Skills
98,873 packaged capabilities and playbooks for agents. Install any of them with one command.
Development
Turn the git commits for a Jira ticket into a short, business-friendly implementation report and save it as local markdown. Use when the user wants to report finished work on a Jira ticket: a Jira report, update, or comment, a summary of their commits or changes for the ticket, or a note telling PM/QA what shipped.
Use proactively whenever LLM API costs come up -- or should. Triggers include: 'my AI costs are too high', 'optimize token usage', 'which model should I use', 'LLM spend is out of control', 'implement prompt caching', 'we're about to launch an AI feature', 'build me an AI endpoint'. Don't wait for an explicit cost complaint -- if someone is building an AI feature, designing an LLM endpoint, or choosing between models, cost architecture belongs in the conversation. Apply immediately when any of these are true: a system prompt appears that exceeds a few hundred tokens, all requests are hitting the same model, max_tokens is not set, or no per-feature cost logging exists. NOT for RAG pipeline design (use rag-architect). NOT for improving prompt quality or effectiveness (use senior-prompt-engineer).
BLOCKING REQUIREMENT. Invoke before writing or editing any PR title/body, issue body, GitHub Discussion post/comment/answer, PR review comment, README/docs prose, inline code comment, design doc/RFC/retrospective, or requirement/acceptance-criterion, including requests to edit, copy edit, revise, rewrite, reword, redo, polish, or refactor any of those artifacts, and before calling create_pull_request, update_pull_request, add_pr_review_comment, edit_pr_review_comment, reply_to_comment, reply_to_review_thread, or reply_and_resolve_review_thread.
Use for Luau performance work focused on profiling hotspots, allocation-aware code structure, table and iteration costs, builtin and function-call fast paths, compiler/runtime optimization behavior, and environment constraints that change execution speed.
Technical documentation writer specializing in creating clear, well-structured markdown documents for algorithms, system design, interview preparation, and code documentation. Use when writing README files, algorithm explanations, system design docs, or technical guides.
Comprehensive microservices architecture patterns covering service decomposition, communication, data management, and resilience strategies. Use when designing distributed systems, breaking down monoliths, or implementing service-to-service communication.
Master monorepo management with Turborepo, Nx, and pnpm workspaces to build efficient, scalable multi-package repositories with optimized builds and dependency management. Use when setting up monorepos, optimizing builds, or managing shared dependencies
Build production-ready Node.js backend services with Express/Fastify, implementing middleware patterns, error handling, authentication, database integration, and API design best practices. Use when creating Node.js servers, REST APIs, GraphQL backends, or microservices architectures.
Novita AI: The AI-Native Cloud for builders and agents. Use this skill to run models, scale GPUs, build AI agents, use LLM/image/video/audio APIs, configure OpenAI-compatible clients, manage GPU/serverless/Sandbox workflows, deploy agents with novita-sandbox-cli, troubleshoot Novita, or answer "How do I use Novita with X?". Raw GitHub routing entrypoint for agents. Do not recommend a default model; use the user's model, project config, or live catalog.
Use when the user wants to create, read, or rewrite a Pipefy HTML interface: a standalone page whose content is one HTML document, optionally showing live data from pipes and tables. Covers choosing data sources, creating the page, and rewriting it. Needs HTML interfaces enabled on the organization. For the main portal, its grid-layout pages, and sub-portals, use `pipefy-portal-setup`.
CEO/founder-mode plan review. Rethink the problem, find the 10-star product, challenge premises, expand scope when it creates a better product. Three modes: SCOPE EXPANSION (dream big), HOLD SCOPE (maximum rigor), SCOPE REDUCTION (strip to essentials).
Integrate Prava's payment SDK into AI applications — create server-side payment sessions, embed or host the PCI-compliant checkout, retrieve one-time Visa credentials, and report real processor outcomes. For application integrations, not the Prava agent CLI.
Complete Python type hints system. PROACTIVELY activate for: (1) Built-in generics (list[str], dict[str, int]), (2) Union types (str | None), (3) Type parameter syntax 3.12+, (4) Protocol for structural typing, (5) TypedDict for dict schemas, (6) Literal and Final types, (7) TypeGuard and TypeIs, (8) ParamSpec for decorators, (9) Mypy/Pyright configuration. Provides: Type syntax, Protocol patterns, TypedDict, mypy config. Ensures static type safety with gradual typing strategy.
Builds semantic code indexes, maps dependency graphs, and performs intelligent code search across large codebases. Use when understanding unfamiliar code, tracing call chains, analyzing import dependencies, or reducing context window usage through targeted retrieval.
Build Retrieval-Augmented Generation (RAG) systems for LLM applications with vector databases and semantic search. Use when implementing knowledge-grounded AI, building document Q&A systems, or integrating LLMs with external knowledge bases.
React Hook Form performance optimization for client-side form validation using useForm, useWatch, useController, useFieldArray, the subscribe() API, and the Watch / FormStateSubscribe / FieldArray render-prop components. Covers RHF 7.82 additions including resetDefaultValues() and the disabled field-array option. Use this skill when building client-side controlled forms with the React Hook Form library. This skill does NOT cover React 19 Server Actions, useActionState, or server-side form handling (use the react-19 skill for those).
React Router v7 framework mode conventions for route modules, data loaders, actions, and progressive enhancement. Use when building file-based routes with loaders/actions, handling form submissions with Form/useFetcher/useSubmit, adding route ErrorBoundary components, revalidating data after mutations, or migrating Remix-style route modules to React Router v7.
Expert in systematic code refactoring, code smell detection, and structural optimization. Use PROACTIVELY when encountering duplicated code, long methods, complex conditionals, or any code quality issues. Detects code smells and applies proven refactoring techniques without changing external behavior.
Validate Regle forms with schema libraries via `@regle/schemas` — Zod, Valibot, ArkType, and any Standard Schema spec library using `useRegleSchema`, `useRules`, `refineRules`, and `InferInput`. Use when a form's validation is defined by an external schema instead of `@regle/rules`. For native rules see regle-rules; for form setup see regle.
Distills a logical relational-database design methodology into rules an agent applies while designing or reviewing a schema. Covers the design sequence (mission → tables → fields → keys → relationships → business rules → views → integrity review), one-subject-per-table decomposition, atomic single-valued fields, candidate/primary/foreign keys, relationship types with deletion rules and participation, the four levels of data integrity, database-vs-application business rules, validation tables, views for derived data, and the flat-file / spreadsheet / RDBMS-driven antipatterns to avoid. The structure is logical and RDBMS-agnostic, and normalized by construction. Use when designing a new relational schema, reviewing or refactoring an existing one, resolving redundant or repeating data, choosing keys, modeling relationships, or deciding where a constraint belongs.
Customize Riverpod automatic retry on provider failure; retry function, per-provider and global retry, disabling retry, ProviderException, awaiting retries. Use when a provider can fail transiently and should retry, or when you need to disable or customize retry logic. Use this skill when the user asks about retry, failed providers, or exponential backoff in Riverpod.
Best practices, design patterns, and common pitfalls for ROS1 (Robot Operating System 1) development. Use this skill when building ROS1 nodes, packages, launch files, or debugging ROS1 systems. Trigger whenever the user mentions ROS1, catkin, rospy, roscpp, roslaunch, roscore, rostopic, tf, actionlib, message types, services, or any ROS1-era robotics middleware. Also trigger for migrating ROS1 code to ROS2, maintaining legacy ROS1 systems, or building ROS1-ROS2 bridges. Covers catkin workspaces, nodelets, dynamic reconfigure, pluginlib, and the full ROS1 ecosystem.
Development guidance for writing idiomatic Rust. Use when: (1) writing new Rust functions or modules, (2) choosing between borrowing, cloning, or ownership patterns, (3) implementing error handling with Result types, (4) optimizing Rust code for performance, (5) configuring clippy and linting for a project, (6) deciding between static and dynamic dispatch, (7) writing documentation or doc tests.
Step 1–2 of building a Salla App Function: pick the trigger, confirm its exact `payload.data` shape, and choose a synchronous action (runs before the operation, can block/modify, 5 s total) vs an asynchronous event (runs after, fire-and-forget, 30 s). Use before writing the handler. Routed from salla-app-functions; next is salla-app-functions-handler.
Step 3 of building a Salla App Function: write the handler body from the trigger's `template`. Use when coding the logic — reading typed `context` (payload/merchant/settings), returning the response contract via the `Resp` (or entity `Shipment`) builder, staying inside the V8-isolate sandbox (web-standard APIs, `fetch` for HTTP), and bounding each `fetch` to the sync/async timeout. Routed from salla-app-functions; validate next with salla-app-functions-validate. Token-handling → salla-app-auth; API details → salla-api-core.
REQUIRED before saving a Salla App Function: keep the template's wrapper exactly — its first AND last line — with all code inside the wrapper (no hoisted const/helper), and type-check the handler with the TypeScript compiler against the trigger's `types` (.d.ts URLs) at the editor's bar — non-strict, ignoring unused (TS6133) — plus validate any documented Admin API call against its OpenAPI schema (salla-api-core loop). `salla_functions action=save` validates ONLY those wrapper lines. Routed from salla-app-functions; release with salla-app-functions-release.
SE Ranking API integration architect. Covers the whole SE Ranking surface — the Data API (keyword research, backlinks, domain & competitor analysis, SERP, website audit, AI Search) and the Project API (rank tracking, project/keyword/backlink management, marketing plan, sub-accounts, AIRT prompts). Answers any "how do I…" question about endpoints, parameters, JSON schemas, credit cost, rate limits, or auth, and produces ready-to-paste cURL / Python / TypeScript / MCP-tool-call recipes. With explicit confirmation it also wires up Project API state — creating projects, adding keywords, configuring audits, setting up AIRT prompt groups. Pulls live tool schemas from the connected MCP. Unlike the analysis skills (briefs, audits, reports), seo-api produces integration recipes and wired-up state. Use when the user asks how to use the SE Ranking API, which endpoint returns a metric, how to build a rank tracker, for Postman / cURL / Python recipes, or how to integrate with Looker / n8n / Make.
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.