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data-centre-operator/references/ai-skills.md
skillfactor-pipeline 102bea4920 feat: data-centre-operator skill package v0.1.0
2026-08-14 19:09:58 +02:00

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External AI agent skills — data-centre-operator

Proven, publicly available AI agent skills mapped to this occupation. Nothing is copied from the sources: every entry is a name, a one-line summary and a link to the upstream skill package. Each section names its source repository, commit, license and retrieval date.

Tiers: core = the skill directly exercises a top market hard skill, tool or method (from gated job-ad evidence) or an essential ESCO competence of this occupation; adjacent = plausibly useful, secondary. Entries are capped at 12 per source and 80 in total per occupation (core first, strongest matches survive); everything beyond the caps is excluded and logged in the pipeline audit trail, not in this package.

Matched deterministically (ISCO group + title/competence keywords, tiered against market evidence + ESCO essentials) by pipeline/p5_enrich_ai_skills.py on 2026-07-14.

Source: anthropics/skills

  • Repository: https://github.com/anthropics/skills (commit f6656c1, retrieved 2026-07-14)
  • License: Apache-2.0; the document skills (docx/pdf/pptx/xlsx) are source-available — see the LICENSE.txt in the upstream skill folder
Skill Tier What it adds Upstream
mcp-builder adjacent Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python … source
skill-creator adjacent Create new skills, modify and improve existing skills, and measure skill performance. Use when users want to create a skill from scratch, edit, or optimize an existing skill, run evals to test a skill, benchmark skill performance with … source
claude-api adjacent Reference for the Claude API / Anthropic SDK — model ids, pricing, params, streaming, tool use, MCP, agents, caching, token counting, model migration. TRIGGER — read BEFORE opening the target file; don't skip because it "looks like a … source
docx adjacent Use this skill whenever the user wants to create, read, edit, or manipulate Word documents (.docx files) or Word templates (.dotx files). Triggers include: any mention of 'Word doc', 'word document', '.docx', '.dotx', or requests to … source
pdf adjacent Use this skill whenever the user wants to do anything with PDF files. This includes reading or extracting text/tables from PDFs, combining or merging multiple PDFs into one, splitting PDFs apart, rotating pages, adding watermarks, creating … source
webapp-testing adjacent Toolkit for interacting with and testing local web applications using Playwright. Supports verifying frontend functionality, debugging UI behavior, capturing browser screenshots, and viewing browser logs. source

Source: obra/superpowers

Skill Tier What it adds Upstream
using-git-worktrees adjacent Use when starting feature work that needs isolation from current workspace or before executing implementation plans - ensures an isolated workspace exists via native tools or git worktree fallback source
brainstorming adjacent You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation. source
executing-plans adjacent Use when you have a written implementation plan to execute in a separate session with review checkpoints source
finishing-a-development-branch adjacent Use when implementation is complete, all tests pass, and you need to decide how to integrate the work - guides completion of development work by presenting structured options for merge, PR, or cleanup source
subagent-driven-development adjacent Use when executing implementation plans with independent tasks in the current session source
writing-plans adjacent Use when you have a spec or requirements for a multi-step task, before touching code source
writing-skills adjacent Use when creating new skills, editing existing skills, or verifying skills work before deployment source
dispatching-parallel-agents adjacent Use when facing 2+ independent tasks that can be worked on without shared state or sequential dependencies source
receiving-code-review adjacent Use when receiving code review feedback, before implementing suggestions, especially if feedback seems unclear or technically questionable - requires technical rigor and verification, not performative agreement or blind implementation source
requesting-code-review adjacent Use when completing tasks, implementing major features, or before merging to verify work meets requirements source
systematic-debugging adjacent Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes source
test-driven-development adjacent Use when implementing any feature or bugfix, before writing implementation code source

Source: wshobson/agents

Skill Tier What it adds Upstream
application-performance-observability-engineer (agent) core Build production-ready monitoring, logging, and tracing systems. Implements comprehensive observability strategies, SLI/SLO management, and incident response workflows. Use PROACTIVELY for monitoring infrastructure, performance … source
auth-implementation-patterns core Master authentication and authorization patterns including JWT, OAuth2, session management, and RBAC to build secure, scalable access control systems. Use when implementing auth systems, securing APIs, or debugging security issues. source
incident-runbook-templates core Create structured incident response runbooks with step-by-step procedures, escalation paths, and recovery actions. Use this skill when building a service outage runbook for a payment processing system; creating database incident procedures … source
async-python-patterns core Master Python asyncio, concurrent programming, and async/await patterns for high-performance applications. Use when building async APIs, concurrent systems, or I/O-bound applications requiring non-blocking operations. source
multi-cloud-architecture core Design multi-cloud architectures using a decision framework to select and integrate services across AWS, Azure, GCP, and OCI. Use when building multi-cloud systems, avoiding vendor lock-in, or leveraging best-of-breed services from … source
python-resource-management core Python resource management with context managers, cleanup patterns, and streaming. Use when managing connections, file handles, implementing cleanup logic, or building streaming responses with accumulated state. source
mtls-configuration core Configure mutual TLS (mTLS) for zero-trust service-to-service communication. Use when implementing zero-trust networking, certificate management, or securing internal service communication. source
python-configuration core Python configuration management via environment variables and typed settings. Use when externalizing config, setting up pydantic-settings, managing secrets, or implementing environment-specific behavior. source
sql-optimization-patterns core Master SQL query optimization, indexing strategies, and EXPLAIN analysis to dramatically improve database performance and eliminate slow queries. Use when debugging slow queries, designing database schemas, or optimizing application … source
distributed-debugging-devops-troubleshooter (agent) core Expert DevOps troubleshooter specializing in rapid incident response, advanced debugging, and modern observability. Masters log analysis, distributed tracing, Kubernetes debugging, performance optimization, and root cause analysis. Handles … source
application-performance-performance-engineer (agent) core Expert performance engineer specializing in modern observability, application optimization, and scalable system performance. Masters OpenTelemetry, distributed tracing, load testing, multi-tier caching, Core Web Vitals, and performance … source
postmortem-writing core Write effective blameless postmortems with root cause analysis, timelines, and action items. Use when conducting incident reviews, writing postmortem documents, or improving incident response processes. source

Source: a5c-ai/babysitter

Skill Tier What it adds Upstream
translation-management core Integration with translation management systems and i18n workflows. Connect with Crowdin, Transifex, Weblate, manage translation memory, synchronize glossaries, and automate localization pipelines. source
embedded-docs core Embedded firmware documentation generation and maintenance using Doxygen and related tools. Expert skill for API documentation, hardware interface documentation, memory maps, and integration with documentation systems. source
incident-platforms core Incident management platform integration for PagerDuty, Opsgenie, and related tools source
node-operations core Blockchain node deployment and operations. Supports Ethereum execution and consensus clients, validator operations, node monitoring, MEV-Boost configuration, and archive node management. source

Source: affaan-m/everything-claude-code

Skill Tier What it adds Upstream
agentic-os core Build persistent multi-agent operating systems on Claude Code. Covers kernel architecture, specialist agents, slash commands, file-based memory, scheduled automation, and state management without external databases. source
network-config-validation core Pre-deployment checks for router and switch configuration, including dangerous commands, duplicate addresses, subnet overlaps, stale references, management-plane risk, and IOS-style security hygiene. source

Source: davila7/claude-code-templates

Skill Tier What it adds Upstream
observability-engineer core Build production-ready monitoring, logging, and tracing systems. Implements comprehensive observability strategies, SLI/SLO management, and incident response workflows. source
it-operations core Manages IT infrastructure, monitoring, incident response, and service reliability. Provides frameworks for ITIL service management, observability strategies, automation, backup/recovery, capacity planning, and operational excellence … source
pinecone core Managed vector database for production AI applications. Fully managed, auto-scaling, with hybrid search (dense + sparse), metadata filtering, and namespaces. Low latency (<100ms p95). Use for production RAG, recommendation systems, or … source
langchain core Framework for building LLM-powered applications with agents, chains, and RAG. Supports multiple providers (OpenAI, Anthropic, Google), 500+ integrations, ReAct agents, tool calling, memory management, and vector store retrieval. Use for … source

Source: itsmostafa/aws-agent-skills

Skill Tier What it adds Upstream
cloudformation core AWS CloudFormation infrastructure as code for stack management. Use when writing templates, deploying stacks, managing drift, troubleshooting deployments, or organizing infrastructure with nested stacks. source

Source: jeffallan/claude-skills

Skill Tier What it adds Upstream
websocket-engineer core Use when building real-time communication systems with WebSockets or Socket.IO. Invoke for bidirectional messaging, horizontal scaling with Redis, presence tracking, room management. source
terraform-engineer core Use when implementing infrastructure as code with Terraform across AWS, Azure, or GCP. Invoke for module development (create reusable modules, manage module versioning), state management (migrate backends, import existing resources, … source

Source: jeremylongshore/claude-code-plugins-plus-skills

Skill Tier What it adds Upstream
generating-stored-procedures core Use when you need to generate, validate, or deploy stored procedures for PostgreSQL, MySQL, or SQL Server. Creates database functions, triggers, and procedures with proper error handling and transaction management. Trigger with phrases … source
supabase-deploy-integration core Deploy and manage Supabase projects in production. Covers database migrations, Edge Functions deployment, secrets management, zero-downtime rollouts, blue/green branching, rollback procedures, and post-deploy health checks. Use when … source
notion-load-scale core High-volume Notion operations: parallel requests within 3 req/sec, worker queues, database pagination at scale, incremental sync for large workspaces, and memory management for bulk operations. Trigger with phrases like "notion scale", … source
collecting-infrastructure-metrics core Collect comprehensive infrastructure performance metrics across compute, storage, network, containers, load balancers, and databases. Use when monitoring system performance or troubleshooting infrastructure issues. Trigger with phrases … source
adobe-prod-checklist core Execute Adobe production deployment checklist covering credential management, API health checks, rate limit configuration, and rollback procedures for Firefly Services, PDF Services, and I/O Events integrations. Trigger with phrases like … source
clickhouse-observability core Monitor ClickHouse with Prometheus metrics, Grafana dashboards, system table queries, and alerting for query performance, merge health, and resource usage. Use when setting up ClickHouse monitoring, building Grafana dashboards, or … source

Source: kubesphere/kubesphere

Skill Tier What it adds Upstream
kubesphere-devops-argocd core Use when configuring ArgoCD in KubeSphere DevOps, including GitOps deployments, application management, SSO setup, or troubleshooting ArgoCD issues source

Source: microsoft/skills

Skill Tier What it adds Upstream
azure-resource-manager-mysql-dotnet core Azure MySQL Flexible Server SDK for .NET. Database management for MySQL Flexible Server deployments. Use for creating servers, databases, firewall rules, configurations, backups, and high availability. Triggers: "MySQL", … source
azure-resource-manager-postgresql-dotnet core Azure PostgreSQL Flexible Server SDK for .NET. Database management for PostgreSQL Flexible Server deployments. Use for creating servers, databases, firewall rules, configurations, backups, and high availability. Triggers: "PostgreSQL", … source
azure-mgmt-apicenter-dotnet core Azure API Center SDK for .NET. Centralized API inventory management with governance, versioning, and discovery. Use for creating API services, workspaces, APIs, versions, definitions, environments, deployments, and metadata schemas. … source
kql core KQL language expertise for writing correct, efficient Kusto Query Language queries. Covers syntax gotchas, join patterns, dynamic types, datetime pitfalls, regex patterns, serialization, memory management, result-size discipline, and … source

Source: mukul975/Anthropic-Cybersecurity-Skills

Skill Tier What it adds Upstream
implementing-pam-for-database-access core Deploy privileged access management for database systems including Oracle, SQL Server, PostgreSQL, and MySQL. Covers session proxy configuration, credential vaulting, query auditing, dynamic credentia source
performing-power-grid-cybersecurity-assessment core This skill covers conducting cybersecurity assessments of electric power grid infrastructure including generation facilities, transmission substations, distribution systems, and energy management system (EMS) control centers. It addresses … source
configuring-host-based-intrusion-detection core Configures host-based intrusion detection systems (HIDS) to monitor endpoint file integrity, system calls, and configuration changes for security violations. Use when deploying OSSEC, Wazuh, or AIDE for endpoint monitoring, building file … source
implementing-delinea-secret-server-for-pam core Implements Delinea Secret Server for privileged access management (PAM) including secret vault configuration, role-based access policies, automated password rotation, session recording, and integration with Active Directory and cloud … source
analyzing-memory-dumps-with-volatility core Analyzes RAM memory dumps from compromised systems using the Volatility framework to identify malicious processes, injected code, network connections, loaded modules, and extracted credentials. Supports Windows, Linux, and macOS memory … source
implementing-security-monitoring-with-datadog core Implements security monitoring using Datadog Cloud SIEM, Cloud Security Management (CSM), and Workload Protection to detect threats, enforce compliance, and respond to security events across cloud and hybrid infrastructure. Covers Agent … source

Source: Orchestra-Research/AI-research-SKILLs

Skill Tier What it adds Upstream
pinecone core Managed vector database for production AI applications. Fully managed, auto-scaling, with hybrid search (dense + sparse), metadata filtering, and namespaces. Low latency (<100ms p95). Use for production RAG, recommendation systems, or … source
langchain core Framework for building LLM-powered applications with agents, chains, and RAG. Supports multiple providers (OpenAI, Anthropic, Google), 500+ integrations, ReAct agents, tool calling, memory management, and vector store retrieval. Use for … source

Source: ruvnet/claude-code-flow

Skill Tier What it adds Upstream
AgentDB Memory Patterns core Implement persistent memory patterns for AI agents using AgentDB. Includes session memory, long-term storage, pattern learning, and context management. Use when building stateful agents, chat systems, or intelligent assistants. source

Source: ruvnet/ruflo

Skill Tier What it adds Upstream
AgentDB Memory Patterns core Implement persistent memory patterns for AI agents using AgentDB. Includes session memory, long-term storage, pattern learning, and context management. Use when building stateful agents, chat systems, or intelligent assistants. source

Source: secondsky/claude-skills

Skill Tier What it adds Upstream
websocket-implementation core Implements real-time WebSocket communication with connection management, room-based messaging, and horizontal scaling. Use when building chat systems, live notifications, collaborative tools, or real-time dashboards. source

Source: wondelai/skills

Skill Tier What it adds Upstream
system-design core Design scalable distributed systems using structured approaches for load balancing, caching, database scaling, and message queues. Use when the user mentions "system design", "scale this", "high availability", "rate limiter", "design a URL … source

Source: zechenzhangAGI/AI-research-SKILLs

Skill Tier What it adds Upstream
pinecone core Managed vector database for production AI applications. Fully managed, auto-scaling, with hybrid search (dense + sparse), metadata filtering, and namespaces. Low latency (<100ms p95). Use for production RAG, recommendation systems, or … source
langchain core Framework for building LLM-powered applications with agents, chains, and RAG. Supports multiple providers (OpenAI, Anthropic, Google), 500+ integrations, ReAct agents, tool calling, memory management, and vector store retrieval. Use for … source

Source: NVIDIA/skills

Skill Tier What it adds Upstream
rag-perf adjacent Performance benchmarking for a deployed NVIDIA RAG Blueprint server: profiling pass + aiperf load test driven by a single YAML config. Not for accuracy / RAGAS scoring (use rag-eval) or for deploying / repairing services (use … source
cuopt-install adjacent Install cuOpt for Python, C, or server via pip, conda, or Docker; verify the install. For building cuOpt from source, see cuopt-developer. source
mcore-run-on-slurm adjacent How to launch distributed Megatron-LM training jobs on a SLURM cluster. Covers a minimal sbatch skeleton, environment-variable setup for torch.distributed.run, CUDA_DEVICE_MAX_CONNECTIONS rules across hardware and parallelism modes, … source
rag-blueprint adjacent NVIDIA RAG Blueprint — deploy, configure, troubleshoot, and manage. Handles any RAG action: deploy, install, start, enable, disable, toggle, change, configure, troubleshoot, debug, fix, shutdown, stop, or tear down any RAG feature or … source
cuopt-server-api-python adjacent cuOpt REST server — start server, endpoints, Python/curl client examples. Use when the user is deploying or calling the REST API. source
tao-run-platform adjacent TAO Execution SDK for submitting and monitoring GPU training jobs on supported platforms (Brev, SLURM, local Docker, Kubernetes). Use when the user wants to run TAO jobs through the SDK, get job tracking, S3 I/O wrapping, multi-node … source
aiq-deploy adjacent Use when asked to install, deploy, run, validate, troubleshoot, or stop NVIDIA AI-Q Blueprint infrastructure. source
deepstream-sop adjacent Use this skill when building, deploying, evaluating, debugging, or measuring latency for the DeepStream SOP Inference Microservice — a GPU-accelerated FastAPI service that detects whether operators perform assembly-line steps in order via … source
dynamo-recipe-runner adjacent Select, validate, patch, and deploy existing NVIDIA Dynamo Kubernetes recipes. Use for model/backend/GPU/deployment-mode recipe bring-up; use router-starter for router-only mode work and troubleshoot for broken deployments. source
launch-nemo-rl adjacent Playbook for launching, monitoring, stopping, and debugging NeMo-RL recipes on a Kubernetes cluster via the nrl-k8s CLI. Covers ephemeral vs long-lived RayCluster modes, iterating on runs, and debugging hung or failed training jobs. source
nemotron-retrieval-recipes adjacent Use when planning, debugging, tuning, evaluating, exporting, or deploying public Nemotron embed/rerank retrieval recipes. source
physical-ai-infrastructure-setup-and-resilient-scaling adjacent Use when the user wants to set up, scale, validate, or harden NVIDIA physical AI infrastructure for synthetic data generation workflows across local MicroK8s or Azure AKS, including Kubernetes clusters, inference endpoint deployment, OSMO … source