Agent Skills
Instruction packs that give your AI agent know-how — some work anywhere, some only with the tool they came with.
✦ Standalone skills3,264
Self-contained. Install one into any project and it works on its own — no other software needed.
🧰 Tool add-ons529
Come bundled with a specific tool and only work together with it — they teach your agent how to operate that tool.
🔌 Needs setup first122
Each relies on something you set up separately — such as an app, a command-line tool or an account — and its page names what that is.
openai · Development
1,540 standalone skillsmcloud-variables
★ 195by medusajs
Execute mcloud variables commands to list and get environment variables for a Cloud environment. Use when inspecting, reading, or exporting environment variables. Never pass --reveal unless the user explicitly requests secret values.
creating-agents-in-medusa
★ 195by medusajs
Use when building an internal admin-facing AI agent in a Medusa project. These agents are operated by merchants and store operators — not customers. Covers data models, module service, agent runtime (tools, system prompt, streamText), streaming API routes (NDJSON), and admin UI chat extensions. Load for any internal agent type: store operations assistant, product audit, cohort analysis, customer service tooling for support staff, etc. Do NOT use for customer-facing agents (storefront chatbots, buyer-side assistants).
db-migrate
★ 195by medusajs
Run database migrations in Medusa
building-admin-dashboard-customizations
★ 195by medusajs
Load automatically when planning, researching, or implementing Medusa Admin dashboard UI (widgets, custom pages, forms, tables, data loading, navigation). REQUIRED for all admin UI work in ALL modes (planning, implementation, exploration). Contains design patterns, component usage, and data loading patterns that MCP servers don't provide.
building-storefronts
★ 195by medusajs
Load automatically when planning, researching, or implementing Medusa storefront features (calling custom API routes, SDK integration, React Query patterns, data fetching). REQUIRED for all storefront development in ALL modes (planning, implementation, exploration). Contains SDK usage patterns, frontend integration, and critical rules for calling Medusa APIs.
db-generate
★ 195by medusajs
Generate database migrations for a Medusa module
mcloud-logs
★ 195by medusajs
Execute mcloud logs to fetch and stream runtime logs for Cloud environments. Use when reading backend or storefront logs, filtering by time range, searching for errors, or scoping logs to a specific deployment.
storefront-best-practices
★ 195by medusajs
ALWAYS use this skill when working on ecommerce storefronts, online stores, shopping sites. Use for ANY storefront component including checkout pages, cart, payment flows, product pages, product listings, navigation, homepage, or ANY page/component in a storefront. CRITICAL for adding checkout, implementing cart, integrating Medusa backend, or building any ecommerce functionality. Framework-agnostic (Next.js, SvelteKit, TanStack Start, React, Vue). Provides patterns, decision frameworks, backend integration guidance.
mcloud-environments
★ 195by medusajs
Execute mcloud environments commands to list, get, create, delete, redeploy, or trigger builds for Cloud environments. Use when managing environment lifecycle, redeploying after variable changes, or starting new builds from source.
temporal-developer
✓★ 191by temporalio
Develop, debug, and manage Temporal applications across Python, TypeScript, Go, Java, .NET, Ruby, and Rust. Use when the user is building workflows, activities, workers, or background job queues with a Temporal SDK, debugging issues like non-determinism errors, stuck workflows, or activity retries, using Temporal CLI, Temporal Server, or Temporal Cloud, or working with durable execution concepts like signals, queries, heartbeats, versioning, continue-as-new, child workflows, or saga patterns. Also use when the user mentions "run a Temporal workflow from the CLI", "start a dev server", "run temporal server start-dev", "temporal workflow start", "temporal workflow execute", "temporal workflow signal", "temporal workflow query", "temporal workflow update".
dv-solution
✓★ 163by microsoft
Dataverse solution lifecycle — create, export, import, promote across environments, and validate deployments. Use when the user wants to package customizations, deploy to another environment, or move work between dev / test / prod.
dv-overview
✓★ 163by microsoft
Tool routing and cross-cutting rules for Dataverse work — which skill applies to which task, environment-confirmation, and pull-to-repo. Use when the user mentions Dataverse, Dynamics 365, Power Platform, or CRM; this skill picks the specialist (dv-connect / dv-data / dv-metadata / dv-query / dv-solution / dv-admin / dv-security) for the request.
dv-connect
✓★ 163by microsoft
One-step setup for a Dataverse environment — installs tools, authenticates, registers the MCP server, and writes `.env`. Use when starting a new project, switching environments, fixing authentication, or troubleshooting an MCP connection that won't come up.
dv-security
✓★ 163by microsoft
Security-role assignment, user access, application users, business units, and admin self-elevation in Dataverse environments. Use when the user wants to give someone access, grant a role, become an admin, or add a service principal.
suggest
✓★ 159by brave
USE FOR query autocomplete/suggestions. Fast (<100ms). Returns suggested queries as user types. Supports rich suggestions with entity info. Typo-resilient.
dd-audit
★ 139by datadog-labs
Audit Trail investigations - who changed what, key compromise, cost spike root cause, compliance evidence (SOC 2/PCI), and AI activity auditing.
agent-observability-eval-bootstrap
★ 139by datadog-labs
Bootstrap evaluators from production traces — by default propose online LLM-judge evaluators and, after you confirm, create them in Datadog as disabled drafts (never auto-enabled); on request emit Python SDK code or a framework-agnostic JSON spec instead. Use when user says "bootstrap evaluators", "generate evaluators", "create evals from traces", "eval bootstrap", "write evaluators", "build eval suite", "publish evaluators", or wants to generate BaseEvaluator/LLMJudge code or online judge configs from production LLM trace data. Works with ml_app and optional RCA report or failure hypothesis.
verify-ssi
★ 139by datadog-labs
Verify Single Step Instrumentation (SSI) is working end-to-end on Linux hosts — SSI automatically instruments applications for APM without code changes. Only use after enable-ssi has run.
onboarding-summary
★ 139by datadog-labs
Generate a live Single Step Instrumentation (SSI) onboarding confirmation report for Linux hosts — verifies APM instrumentation is working end-to-end with deep links into the Datadog UI. Only use after agent-install and enable-ssi have both completed.
upgrade-browser-sdk-v5
★ 139by datadog-labs
Upgrade Datadog Browser SDK from v4 to v5. Use when encountering removed options like proxyUrl, sampleRate, replaySampleRate, premiumSampleRate, allowedTracingOrigins, or deprecated APIs like addRumGlobalContext, removeUser, or when a project references datadoghq-browser-agent.com CDN with /v4/ paths.
upgrade-browser-sdk-v6
★ 139by datadog-labs
Upgrade Datadog Browser SDK from v5 to v6. Use when encountering removed options like useCrossSiteSessionCookie, sendLogsAfterSessionExpiration, or when dropping IE11 support, or when a project references datadoghq-browser-agent.com CDN with /v5/ paths.
upgrade-browser-sdk-v7
★ 139by datadog-labs
Upgrade Datadog Browser SDK from v6 to v7. Use when encountering removed options like betaEncodeCookieOptions, allowFallbackToLocalStorage, trackBfcacheViews, usePciIntake, changed APIs like forwardErrorsToLogs, startDurationVital, stopDurationVital, or when a project references datadoghq-browser-agent.com CDN with /v6/ paths.
dd-apm
★ 139by datadog-labs
APM - install, onboard, instrument, enable, set up, configure, traces, services, dependencies, performance analysis. Use for any request involving Datadog APM setup, instrumentation (SSI, ddtrace, agent install), or analysis.
agent-observability-eval-pipeline
★ 139by datadog-labs
End-to-end Agent Observability pipeline for an instrumented ml_app — classify production traces, root-cause failures, bootstrap evaluators, then (optionally) sample + publish a dataset, generate + run an experiment, and analyze results. Six narrated phases with a standardized banner and a "continue" checkpoint between each. Pure orchestration over the agent-observability sub-skills (`agent-observability-session-classify`, `agent-observability-trace-rca`, `agent-observability-eval-bootstrap`, `agent-observability-experiment-bootstrap`, `agent-observability-experiment-analyzer`). Use when user says "run the eval pipeline", "go from traces to evals", "bootstrap evals end to end", "classify then RCA then bootstrap", "build an eval set from scratch", "onboard me to datasets and experiments", "walk me through experiments", "I have an ml_app, now what", "Agent Observability onboarding", "guided experiment setup", "from traces to experiments", or wants a deterministic, narrated tour from production data through evaluators, datasets, and experiments. Stop early with `--stop-after <phase>` to short-circuit at evaluators or dataset, or resume mid-flow with `--start-at <phase>`.
agent-observability-experiment-analyzer
★ 139by datadog-labs
Analyze LLM experiment results. Handles single or comparative experiments, exploratory or Q&A modes. Use when user says "analyze experiment", "compare experiments", "analyze against baseline", or provides one or two experiment IDs for analysis.
agent-skills
★ 139by datadog-labs
Datadog skills for AI agents. Essential monitoring, logging, tracing and observability.
k9-ownership-byod-setup
★ 139by datadog-labs
Generate a BYOD ownership preferences reference table for a customer. Walks through preference types, generates CSV, and provides upload instructions (UI, API, cloud storage, or Terraform). Use when asked about BYOD setup, preferences reference table, k9_ownership_preferences, or ownership customization.
dd-logs
★ 139by datadog-labs
Log management - search, archives, metrics, and cost control.
troubleshoot-ssi
★ 139by datadog-labs
Diagnose and fix Single Step Instrumentation (SSI) issues on Linux hosts — SSI automatically instruments applications for APM without code changes. Only use if the agent and SSI are configured but traces are missing or instrumentation is not working.
dd-audit-key-compromise
★ 139by datadog-labs
Investigate a potentially compromised Datadog API key — timeline of actions, geo/IP breakdown, endpoints called, anomaly flags, and remediation steps.