Skills
98,639 packaged capabilities and playbooks for agents. Install any of them with one command.
Development
React and Next.js performance optimization guidelines from Vercel Engineering. This skill should be used when writing, reviewing, or refactoring React/Next.js code to ensure optimal performance patterns. Triggers on tasks involving React components, Next.js pages, data fetching, bundle optimization, or performance improvements.
React and Next.js performance optimization guidelines from Vercel Engineering. This skill should be used when writing, reviewing, or refactoring React/Next.js code to ensure optimal performance patterns. Triggers on tasks involving React components, Next.js pages, data fetching, bundle optimization, or performance improvements.
Analyze and port WordPress plugin behavior, custom post types, shortcodes, admin workflows, and stored data to current EmDash extension points. Use for WordPress-plugin migrations or when deciding which behavior belongs in an EmDash plugin, site schema, seed, or Astro code. Do not use for visual theme ports without plugin functionality.
Expert guidance for using JJ (Jujutsu) version control system. Use when working with JJ, whatever the subject. Operations, revsets, templates, debugging change evolution, etc. Covers JJ commands, template system, evolog, operations log, and interoperability with git remotes.
WordPress admin UI review and development guidance. Use when reviewing admin pages, settings screens, menu pages, notices, list tables, metabox-like interfaces, screen options, capability checks, admin scripts or styles, or when user mentions "admin UI", "settings page", "wp-admin", "admin screen", "options page", "list table", "admin menu", "admin notice", "screen options", or "dashboard page". Detects capability issues, Settings API misuse, admin-only performance problems, and UX mistakes in WordPress admin interfaces.
Headless WordPress and WPGraphQL review guidance. Use when reviewing decoupled WordPress architectures, WPGraphQL schema design, `register_graphql_field`, `register_graphql_connection`, `graphql_register_types`, Next.js/Gatsby/Remix frontends, preview mode, auth flows, persisted queries, or build/revalidation pipelines. Helps review schema boundaries, resolver performance, preview/auth correctness, cache invalidation, and content modeling decisions for headless WordPress stacks.
Write user stories, and acceptance criteria (which represent requirements) from a feature idea, ticket, notes, or existing behavior. Use when the user asks to write, draft, or rewrite/edit/improve requirements, a spec, BRD, user stories, use cases, or acceptance criteria.
Zod schema validation best practices for type safety, parsing, and error handling. This skill should be used when defining z.object schemas, using z.string validations, safeParse, or z.infer. This skill does NOT cover React Hook Form integration patterns (use react-hook-form skill) or OpenAPI client generation (use orval skill).
Create or redesign React and Tailwind sections, pages, flows, shells, and components. Use when the user wants new UI or a redesign. Implement one requested or selected direction directly, or generate distinct alternatives when the user asks to compare options.
Add a custom Python tool to an AG2 `Agent` using the `@tool` decorator. Use when the user wants to give an Agent a new capability backed by Python code (API calls, DB queries, computations, file ops). Covers sync and async tools, parameter typing, Pydantic schema customisation, returning typed `Input` / `ToolResult` (text / data / images / binary), `final=True` early-exit, and dependency injection via `Context` / `Inject` / `Variable` / `Depends`.
Pause an AG2 `Agent` mid-run to collect human input via `context.input()`, or gate a tool call with `approval_required()` middleware. Use when the user wants the agent to ask for confirmation, request missing info (passwords, API keys, data), or have a human approve sensitive / irreversible / expensive tool calls (sending emails, deleting records, payments).
Persist agent state across runs, shape what the LLM sees per turn, and cap history to fit a context window. Covers `KnowledgeStore` (memory / sqlite / disk / redis), `KnowledgeConfig` (`store=`, `expose_tool=`, `write_event_log=`, `compact=`, `aggregate=`, `bootstrap=`) and its opt-out flags, aggregation strategies (`WorkingMemoryAggregate` with `prompt=` override, `ConversationSummaryAggregate`), assembly policies (`WorkingMemoryPolicy`, `EpisodicMemoryPolicy`, `ConversationPolicy`, `SlidingWindowPolicy`, `TokenBudgetPolicy`, `AlertPolicy`), compaction (`TailWindowCompact`, `SummarizeCompact`), and the lifecycle events (`AggregationStarted/Failed`, `CompactionStarted/Failed`, `EventLogFailed`). Use when the user wants the agent to remember between conversations, manage long histories, or control prompt assembly.
Single-agent recursion and parallel fan-out within one AG2 `Agent` — auto-injected `run_subtask` / `run_subtasks(parallel=True)` (opt in via `tasks=TaskConfig(...)`) for self-delegation, and `Agent.as_tool()` as a lightweight no-hub way to call one named agent from inside another. Use when a single coordinator wants to break work into its own sub-tasks, fan out concurrent sub-tasks, or invoke a specialist agent as a tool. Covers context flow, recursion safety, and `persistent_stream` for sub-task history. **For two or more agents actually collaborating with a registry, durable channels, governance, or turn-taking, use `ag2-network-quickstart` instead** — the network is the standard multi-agent pattern in AG2.
Builds, simulates, and runs quantum circuits with Cirq, Google Quantum AI's framework for NISQ hardware, noise-aware low-level circuit design, and noise characterization. Use when targeting Google Quantum AI processors or their Quantum Virtual Machine models (Willow, Sycamore-class Rainbow/Weber), IonQ/AQT/Pasqal via Cirq plugins, designing noise-aware NISQ circuits, or running characterization experiments (randomized benchmarking, XEB). For IBM Quantum hardware and Qiskit Runtime prefer alterlab-qiskit; for gradient-trained quantum ML and hybrid quantum-classical models prefer alterlab-pennylane; for open-system Lindblad/master-equation dynamics prefer alterlab-qutip. Part of the AlterLab Academic Skills suite.
Graph Neural Networks with PyTorch Geometric (PyG) — node and graph classification, link prediction, GCN, GAT, and GraphSAGE layers, heterogeneous graphs, and molecular property prediction. Use when building or training GNNs for geometric deep learning on graph-structured data. Part of the AlterLab Academic Skills suite.
Swift Standard Library, Concurrency, and Observation reference. Protocols/generics, async/await, actor, SerialExecutor, Sendable, Task, TaskGroup, AsyncSequence, AsyncStream, Continuation (CheckedContinuation), Observable, @Observable, Observations, ObservationRegistrar, Span, InlineArray, RangeSet, Equatable, Hashable, Comparable, Identifiable, Optional, Codable, Result, generics, some/any.
Configure Aspire AppHost to emit explicit app config via environment variables while keeping app code free of Aspire clients and service discovery. Use when wiring AppHost resources to application configuration, ensuring production configuration is transparent and portable outside of Aspire, or avoiding Aspire client packages inside application code.
Use this skill when writing, debugging, or reviewing ast-grep patterns, YAML rules, or codemods against TypeScript or React (.ts/.tsx) code — searching for JSX elements, props, hooks, imports, or type constructs, and rewriting them. Covers the TS/React-specific traps — the tsx-vs-typescript language split, JSX and TypeScript node kinds, fragment matching, rewrites, and the @ast-grep/napi API. Complements the general-purpose ast-grep skill (rule mechanics) — reach for this one whenever the target code is TypeScript or React.
Skill for building with the Astro web framework. Helps create Astro components and pages, configure SSR adapters, set up content collections, deploy static sites, and manage project structure and CLI commands. Use when the user needs to work with Astro, mentions .astro files, asks about static site generation (SSG), islands architecture, content collections, or deploying an Astro project.
Fetch unresolved review threads on a GitHub PR, verify the validity of each comment, then pick only the valid points and fix and commit them. Handles comments from all reviewers (bots and humans). Activates on requests such as "apply the code review", "handle the review comments", "apply the PR review", "apply PR review comments", "handle review feedback", "autofix", "/autofix". Rather than applying review comments as-is, it applies only those judged valid in verification, either with user approval (default) or automatically (`--auto`).
Task tracking system for agents via Backlog.md CLI. Use when creating deferred issues during implementation, filing audit findings, working assigned tasks, or managing project work. Optimized for agent workflows: structured issue filing, priority/labeling system, and task completion tracking.
Use when designing or auditing high-standard video-game accessibility in Bevy 0.20, integrating screen readers and focus navigation, supporting adaptive controllers and complete remapping, implementing captions or audio description, checking contrast and motion safety, or building disabled-player test evidence.
MANDATORY — invoke this skill BEFORE making any Blockscout MCP tool calls or writing any blockchain data scripts, even when the Blockscout MCP server is already configured. Provides architectural rules, execution-strategy decisions, MCP REST API conventions for scripts, endpoint reference files, response transformation requirements, and output conventions that are not available from MCP tool descriptions alone. Use when the user asks about on-chain data, blockchain analysis, wallet balances, token transfers, contract interactions, on-chain metrics, wants to use the Blockscout API, or needs to build software that retrieves blockchain data via Blockscout. Covers all EVM chains.
Design Bolna graph agents: node-based voice flows with LLM, expression, unconditional and event edges, static low-latency nodes, silence repeat with escalation, per-node RAG, function tools, and real-time event injection via REST. Use when a single prompt is too fragile for a multi-step voice workflow — appointment booking, lead qualification, collections, IVR with LLM fallback, payment confirmation, or any flow with branches, compliance checkpoints, or external events.
Use when writing Python application code that connects to a data source through a CData driver — after the connection and SQL have been validated with the cdata-cli discovery skill. Covers mapping the language to the CData Python Connector edition, downloading the connector wheel from CData's Python repository, activating its license, and connecting via DB-API 2.0 (cdata.<source>.connect). This is the Python build-phase companion to cdata-cli; invoke it whenever the target application language is Python (Salesforce, Snowflake, Jira, Gmail, etc.).
Use when reviewing a set of changes before they merge — a PR, a branch diff, or the working-tree changes you just made — in a Repowise-indexed codebase (.repowise/ directory exists). Activates for "review this PR", "is this safe to merge", "what's the blast radius of these changes", "did I miss anything", or "what else should change with this".
Use when the user asks to "optimize CLAUDE.md", "create a new skill", "write a custom agent", "configure hooks", "manage context window", "set up MCP servers", "scaffold a skill package", "analyze token budget", "create subagents", "configure permissions", "set up worktrees", or "integrate Claude Code with editors". Covers Claude Code CLI mastery, skill authoring, context engineering, hooks automation, subagent creation, and development workflow optimization.
Use when running a CloudCannon site locally with `cloudcannon dev` — starting the local editing loop so the user can edit in the CloudCannon editor and see the site rebuild, choosing the build command per SSG, and reading the `/__api` surface the server exposes
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.