Skills
98,639 packaged capabilities and playbooks for agents. Install any of them with one command.
Development
Comprehensive bash script debugging and troubleshooting techniques for 2025. Proactively activate for: (1) debugging a misbehaving bash script, (2) using set -x, set -e, set -u, set -o pipefail (strict mode), (3) customizing PS4 for richer trace output, (4) trap DEBUG, ERR, and EXIT for diagnostics, (5) bashdb and other interactive debuggers, (6) profiling slow scripts (timing, BASH_REMATCH overhead), (7) reproducing CI-only failures locally, (8) resolving unbound variable or command not found errors, (9) understanding subshell vs current-shell variable scope. Provides: strict-mode template, PS4 patterns, trap recipes for instrumentation, profiling techniques, and a step-by-step debugging playbook.
Expert in design tokens using the DTCG specification. Use this skill when users ask about design tokens, DTCG format, token validation, formatting, transformation, color spaces (sRGB, Display P3, OKLCH), references and aliasing, resolvers, theming with modifiers/contexts, multi-platform design systems, accessibility, or working with tools like jq, jsonata, and terrazzo. Helps with token file creation, resolver configuration, structure, naming conventions, and best practices
Use for any project where external users need a login to view or interact with Domo dashboards — regardless of what the user calls it. If someone wants clients, customers, or partners to have accounts and see Domo content (their data only, branded, filtered per user), this is the right skill. Covers the full build from scratch — auth, user management, data isolation, and Domo embed integration. Trigger on phrases like 'give clients a login to see dashboards,' 'sell access to our analytics,' 'white-label reporting for customers,' 'client portal with Domo,' 'productize our Domo data,' or 'external users should see their own dashboards.' Skip only if they already have a working portal and need just one specific sub-feature (edit embeds → use edit-embed, JS API filters → use jsapi-filters, programmatic filters → use programmatic-filters).
Use when the user wants the GitNexus engineering pipeline run end-to-end on a task: gitnexus-plan (plan depth chosen up front), a blocking gate to execute with gitnexus-work or stop, finishing with a gitnexus-review of the result. Examples: "/gitnexus-lfg Add retry support to the ingestion pipeline", "run the gitnexus pipeline on this", "plan, build and review this feature".
Integrate LaunchDarkly qualitative user feedback into a JavaScript/TypeScript codebase. Guides framework and design system detection, builds the sendFeedback utility and feedback widget matching existing project patterns. Use when the user wants to add a Give Feedback widget, collect user sentiment tied to feature flags, set up feedback collection, or wire up the $ld:feedback tracking event
Designs and implements data layer architecture for Magento 2. Use when creating data models, designing database schemas, implementing repositories, or working with EAV/flat table structures. Masters entity design, repository patterns, collections, and database optimization.
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 (FastMCP) or Node/TypeScript (MCP SDK).
Complete Metaplex Protocol guide for Solana NFTs and digital assets. Covers Core (next-gen NFTs), Token Metadata, Bubblegum (compressed NFTs), Candy Machine, Genesis (token launches), MPL-Hybrid, Inscriptions, DAS API, and the Umi framework. The single source of truth for all Metaplex integrations.
Build and deploy an MCP server from an OpenAPI / Swagger spec using the mcp-use TypeScript SDK. Use this skill whenever the user wants to "turn this OpenAPI spec into an MCP server", "make this API usable from Claude/ChatGPT", "wrap this Swagger doc as MCP tools", "expose this REST API to an LLM", "generate MCP tools from a spec", or pastes/attaches an `openapi.yaml`, `openapi.json`, or `swagger.json` and asks for a Claude-compatible version. Trigger even if the user doesn't say "MCP" — if they describe an existing HTTP API (REST endpoints, an internal service, a third-party API they have a key for) and want an LLM to call it, this is the right skill. Covers spec ingestion (file path, URL, or pasted), operation-to-tool mapping, auth wiring (apiKey, bearer, basic, OAuth bearer), scaffolding with `create-mcp-use-app`, tool generation with proper zod schemas, live testing in the mcp-use inspector, and deploying to Manufact / mcp-use cloud
Control which data each viewer sees in an embedded Domo dashboard/card via server-side programmatic filters and dataset switching. Covers the OAuth → embed token flow, standard filters, SQL filters (OR/BETWEEN/LIKE), per-dataset targeting, datasetRedirects for multi-tenant architectures, and token size limits. Use for any per-viewer, per-role, or per-tenant data restrictions at embed time. Not for client-side JS API filtering (use jsapi-filters).
Use when a Roblox experience is slow, laggy, stuttering, crashing or out of memory, or before shipping or updating one: my game lags on mobile, low FPS, frame spikes, server lag or low heartbeat, physics lag, network lag or high KB/s, memory leaks or memory that keeps growing, crashes on phones, long join or load times, too many parts, instances, draw calls or triangles, MicroProfiler, Script Profiler, Luau heap, Developer Console memory, Scene Analysis, StreamingEnabled tuning, performance budgets, and publishing, releasing an update, restarting servers or rolling back a version.
Server-side API endpoints using the server property on createFileRoute, HTTP method handlers (GET, POST, PUT, DELETE), createHandlers for per-handler middleware, handler context (request, params, context), request body parsing, response helpers, file naming for API routes.
Guide for Vercel AI SDK v6 implementation patterns including generateText, streamText, ToolLoopAgent, structured output with Output helpers, useChat hook, tool calling, embeddings, middleware, and MCP integration. Use when implementing AI chat interfaces, streaming responses, agentic applications, tool/function calling, text embeddings, workflow patterns, or working with convertToModelMessages and toUIMessageStreamResponse. Activates for AI SDK integration, useChat hook usage, message streaming, agent development, or tool calling tasks.
Web Animations API adapter patterns for HyperFrames. Use when authoring element.animate() motion, Animation currentTime seeking, document.getAnimations(), KeyframeEffect timing, fill modes, or native browser animations that must render deterministically in HyperFrames.
Batteries-included agent component for React/Next.js from ui.inference.sh. One component with runtime, tools, streaming, approvals, and widgets built in. Capabilities: drop-in agent, human-in-the-loop, client-side tools, form filling. Use for: building AI chat interfaces, agentic UIs, SaaS copilots, assistants. Triggers: agent component, agent ui, chat agent, shadcn agent, react agent, agentic ui, ai assistant ui, copilot ui, inference ui, human in the loop
AscendC operator end-to-end development orchestrator. Use when the user needs to develop a new operator, implement a custom operator, or complete the full process from requirements to testing. Keywords: operator development, end-to-end, complete process, workflow orchestration, create a new operator.
Server-side authentication primitives for TanStack Start: session cookies (HttpOnly, Secure, SameSite, __Host- prefix), session read/issue/destroy via createServerFn and middleware, OAuth authorization-code flow with state and PKCE, password-reset enumeration defense, CSRF for non-GET RPCs, rate limiting auth endpoints, and session rotation on privilege change. Pairs with router-core/auth-and-guards for the routing side.
Expert knowledge for Azure Event Grid development, including troubleshooting, best practices, decision-making, architecture and design patterns, limits and quotas, security, configuration, integrations, and coding patterns. Use when building Event Grid topics/namespaces, MQTT brokers, webhook handlers, Functions, or Service Bus integrations, and other Azure Event Grid development tasks. Not for Azure Service Bus (use azure-service-bus), Azure Event Hubs (use azure-event-hubs), Azure Notification Hubs (use azure-notification-hubs), or Azure Functions (use azure-functions).
CCXT cryptocurrency exchange library for C# and .NET developers. Covers both REST API (standard) and WebSocket API (real-time). Helps install CCXT, connect to exchanges, fetch market data, place orders, stream live tickers/orderbooks, handle authentication, and manage errors in .NET projects. Use when working with crypto exchanges in C# applications, trading systems, or financial software. Supports .NET Standard 2.0+
Create Domo Code Engine packages from CLI workflows with deterministic payload contracts, automatic function parameter datatype mapping, and manifest packagesMapping follow-up guidance. Use when an agent must create a new package/versioned package container rather than only invoke an existing function from app runtime code.
Update Domo Code Engine packages through CLI-driven versioned lifecycle workflows with compatibility checks, datatype contract safeguards, and manifest mapping drift synchronization. Use when an agent must update package code or create a new package version and keep app mappings aligned.
Create a plan for the specified task and store it as GitHub issues in the repository of the current working directory. Given the URL of a GitHub issue, it turns that issue into the parent "plan" issue (Goal, Context and a checklist of phases) and creates one child issue per phase, linking every phase as a native GitHub sub-issue of the parent. Stops for user approval before creating any issue. After creation, the plan is meant to be implemented with the codely-plan-phase-implement-github skill.
**Custom Domo connector authorship** — invoke when someone is writing the JavaScript code that defines a custom Domo connector. Primary signals: questions about authentication.js, dataProcessing.js, or Domo's connector APIs (datagrid, httprequest, auth, metadata). Covers all connector coding topics: auth credential validation, API pagination loops, writeback connectors, column consistency, connector README docs. The user is *building* a connector in Connector Dev Studio, not using a pre-built one. Skip for: pre-built connectors (Salesforce, Postgres, Snowflake), Python connector, Domo App Platform cards/apps, Workflows, Federated Connectors.
Wire a PostHog endpoint into a client app or SDK. Covers fetching the OpenAPI spec, generating a typed client with openapi-generator or @hey-api/openapi-ts, sending the right auth header, shaping the variables payload (HogQL code_name vs insight breakdown property), handling rate-limit and materialised-endpoint error responses. Use when the user says "how do I call my endpoint", "generate a client for this", or "what auth header do I use".
Create a PostHog endpoint with the right shape on the first try — covers query kind choice, name conventions, what to expose as variables (HogQL code_name vs insight breakdown), data_freshness_seconds, and whether to materialise on day one. Use when the user says "create an endpoint", "expose this query as an API", "turn this insight into an endpoint", or asks for help structuring a new endpoint. Steers away from common mistakes: materialising a query with cohort breakdowns or an ineligible compare query, inline-only variables on a materialised endpoint, unbounded date ranges, ambiguous names.
Diagnoses CI and pull-request pipeline health for a GitHub repo using the engineering analytics MCP tools—pull-requests (PR list with CI status), workflow-health (per-workflow CI trends), and pr-lifecycle (a single PR's timeline). Use when asked whether CI is getting faster or slower, which GitHub Actions workflow is the slow or flaky long pole, how long PRs take from open to merge, how an author's merge time compares to the cohort, which open PRs have failing or pending CI, or where a specific pull request is stuck. Triggers on “engineering analytics,” “is CI getting slower,” “slow workflow,” “flaky CI,” “time to merge,” “cycle time,” “PR throughput,” “failing checks,” “where is PR <n> stuck,” “CI long pole,” “what's holding up this PR.” For a verdict on one specific CI failure (whose fault, which commit) use investigating-ci-failures; to save these numbers as insights use turning-engineering-analytics-into-insights.
Diagnose why a PostHog endpoint is slow or expensive and propose a concrete fix — bump the cache TTL, enable materialisation, restructure variables, or rewrite the query. Use when the user says “this endpoint is slow”, “my endpoint times out”, “we're hitting the cost cap on this one”, or asks “should I materialise this?”. Focuses on a single named endpoint, not a project-wide audit.
Set up Domo's embedded edit experience — external users create, edit, save, and share Domo content via an embedded iframe. Covers Identity Broker, JWT auth, role-based access (Admin/Privileged/Editor/Participant), instance mapping, and edit URL generation. Use for any Domo edit-mode embedding. Not for read-only embeds (use programmatic-filters) or client-side filtering (use jsapi-filters).
AI movement decision router for chase, patrol, crowd, and bake choices on top of NavigationAgent/Server. Use when deciding node agent vs RID server, bake vs obstacle, layer masks, or retarget policy — not for engine navmesh recipes. Keywords: AI navigation, chase retarget, patrol, crowd RVO, bake vs obstacle, NavigationAgent decision tree.
Install and wire registry blocks and components into HyperFrames compositions. Use when running hyperframes add, installing a block or component, wiring an installed item into index.html, or working with hyperframes.json. Covers the add command, install locations, block sub-composition wiring, component snippet merging, and registry discovery
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.