LLM Mart Basic

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

Review AWS infrastructure-as-code changes across CDK, CloudFormation, SAM, Terraform, Serverless Framework, generated templates, plans, stack updates, change sets, and drift. Use when the user asks whether an AWS IaC deployment is safe, what a change set will do, why a resource r

Edit AWS IaC files including CloudFormation, SAM, CDK config, and Terraform to patch defects, prepare change set review, or unblock rollout work. Prefer this for bounded repo changes only; do not use for apply, deploy, or destructive infrastructure execution.

Review AWS IAM identity policies, trust policies, resource policies, permission boundaries, SCPs, session policies, role design, pass-role, federation, and Access Analyzer findings for least-privilege risk. Prefer KMS/secrets steward for key/secret lifecycle design and S3 perimet

Review AWS KMS and Secrets Manager lifecycle posture across key policies, grants, rotation, multi-Region keys, imported key material, aliases, secret rotation, replication, caching, endpoint conditions, recovery, and break-glass access. Prefer this for cryptography/secret lifecyc

Review and design AWS landing zones, AWS Control Tower environments, Organizations structures, OUs, account vending patterns, guardrails, central logging, security/audit accounts, and multi-account governance. Use when the user asks how to structure AWS accounts or govern a cloud

Operate guarded live AWS deployment changes with explicit account, region, profile, approval, dry-run, rollback, and verification gates. Use only when the target environment is confirmed and a live deployment action is intentionally requested.

Guard live Amazon ECS and Fargate rollout actions with ecs service, task definition, deployment circuit breaker, alarms, rollback, health check, and approval gates. Use only for intentional live ECS rollout actions against confirmed targets.

Guard live CloudFormation, SAM, CDK, and Terraform-backed AWS infrastructure changes with change set, drift, stack policy, rollback trigger, approval, and execute gates. Use only for intentional live IaC execution with confirmed targets.

Handle live CodePipeline approval and gated resume decisions with pipeline, stage, approver, SNS, approval, blast radius, and rollback checks. Use only when a real pipeline execution is paused or about to be approved.

Guard live Lambda and serverless release actions with lambda alias, codedeploy, canary, linear, alarms, rollback, and approval gates. Use only for intentional live serverless rollout actions against confirmed targets.

Route AWS tasks to the narrowest specialist or team of specialists from the 42-agent catalog. Use when you do not already know the specialist. Not for direct AWS answers; Maestro classifies, dispatches, and synthesizes only. Dispatches single agent for focused tasks, parallel tea

Plan, review, and de-risk AWS migrations and cutovers across discovery, dependency mapping, wave planning, AWS Application Migration Service, Migration Hub, test launches, acceptance tests, downtime windows, rollback, DNS, data consistency, and post-cutover validation. Use for mi

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.

Audit project dependencies for vulnerabilities, outdated packages, license conflicts, and supply chain risks — then provide actionable remediation strategies.

Refactor provided code for cleanliness, maintainability, and alignment with SOLID principles and modern best practices — no over-engineering.

Analyze and remediate technical debt — inventory debt items, score by impact, and produce a prioritized remediation plan with estimated effort.

Orchestrate comprehensive multi-dimensional code review using specialized review agents across architecture, security, performance, testing, and best practices

Enhance a pull request with a generated description, review checklist, risk assessment, and test coverage report

Execute tasks from a track's implementation plan following TDD workflow

Manage track lifecycle: archive, restore, delete, rename, and cleanup

Create a new track with specification and phased implementation plan

Git-aware undo by logical work unit (track, phase, or task)

Initialize project with Conductor artifacts (product definition, tech stack, workflow, style guides)

Display project status, active tracks, and next actions

Restore saved project context and decisions to resume a session

Save project context, decisions, and progress for a later session

Build features guided by data insights, A/B testing, and continuous measurement

Design and implement batch and streaming data pipelines with ingestion, orchestration, dbt transformations, data quality checks, and monitoring

Reduce cloud costs across AWS, Azure, and GCP through rightsizing, reserved and spot capacity, storage tuning, and cost monitoring

Migration monitoring, CDC, and observability infrastructure

SQL database migrations with zero-downtime strategies for PostgreSQL, MySQL, SQL Server

AI-assisted smart debugging — parse error messages, stack traces, and failure patterns to identify root causes and produce a fix with automated observability steps.

Audit project dependencies for vulnerabilities, outdated packages, license conflicts, and supply chain risks — then provide actionable remediation strategies.

The fastest way to put Volcengine Ark in your terminal and your AI agent — go from prompt to generated media, multimodal answer, or deployed endpoint in a sin…

本地私有、开源的自进化跨平台 AI 内容发现 Agent：先理解你，再主动从 B站、小红书、抖音、YouTube、X、知乎、Reddit、微博等平台与开放 Web 寻找内容。（支持 deepseek harness 插件） | Local-first open-source cross-platform AI cont…

Persistent memory for AI coding agents — one verified kb_search replaces the grep/find/ls orientation loop. Cross-repo, CPU-only, zero token spend.

AI 时代的伯克希尔：基于 Claude Code / Codex 的价值投资研究框架。巴菲特·芒格·段永平·李录四大师方法论 + 多Agent并行研究。| AI-era Berkshire: a value investing research framework built for Claude Code / Co…

The batteries-included, No-Code FinOps automation platform, with the AI you trust.

Open-source 3D AI agent framework — GLB/glTF avatars with LLM brains, memory, emotions, and autonomous payments. MCP server · x402 · Solana/EVM · Three.js. Embe…

XLSX parser for LLMs, RAG, LangChain, LangGraph, CrewAI, Claude, MCP — turns Excel (.xlsx) into citation-ready JSON with formulas, charts, dependency graphs, an…

Hermes-Relay — Your Hermes AI agent, in your pocket — chat, voice, and control.

A minimalist, terminal-native coding agent written in C.

AI-powered OSINT agent with interactive REPL, MCP server, and CLI. 19 tools. Works with Claude, GPT-4, or local models. For authorized security research only.

AI pair programming in your terminal — one static binary, sub-ms startup, any model

Where data access meets operational intelligence

Build your own security agents. Open-source framework for agents with live, read-only access to your infrastructure, with no path to widen it. Reasons across AW…

Multi-workspace terminal aggregator with Claude Code AI integration

Go implementation of AI coding agent

Harness engineering beginner tutorial, from 0 to 1

Generate images directly in DeepSeek Harness chats

A smarter, self-hosted AI assistant — multi-user, multi-agent.

Turn any research paper into a commercialization report — 6 AI agents, TRL/MRL scoring, patent landscape, market intelligence, verified citations. DeepSeek / Op…

Power BI CLI - semantic models (.NET TOM) and PBIR reports for token-efficient AI agent usage, built for Claude Code