LLM Mart Basic

Use this skill for Argo CD GitOps review across Application, AppProject, ApplicationSet, sync windows, RBAC, sync impersonation, and Argo CD Agent multi-cluster topologies. Trigger when the user asks whether an Argo CD configuration is safe for production, whether automated sync

Build, test, migrate, integrate, and deploy Amazon Bedrock AgentCore agents. Use for AgentCore runtime, local development, import/migration, deployment, Memory, Gateway/MCP tools, Identity, Observability, Browser, Code Interpreter, Evaluations, Registry, Payments, policy, and har

Review AWS API and edge delivery posture across API Gateway, CloudFront, AWS WAF, Shield, ALB, custom domains, TLS policies, authentication, authorization, throttling, quotas, caching, origin protection, logging, and abuse controls. Use when public APIs, web entry points, or edge

Review Amazon Bedrock agents, AgentCore, Guardrails, knowledge bases, action groups, memory, MCP/tool integrations, prompt-injection and prompt-leakage defenses, PII handling, encryption, logging, observability, and least-privilege IAM. Use for AWS-native GenAI and agent security

Assess AWS change impact using change sets, deployment blast radius, rollback readiness, dependency mapping, risk, go/no-go context, approval context, and stakeholder communication. Prefer this for non-destructive pre-change advisory work; prefer IaC or platform-specific skills f

Review AWS CI/CD and release safety across CodePipeline, CodeBuild, CodeDeploy, GitHub Actions, GitLab, artifact provenance, deployment gates, approvals, tests, progressive delivery, rollback, change correlation, and incident-prevention recommendations. Use when AWS releases or p

Map AWS compliance evidence for audits across Security Hub controls, AWS Config rules/conformance packs, Audit Manager assessments, evidence folders, manual evidence, AWS Artifact reports, CloudTrail, and control narratives. Use for evidence packaging and audit readiness, not gen

Review AWS cost anomalies using Cost Explorer, Cost Anomaly Detection, Budgets, usage spikes, commitments, and tagging gaps. Prefer this for proactive FinOps watch and non-destructive escalation; prefer aws-cost-optimization-governor for broader optimization strategy.

Review AWS cost optimization and FinOps posture across Cost Explorer, Budgets, Cost Optimization Hub, Compute Optimizer, Savings Plans, Reserved Instances, tagging, showback, idle resources, rightsizing, storage, data transfer, and forecast risk. Use when the user asks to reduce

Prepare AWS daily operations briefings using CloudWatch, Personal Health Dashboard, Trusted Advisor, cost signals, deployment timelines, incidents, risks, and action backlog. Prefer this for non-destructive business and engineering status coordination; prefer observability, cost,

Review AWS backup and data protection implementation across AWS Backup, EBS/RDS/EFS/S3 recovery patterns, vaults, vault lock, retention, encryption, cross-account/cross-Region copy, restore testing, lifecycle, and recovery evidence. Prefer resilience BCDR review for broader RTO/R

Patch AWS deployment hotfix config, release parameters, manifest mistakes, environment drift, rollback blockers, and rollout blockers in-repo. Use for rapid non-destructive deployment corrections; do not use for live deploy/apply/destroy actions.

Design, review, and improve AWS DevOps Agent-compatible skills, investigation workflows, learned skills, tool-use best practices, agent type targeting, frontmatter descriptions, reference materials, and operational output contracts. Use when creating or adapting skills for AWS De

Review Amazon DynamoDB data modeling and performance across access patterns, partition keys, sort keys, secondary indexes, GSI/LSI design, hot partitions, query versus scan behavior, capacity mode, adaptive capacity, global tables, TTL, DAX, item size, transactions, and cost. Use

Review Amazon EC2 compute operations across instances, Auto Scaling groups, Launch Templates, AMIs, Systems Manager, Patch Manager, Session Manager, EBS volumes, snapshots, health checks, instance refresh, lifecycle hooks, patch compliance, and fleet reliability. Use for EC2 day-

Review Amazon ECS and Fargate platform operations across services, task definitions, task roles, execution roles, capacity providers, load balancers, deployment circuit breakers, blue/green, autoscaling, health checks, logs, secrets, networking, and rollback. Use only for ECS/Far

Correct AWS ECS and Fargate service definitions, task definition config, deployment parameters, health checks, environment settings, and rollout wiring in-repo. Use for non-destructive repo fixes only; do not force deployments or mutate live services from this role.

Review Amazon EKS Kubernetes platform operations across cluster access, IRSA, IAM roles for service accounts, pod identity, node groups, Karpenter, autoscaling, CNI/network policy, upgrades, reliability, observability, and cost. Use only for EKS/Kubernetes; prefer ECS/Fargate ope

Review AWS event-driven system design across EventBridge, event buses, Pipes, SQS, SNS, Step Functions, event schemas, filtering, cross-account routing, retries, DLQs, replay, idempotency, monitoring, and event-loop risk. Prefer serverless production readiness for Lambda runtime/

Build Amazon Bedrock and serverless generative AI applications using Lambda, API Gateway, Step Functions, EventBridge, S3, DynamoDB, SQS, Guardrails, and IAM. Prefer this for serverless GenAI app design and implementation; prefer aws-agentcore for AgentCore runtime, aws-bedrock-a

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.

Create new Svelte components with best practices, proper structure, and optional TypeScript support.

Help debug Svelte and SvelteKit issues by analyzing error messages, stack traces, and common problems.

Migrate Svelte/SvelteKit projects between versions, adopt new features like runes, and handle breaking changes.

Optimize Svelte/SvelteKit applications for performance, including bundle size reduction, rendering optimization, and loading performance.

Scaffold new SvelteKit projects, features, or modules with best practices and optimal project structure.

Migrate Storybook configurations and stories to newer versions, including Svelte CSF v5 and @storybook/sveltekit framework.

Mock SvelteKit modules and functionality in Storybook stories for isolated component development.

Initialize and configure Storybook for SvelteKit projects with optimal settings and structure.

Create comprehensive Storybook stories for Svelte components using modern patterns and best practices.

Diagnose and fix common Storybook issues in SvelteKit projects, including build errors, module problems, and configuration issues.

General-purpose Storybook assistance for SvelteKit projects, including setup guidance, best practices, and common tasks.

Analyze test coverage, identify testing gaps, and provide recommendations for improving test coverage in Svelte/SvelteKit projects.

Troubleshoot and fix failing tests in Svelte/SvelteKit projects, including debugging test issues and resolving common testing problems.

Set up comprehensive testing infrastructure for Svelte/SvelteKit projects, including unit testing, component testing, and E2E testing frameworks.

Create comprehensive tests for Svelte components and SvelteKit routes, including unit tests, component tests, and E2E tests.

Setup automated synchronization workflows

Resolve synchronization conflicts automatically

Sync GitHub issues to Linear workspace

Sync Linear tasks to GitHub issues

Link pull requests to Linear tasks

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.