — load state files, flag staleness, and give a briefing on current priorities, deadlines, and blockers

Create a morning heartbeat from repository state and update the local heartbeat log.

Mid-session checkpoint — append progress to today's session log and update state files if a priority shifted, without ending the session

Maintainer-only. Find every file that would newly ship to adopters and decide, one file at a time, whether to ship it or withhold it. Drives the release CLI, which refuses to produce a manifest until every shipping file has an answer.

Audit memory, wiki, and auto-loaded files for duplication, conflicting instructions, and stale content. The default path researches, then asks you a single Apply / Discuss / Decline question; on Apply it applies the report, files any out-of-scope problem as a tech-debt issue, then commits, opens a PR, and merges it on a main-branch run like /update-deps. Pass --apply to re-run the apply-and-publish stage against the most recent report.

Fix the tech-debt backlog, a single issue or a recommended related batch, highest severity then oldest first, on a fresh isolated branch through the audit gate, closing the issue(s) on merge. Pass `list` to see the ordered backlog, `why <issue-number>` to explain the recommendation, or a bare `<issue-number>` to fix that issue directly.

Health-check and auto-heal this project's Claude integration, triage, heal, verify, and report an F-to-A+ grade.

Make any song you can imagine

Leading AI-powered video generation platform that specializes in creating hyper-realistic talking avatars

Hermes Agent is an open-source, self-improving autonomous AI agent developed by Nous Research

Kilo Code is a popular, open-source AI coding agent and "agentic engineering" platform designed to help developers build, refactor, and debug software faster

General-purpose agent in one static Go binary. ReAct loop, ACP server for IDEs, OpenAI-compatible REST API with embedded web UI, Telegram gateway, cron schedule…

Autonomous agent framework with structured memory, safety hooks, and loop management. Built by the agent that runs on it.

TSP自托管、零运维的 A 股「选股 + 监控 + 回测」量化工作台 | 基于 TickFlow 数据源 | LLM能力驱使策略定制+个股分析+复盘 | 自由接入第三方数据源与个性化扩展数据 | 个人开源 ,非TickFlow官方项目

Curated, verified Agent Skills powered by ModelStudio.

Run Claude Code, Codex, Antigravity, Cursor Agent and OpenCode as one runtime — persistent sessions, multi-agent councils, an OpenAI-compatible endpoint, an MCP…

pi had nothing (nothing), so I made something (something) — sorry mariozechner-senpai, I went ahead and lovingly soiled your pure pi for you. opinionated fork o…

A persistent workspace for development work that self-improves and continues beyond one session.

Open-source memory and context for user-aware agents: scoped memory, provenance, retrieval quality, correction, boundaries, evals, and MCP/HTTP access.

📚 A zero-dependency, git-backed micro-lesson library for AI Agents to asynchronously share and search verified debugging experience. Python stdlib only. | http…

Deterministic, local-first memory and guardrails for AI coding agents with no LLM in the hot path.

Deterministic spec-orchestration for local LLMs in the pi coding agent — drives prompts through refine→research→grill→compose→critique, with bundled web/docs/fe…

Native Safari browser automation for AI agents. 97 tools via AppleScript — zero overhead, keeps logins, runs silently in background. Drop-in alternative to Chro…

Agent OS: keep specialist agents in a hub, spin up a temporary orchestrator per task. Local-first, works with any model.

Git for agent memory. Branches, diffs, PRs, and rollback for what your agents know.

Multi-Provider AI Gateway - No personal logs by design. Model autodiscovery, Failover groups, High availability, Android companion app, and more - "Because we h…

Production-grade MCP server for MikroTik RouterOS with secure AI-native network automation.