LLM Mart Basic
@llm-mart · Joined Jun 2026
Manage MaxCompute CU package governance, DataWorks scheduling, Quick BI reporting, and PAI ML platform. Optimize query cost and job scheduling efficiency for big data workloads.
Plan Alibaba Cloud migrations using SMC (Server Migration Center), DTS (Data Transmission Service) for data sync, OSSImport for object storage migration, and design cutover sequencing with rollback paths.
Configure and operate Alibaba MSE (Microservice Engine) — Nacos service discovery and configuration management, Sentinel rate limiting and circuit breaking, Seata distributed transactions, and ARMS APM for microservices observability.
Design Alibaba Cloud network topology — VPC peering, CEN for multi-VPC/multi-region connectivity, Express Connect for private circuits, SLB/ALB/NLB/CLB load balancer selection, and Smart Access Gateway for branch offices.
Respond to Alibaba Cloud incidents using CloudMonitor alarms, SLS log analytics, ARMS APM distributed tracing, and alert governance for ECS, RDS, ACK, and network services.
Govern Alibaba Cloud OSS data perimeters — bucket ACL and policy conflict resolution, Block Public Access configuration, cross-account access via RAM role, VPC endpoint binding for private access, WORM (Object Lock), and MLPS 2.0 data residency compliance.
Manage OSS lifecycle policies, bucket policy and ACL governance, NAS/CPFS shared file storage, cross-region replication, and access control hardening for Alibaba Cloud object and file storage.
Operate PolarDB (MySQL/PG/Oracle) clusters and RDS instances — DAS diagnostics, database proxy, Global Database Network, backup strategy, and performance tuning.
Audit Alibaba Cloud RAM users, groups, roles, and policies; review STS token lifecycle and scope; assess Resource Directory permission boundaries; review Control Policy statements for org-wide gaps or over-privilege.
Govern Alibaba Cloud Container Registry (ACR) — Enterprise Edition vs Personal Edition selection, image vulnerability scanning, namespace IAM least privilege, image retention policies, cross-region replication, and supply chain security posture.
Review Alibaba Cloud workload HA and BCDR designs — RDS High-Availability Edition failover, PolarDB Global Database Network, ACK multi-zone, ECS disaster recovery cross-region, RTO/RPO target analysis, and HBR (Hybrid Backup Recovery) coverage.
Harden Alibaba Cloud security posture via Security Center (threat detection, vulnerability scanning, baseline checks), WAF, Anti-DDoS Pro, Cloud Firewall, and Network Traffic Analysis (NTA).
Review Function Compute 3.0 (FC3), SAE (Serverless App Engine), and EDAS for production readiness — cold start optimization, VPC binding, RAM role injection, ARMS distributed tracing, security group rules, concurrency limits, and SLA-readiness.
Design Alibaba Cloud solutions — product selection (PolarDB vs RDS, ACK vs ASK vs SAE, MaxCompute vs AnalyticDB), architecture patterns, landing zone design, and disaster recovery strategies aligned to the Alibaba Well-Architected Framework.
Coordinate Alibaba Cloud support incidents — case creation with correct severity (紧急/高/中/低), Enterprise Support SLA enforcement, account manager escalation path, status page monitoring for CN-* and international, internal stakeholder communication, and post-incident evidence pack
Triage Alibaba Cloud operational alerts, incidents, and support tickets — P0/P1/P2/P3 classification, Alibaba Cloud Support SLA enforcement, account manager escalation, DingTalk war room coordination, evidence collection from CloudMonitor and SLS, and safe escalation paths.
Assess Alibaba Cloud cost posture: ECS instance family rightsizing, Savings Plans and Reserved Instance coverage, Preemptible Instance adoption, cost allocation tagging, OSS storage tiering, analytics pricing, and idle resource elimination.
Assess Alibaba Cloud workload reliability: multi-AZ ECS topology, SLB/ALB/NLB load balancing, Auto Scaling health policies, RDS/PolarDB HA failover, backup and cross-region DR, and Cloud Monitor/ARMS observability coverage.
Assess Alibaba Cloud workload security posture: RAM least-privilege, VPC isolation, KMS/HSM encryption, Cloud Security Center threat detection, ActionTrail audit, WAF/Anti-DDoS web protection, and Chinese regulatory compliance (MLPS 2.0, DSL, PIPL).
Use this skill when reviewing Argo Rollouts progressive delivery configuration. Trigger when the user asks about canary or blue-green Rollout strategy correctness, AnalysisTemplate success/failure conditions, traffic weighting provider alignment, canaryService isolation, PDB dead
Use MCP Inspector to connect to local or remote servers, inspect capabilities, call tools, read resources, test prompts, and diagnose failures before release.
Build an MCP server in TypeScript with focused tools, validated schemas, local and remote transports, Inspector tests, and production security controls.
An MCP server exposes tools, resources, or prompts through a standard protocol so an AI application can discover and use external capabilities.
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.
/device-inventory
Device inventory
Inventory devices for an Auvik tenant with type, manage status, and lifecycle breakdown
/network-audit
Network audit
Audit a tenant's networks, interfaces, and saved configurations; flag drift and missing backups
/tenant-overview
Tenant overview
Single-tenant Auvik snapshot - devices, alerts, networks, billing usage
/phishing-results
Phishing results
Phishing-simulation results and click-rate trend for a given window
/risk-report
Risk report
Human risk score report for one client or the whole portfolio, built from training completion and phishing-simulation performance
/training-status
Training status
Training completion snapshot for one client or the whole portfolio — completion rates, overdue users, and cadence status
/backup-health-check
Backup health check
Check backup health for one Axcient-protected device
/client-backup-overview
Client backup overview
Backup health overview across every device for one Axcient client
/azure-cost
Azure cost
Azure cost and pricing analysis for a subscription — Advisor cost recommendations, retail pricing lookups, and quota-driven right-sizing signals, scoped to one subscription
/azure-diagnostics
Azure diagnostics
Resource health and diagnostics triage for an Azure resource or subscription — Resource Health status, AppLens deep diagnostics, and Azure Monitor alert state
/backup-status
Backup status
Portfolio-wide backup job health snapshot - failure count, at-risk clients, and storage trends
/restore-check
Restore check
Restore-readiness check - has this actually been restore-tested, for one client or the whole portfolio
/retention-audit
Retention audit
Retention and RPO compliance audit against contracted requirements, for one client or the whole portfolio
/create-monitor
Create monitor
Create a new Better Stack uptime monitor
/incident-triage
Incident triage
Triage current Better Stack incidents
/monitor-status
Monitor status
Check all Better Stack monitor statuses and identify downtime
/search-logs
Search logs
Search logs via Better Stack Logtail
/status-page-update
Status page update
Update a Better Stack status page with current status or maintenance
/investigate-detection
Investigate detection
Investigate a single Blackpoint Cyber / CompassOne detection end-to-end
/partner-overview
Partner overview
Portfolio-level Blackpoint Cyber / CompassOne rollup of detections and exposure across all tenants
Make any song you can imagine
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