Skills
98,067 packaged capabilities and playbooks for agents. Install any of them with one command.
Development
Build comprehensive ARCHITECTURE.md files following matklad's canonical guidelines — bird's-eye views, ASCII/Mermaid diagrams, codemaps, invariants, and layer boundaries. Triggers on document the architecture, create ARCHITECTURE.md, map this codebase, architectural overview.
Help users discover Jev apps, tools, and examples, with clear source-access and paid-product disclosures. Use for Jev solution discovery, app recommendations, starter-kit selection, API-key setup, or adapting/building a Jev workflow in the user's stack.
This skill helps an LLM generate correct core AxAgent code using @ax-llm/ax. Use when the user asks about agent(), child agents, namespaced functions, discovery mode, clarification, bubbleErrors, host-side final/clarification protocol, or ordinary agent runtime behavior. For MCP clients, native runtime modules, subscriptions, tasks, or authentication use ax-mcp alongside this skill. For RLM/code-runtime work use ax-agent-rlm; for callbacks and telemetry use ax-agent-observability; for recall/memory/skill loading use ax-agent-memory-skills; for agent.optimize(...) use ax-agent-optimize.
This skill helps an LLM generate correct AxAgent observability code using @ax-llm/ax. Use when the user asks about axGlobals.onUsage, usageContext, centralized or multi-tenant usage accounting, actorTurnCallback, onContextEvent, agentStatusCallback, onFunctionCall, reportSuccess, reportFailure, getChatLog(), getUsage(), resetUsage(), debug traces, progress updates, or telemetry for AxAgent runs.
This skill helps an LLM generate correct AxAgent RLM/runtime code using @ax-llm/ax. Use when the user asks about RLM code execution, AxJSRuntime, contextFields, contextPolicy, liveRuntimeState, promptLevel, stage prompt controls, executorModelPolicy, maxRuntimeChars, agent.test(...), llmQuery(...), recursionOptions, or long-running agent runtime behavior.
This skill helps an LLM generate correct AI provider setup and configuration code using @ax-llm/ax. Use when the user asks about ai(), providers, models, routing, adaptive balancing, presets, embeddings, batch audio with ai.transcribe() or ai.speak(), extended thinking, context caching, or mentions OpenAI/Anthropic/Google/Azure/DeepSeek/Meta/Mistral/Cohere/Reka/Grok/Typesafe/Jev with @ax-llm/ax.
Set up a Python repository with the Beaker Integration contract, connect real labeled data and application execution, and validate setup. Keep evaluation tooling under .beaker and preserve production behavior. Use beaker-usage for operating an already configured integration.
Decide whether a system needs a backend-for-frontend, how many, and what each one may own: adoption signals and honest costs, one-experience-one-BFF granularity with frontend-team ownership, the shape-don't-decide rule, upstream aggregation with partial-failure and resilience budgets, identity-keyed BFF caching, mediating user identity toward upstream services (token exchange, confused-deputy prevention), and the alternatives (shared gateway, GraphQL federation, token-mediating backend, direct SPA→API, meta-framework server as BFF). Use when adopting or splitting BFFs, aggregating upstream services, handling upstream failures, forwarding user identity downstream, weighing GraphQL against per-client BFFs, or auditing a BFF that has drifted into a public API or a business-logic layer. For protecting the BFF's own entry points use bff-entry-points; for physical route layout use structure-codebase; for externally consumed API contracts use api-design; for OAuth/OIDC protocol flows use secure-oauth-oidc.
Blade template conventions for any Bagisto package or module (Admin, Shop, or any custom Webkul-style package). Activates when creating or editing Blade views, building Blade components (anonymous @props components or Vue-backed x-template components), wiring forms, datagrids, modals, layouts, or slots, or matching the project's markup, attribute-binding, indentation, and formatting style. The conventions are framework-wide; only the per-package namespace tokens differ.
Find what a change could break somewhere else before it ships, beyond the diff, and prove the one fact it's safe because of by running real code instead of writing it up. Use for 'blast radius of X', 'what could this break', or reviewing a small diff you don't trust.
Set up a new app repository for the Boring Factory end to end — create it from the app template (hachej/boring-app), set its secrets and settings, invite the expert, verify the first runs, and hand the expert their next steps. Use when the maintainer asks to create, bootstrap or set up a new app or repository for the Factory, or to connect an existing repository to it.
Explore user intent, requirements and design before implementation through structured dialogue and design proposals. Use when asked to: create features, build components, add functionality, modify behavior, plan projects, or when user says 'help me design X', 'what should we build', 'let's brainstorm', or starts describing a new feature without a design.
General-purpose Git branch management skill. Used to help wangxin/wx create a new feature branch in the current repository, sync develop, commit and push, run pre-MR checks, and clean up branches after merging. By default branches feature/wx-YYYYMMDD-<task> off develop and proactively performs low-risk Git operations; history rewrites, remote deletions, and actions involving production branches require explicit confirmation.
Guidance for converting COBOL programs to modern languages (Python, Java, etc.) while preserving exact behavior and data format compatibility. This skill should be used when modernizing legacy COBOL applications, converting COBOL business logic to modern languages, or ensuring byte-for-byte output compatibility between COBOL and its replacement.
Agent skill for interacting with code.storage, a managed Git infrastructure layer. Provides repository creation, branching, commits, file access, diffs, search, notes, GitHub sync, ephemeral branches, and forking through a RESTful HTTP API authenticated with customer-signed JWTs. Every repo operation scoped per-JWT.
Coding Agent Harness engineering methodology. For teams doing long-horizon project development with Coding Agents (Codex, Claude Code, Gemini CLI, etc.), build a complete harness engineering system on the user's project. Includes: project diagnosis, AGENTS.md + CLAUDE.md entry file generation, coding-agent-harness/ directory setup, Planning Loop, SSoT governance, Delivery Operating Model, Repository Governance, CI/CD, Long-Running Task Protocol, Adversarial Review Report, Review Routing, Worktree parallel development, Regression SSoT and Evidence Depth tiered regression, Walkthrough / Closeout Index closeout, Cadence Ledger, task-local lesson candidates and promoted lesson detail documents, Harness Ledger global context write-back ledger. Use this skill when the user asks to set up a coding agent development process, establish a regression testing system, design AGENTS.md / CLAUDE.md, plan an execution framework for long-horizon agent tasks, sub-agent review loops, adversarial review reports, build a harness, or mentions harness engineering. Also applies to scenarios such as "help me set up a set of agent development standards", "how to keep AI from drifting off on long tasks", "how to do regression testing for agents", "help me initialize the project's harness".
Load PROACTIVELY when task involves designing or building UI components. Use when user says "build a component", "create a form", "add a modal", "design the layout", or "refactor this page". Covers component composition and hierarchy, prop design and typing, render optimization (memo, useMemo, useCallback), compound component patterns, controlled vs uncontrolled forms, file organization, and accessibility for React, Vue, and Svelte.
Refactor high-complexity React components in Langflow frontend. Use when manual complexity assessment shows complexity > 50 or lineCount > 300, when the user asks for code splitting, hook extraction, or complexity reduction; avoid for simple/well-structured components, third-party wrappers, or when the user explicitly wants testing without refactoring.
Use when implementing any substantial feature, multi-file modification, or architectural change - produces a plain-language walkthrough of every alteration so the developer can verify genuine understanding before committing, preventing the accumulation of cognitive debt where code ships faster than comprehension
Use this skill when the user asks to create, modify, debug, validate, or scaffold a MoviePilot local plugin. Covers version-aware V3/V2 plugin development, _PluginBase implementations, package.v3.json/package.v2.json/package.json metadata, plugins.v3/plugins.v2/plugins source layout, PLUGIN_LOCAL_REPO_PATHS local plugin sources, plugin APIs, Vuetify JSON forms/pages/dashboards, Vue module federation remote components, get_render_mode, get_sidebar_nav, plugin sidebar pages, get_agent_pets assistant avatars, commands, services, workflow actions, agent tools, and local install/reload flows. Also use for Chinese requests mentioning 编写插件、本地插件源, 插件开发, V3插件, V2插件, 插件市场, 本地安装插件, 插件热加载, 前端联邦, 侧栏入口, Vue插件页面, 助手形象.
Plans a change as an ADR that records the decision, plus an implementation plan that belongs to it. Use this skill when the user asks to plan a feature or change, or to revise an existing plan or ADR. Do not use for implementing a plan (use implement-plan) or for small changes that involve no real decision.
Scaffold a new Dart or Flutter project from a Very Good CLI template, covering the flutter_app, dart_package, flutter_package, flutter_plugin, dart_cli, flame_game, and docs_site templates, inferring the right one from what the user wants to build and then installing dependencies. Use when the user says "create a new project", "start a new flutter app", "scaffold a package", "create a new package", "initialize a dart cli", "new flame game", or "generate a plugin". Use it for bare, vague, or under-specified scaffolding requests too — "create a new package for me", "make me a new app", "I need a new project", "set one up" — including ones that name no template, no project name, and no organization, or that only hint at what is being built. Missing or ambiguous details are a reason to use this skill, not a reason to skip it: it asks the clarifying questions and picks the template.
Database performance audit — detects N+1 queries, missing indexes, join opportunities, slow queries, EXPLAIN analysis, and per-endpoint DB call counts. Use when asked to "optimize the database", "find slow queries", "check for N+1", "analyze query performance", or "audit DB calls".
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.
