Agent Skills

create-auth-skill

★ 199

by better-auth

Scaffold and implement authentication in TypeScript/JavaScript apps using Better Auth. Detect frameworks, configure database adapters, set up route handlers, add OAuth providers, and create auth UI pages. Use when users want to add login, sign-up, or authentication to a new or existing project with Better Auth.

organization-best-practices

★ 199

by better-auth

Configure multi-tenant organizations, manage members and invitations, define custom roles and permissions, set up teams, and implement RBAC using Better Auth's organization plugin. Use when users need org setup, team management, member roles, access control, or the Better Auth organization plugin.

two-factor-authentication-best-practices

★ 199

by better-auth

Configure TOTP authenticator apps, send OTP codes via email/SMS, manage backup codes, handle trusted devices, and implement 2FA sign-in flows using Better Auth's twoFactor plugin. Use when users need MFA, multi-factor authentication, authenticator setup, or login security with Better Auth.

email-and-password-best-practices

★ 199

by better-auth

Configure email verification, implement password reset flows, set password policies, and customise hashing algorithms for Better Auth email/password authentication. Use when users need to set up login, sign-in, sign-up, credential authentication, or password security with Better Auth.

better-auth-best-practices

★ 199

by better-auth

Configure Better Auth server and client, set up database adapters, manage sessions, add plugins, and handle environment variables. Use when users mention Better Auth, betterauth, auth.ts, or need to set up TypeScript authentication with email/password, OAuth, or plugin configuration.

accessibility-aria-expert

✓★ 197

by microsoft

Detects and fixes accessibility issues in React/Fluent UI webviews. Use when reviewing code for screen reader compatibility, fixing ARIA labels, ensuring keyboard navigation, adding live regions for status messages, or managing focus in dialogs.

cosmosdb-best-practices

✓★ 197

by microsoft

Azure Cosmos DB performance optimization and best practices guidelines for NoSQL, partitioning, queries, and SDK usage. Use when writing, reviewing, or refactoring code that interacts with Azure Cosmos DB, designing data models, optimizing queries, or implementing high-performance database operations.

backport

✓★ 197

by microsoft

Backport changes (current branch, a PR, a branch, or specific commits/SHAs) onto a target branch (typically a release branch like `rel/*`). Use when the user says "backport this", "backport PR ...", "cherry-pick to <branch>", or asks to port commits to another branch. Handles stashing uncommitted work, branch creation, cherry-picking with conflict handling, pushing, and opening a PR.

building-with-medusa

★ 195

by medusajs

Load automatically when planning, researching, or implementing ANY Medusa backend features (custom modules, API routes, workflows, data models, module links, business logic). REQUIRED for all Medusa backend work in ALL modes (planning, implementation, exploration). Contains architectural patterns, best practices, and critical rules that MCP servers don't provide.

new-user

★ 195

by medusajs

Create an admin user in Medusa

mcloud-auth

★ 195

by medusajs

Execute mcloud authentication and context commands: login, logout, whoami, use, version, and signup. Use when setting up the CLI, switching accounts, verifying auth state, setting the active org/project/environment context, or checking the CLI version.

ffuf-web-fuzzing

★ 195

by jthack

Expert guidance for ffuf web fuzzing during penetration testing, including authenticated fuzzing with raw requests, auto-calibration, and result analysis

building-admin-dashboard-customizations

★ 195

by 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

★ 195

by 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.

mcloud-environments

★ 195

by 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.

mcloud-projects

★ 195

by medusajs

Execute mcloud projects commands to list, get, or delete Cloud projects. Use when discovering projects, resolving project handles by name, or retrieving project details including linked environments.

db-generate

★ 195

by medusajs

Generate database migrations for a Medusa module

mcloud-logs

★ 195

by 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

★ 195

by 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-variables

★ 195

by 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.

mcloud-deployments

★ 195

by medusajs

Execute mcloud deployments commands to list deployments, retrieve deployment details, and fetch build logs. Use when listing deployments, checking deployment status, or reading build output for debugging build failures.

mcloud-organizations

★ 195

by medusajs

Execute mcloud organizations commands to list or get Cloud organizations. Use when discovering organizations, resolving organization IDs by name, or retrieving organization details including members and subscription.

using-medusa-cloud

★ 195

by medusajs

Manages Medusa Cloud resources through the Cloud CLI (mcloud). Use when deploying, debugging deployments, managing environments, environment variables, or any Medusa Cloud operation. CRITICAL for mcloud commands, deployment failures, build logs, Cloud setup, and CI/CD workflows.

learning-medusa

★ 195

by medusajs

Load automatically when user asks to learn Medusa development (e.g., "teach me how to build with medusa", "guide me through medusa", "I want to learn medusa"). Interactive guided tutorial where Claude acts as a coding bootcamp instructor, teaching step-by-step with checkpoints and verification.

creating-agents-in-medusa

★ 195

by 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

★ 195

by medusajs

Run database migrations in Medusa

temporal-developer

✓★ 191

by 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".

agent-observability-auto-experiment

✓★ 177

by datadog-labs

Run an iterative code-improvement hill-climb against real Datadog LLM-Obs data, locally, with Claude Code as the agent. Establishes a baseline eval, makes one focused change, re-scores with the same harness, keeps the change if it improves the score in the goal's direction (labeling within-noise gains tentative), and repeats. Use when the user says "run an auto experiment", "hill-climb this code", "iteratively improve X and measure the delta", "optimize this prompt/file against my traces", "auto-optimize against LLM-Obs", or wants the local equivalent of the auto_experiments worker. Works from an ml_app, a dataset_id, an annotation_queue_id (a queue of human-labelled interactions), a list of trace_ids, or (by exception) a local dataset file. The corpus and its val/test splits live in Datadog LLM-Obs Datasets, created once per run with a timestamp in their names.

agent-observability-build-eval-from-annotations

✓★ 177

by datadog-labs

Fit a Datadog LLM-Obs evaluator to human labels. Takes an annotation queue, works out where in the trace the labelled property actually lives, drafts an LLM-judge that predicts the human label, scores that judge against the already-labelled rows with a metric agreed with the user, then hill-climbs it — inspect the errors, make one focused change, re-score, keep it only if it beats the best — for a bounded number of iterations, and finally publishes the winner to Datadog as a DISABLED evaluator (not a Datadog draft — a real evaluator with `enabled: false`). Use when the user says "build an eval from my annotations", "build an evaluator from the annotation queue", "turn my annotations into an evaluator", "learn an evaluator from my labels", "fit a judge to the annotation queue", "auto-label", "auto labelling", "automate this annotation queue", "scale up my human labels", or wants the rest of a queue graded the way the humans graded the first rows. Needs an annotation queue with at least two classes present in the human labels (e.g. one true and one false for a boolean).

agent-observability-experiment-bootstrap

✓★ 177

by datadog-labs

Bootstrap a reproducible LLM Observability experiment through the Python ddtrace SDK or the Node dd-trace SDK. Use for experiment, dataset, evaluator, benchmark, regression, or LLM-as-a-judge scaffolding. The legacy Python invocation remains supported.