Skills
99,064 packaged capabilities and playbooks for agents. Install any of them with one command.
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Provides comprehensive code review covering 6 focused aspects - architecture & design, code quality, security & dependencies, performance & scalability, testing coverage, and documentation & API design. Use this skill for deep analysis with actionable feedback after significant code changes.
(NS) Senior Tech Lead code review on SOLID, clean code, performance, security, and testability. Use proactively after writing or modifying code, before opening PRs, after implementation closure, or when the user asks for a code review, PR review, or issue review gate — even if they do not name this skill. For GitLab issue execution with ISSUE_URL, use Issue review mode. Do NOT use for root-cause debugging (use code-investigator).
Use this when user wants you to walk through (code or text) files in a EDITOR to either explain how some code works, or to show the user what changes you made, etc. You would typically use this repeatedly to show the user your changes or code files one by one, sometimes with specific line-numbers. This way the user is easily able to follow along in their favorite EDITOR as you point at various files possibly at specific line numbers within those files.
Shared vocabulary for designing deep modules. Use when the user wants to design or improve a module's interface, find deepening opportunities, decide where a seam goes, make code more testable or AI-navigable, or when another skill needs the deep-module vocabulary.
Teaches AI assistants how to develop FlutterFlow apps using MCP tools. Use this skill when working with FlutterFlow projects, editing FF YAML, creating or inspecting pages and components, reading project configuration, or navigating FlutterFlow widget trees. It covers all 25 MCP tools for discovery, reading, editing, and settings. Triggers on: FlutterFlow, FF YAML, FF page, FF component, FF widget, FF theme, FF project.
Expert in running the day-to-day operations of thriving communities. Covers moderation systems, onboarding flows, crisis management, scaling operations, and team management. The engine room that keeps communities healthy and safe. Use when "community operations, community moderation, community management, onboarding flow, crisis management, trust and safety, community team, " mentioned.
Generates business/company names across 10 categories (Descriptive, Metaphoric, Invented, Founder-based, Acronym, Compound, Foreign, Playful, Geographic, Legacy) with USPTO trademark screening, domain availability checking, and 0-100 scoring. Use when users need company/product/brand naming for new business launches, rebranding, trademark strategy, IP protection naming, evaluating current name strength, or any naming/branding tasks requiring systematic analysis with legal clearance.
Deep BD-grade research report on any target company — financials, leadership, hiring, tech stack, competitors, outsourcing exposure, KServe service fit, ICP score, and BD briefing. Triggers on any BD context where a company name is dropped — even without an explicit "research" request. "Look up [company]", "check out [company]", "who should I call at [company]", "what do we know about [company]", "get me a profile on [company]", or simply naming a company while discussing a prospect, outreach plan, or account intelligence. If the context is prospecting, pre-call prep, or finding outsourcing clients — trigger immediately.
Find leads by scraping engagers from a competitor's top LinkedIn posts. Given one or more company page URLs, scrapes recent posts, ranks by engagement, selects the top N, extracts all reactors and commenters, ICP-classifies, and exports CSV. Use when someone wants to "find leads engaging with competitor content" or "scrape people who interact with [company]'s LinkedIn posts".
Enrich contacts with LinkedIn URLs, verified work/personal emails, and phone numbers through the ColdIQ marketplace, layering providers cheapest-first. Use when finding emails for a list, building an email waterfall, verifying deliverability, finding phone numbers, resolving company LinkedIn URLs from domains, or enriching contacts before a campaign. Triggers on "enrich contacts", "find emails", "email waterfall", "verify emails", "bounce check", "find phone numbers", "company LinkedIn URL", "enrich before campaign", "deliverability". Do NOT use for prospecting/search to BUILD a list (see coldiq-search-enrich / apollo-search) or list dedup (see list-dedup).
Break saved articles, Clippings, and long foreign-language pieces into reusable Chinese material fragments, and store them reliably following an existing material library template. Whenever the user mentions "mining gold", "breaking down material", "store into the material library", "break this article into titles/quotes/structure", "batch process Clippings", or "turn English articles into Chinese material assets", prefer this skill instead of doing a plain summary.
Content atomization — turn one piece of content into many formats. Covers blog-to-thread, blog-to-carousel, podcast-to-blog, video-to-quotes, and more. Use for: content marketing, social media, multi-platform distribution, content strategy. Triggers: content repurposing, repurpose content, content atomization, content recycling, one to many content, multi platform content, cross post, adapt content, reformat content, blog to thread, blog to video, podcast to blog, content multiplication
Write git commit messages that follow the Conventional Commits v1.0.0 spec. Use this whenever you are about to author a commit on the user's behalf, prepare or run `git commit`, suggest or clean up a commit message, split a diff into commits, write a PR title/description that references commits, or generate a CHANGELOG from history — even when the user never says "conventional commits". If a commit message is being written in a git repo, this skill applies.
SEO website crawler built on Crawl4AI. Full page audit: title, meta, H1, canonical, breadcrumbs, navigation, internal links. Site inventory, navigation audit, landing page comparison, competitor analysis. Works for Google and Yandex SEO (Cyrillic URLs, commercial factors, regionality). Integrates with yandex-search-api, yandex-metrika, yandex-webmaster, scrapedo-web-scraper. Triggers: crawl4ai, seo crawl, site audit, page inventory, site inventory, on-page audit, internal links, internal linking audit, navigation audit, landing comparison, competitor analysis, competitor pages, orphan pages, technical seo, аудит сайта, краулер, перелинковка, навигационный аудит.
Set up a "software factory" that turns labelled GitHub issues into reviewed pull requests, using coding agents (Claude Code, Codex or any other CLI agent) that run in Upstash Box sandboxes and are started by GitHub Actions. Use this whenever someone wants to build, recreate, extend or debug an issue-to-PR pipeline, a pool of background coding agents, "agents that work on my GitHub issues", a label-triggered agent workflow, or anything that combines Upstash Box with coding agents and GitHub, even if they never say "software factory". Also use it to add a repo, an agent type, workers, a model or effort setting, or a worker image (snapshot) to a factory built this way.
Generate a project-local verification skill that drives your app the way a user does — any language, framework, or platform. Use for /create-verification-skill, "make a control skill for this repo", or when a project has no scripted way to prove UI/CLI/service behavior.
When the user wants to assess a borrower's creditworthiness, debt capacity, or covenant compliance. Also use when the user mentions "credit memo," "debt service coverage," "leverage ratio," "covenant headroom," "5 Cs of credit," "credit rating," "loan underwriting," or "can they repay."
Design and execute customer onboarding that drives activation and retention. Use when building onboarding flows for new users, reducing churn in the first 30 days, improving time-to-value, or creating onboarding sequences (email, in-app, or manual). Covers activation metrics, onboarding step design, friction reduction, and measuring onboarding success. Trigger on "customer onboarding", "onboarding flow", "user onboarding", "reduce early churn", "improve activation", "onboarding sequence", "time to value".
Automates the ingestion of customer requirement documents such as diagrams, BRDs, code etc., synthesizes high-fidelity natural transcripts, and compiles them into highly interactive, responsive Critical User Journey (CUJ) reports.
A flexible library for parallel computing in Python. It scales Python libraries like NumPy, pandas, and scikit-learn to multi-core systems or distributed clusters. Features lazy evaluation and task scheduling for data that exceeds RAM capacity. Use for out-of-core computing, parallel processing, distributed computing, large-scale data analysis, dask.array, dask.dataframe, dask.delayed, dask.bag, task scheduling, lazy evaluation, and scaling beyond memory limits.
[Deprecated] Optional advanced tool for complex data modeling. For simple MySQL table creation, use relational-database-tool directly; for PostgreSQL / CloudBase PG schema work, use postgresql-development. New environments should use PostgreSQL DDL via queryPgDatabase/managePgDatabase—see postgresql-development skill instead
Build virtualized data tables with @virtuoso.dev/data-table. Use this skill when (1) building a data grid with sorting, filtering, or grouped rows, (2) installing the shadcn-styled or headless table, (3) connecting remote/paginated data sources, (4) adding sticky, resizable, reorderable, or hideable columns, (5) persisting table state, (6) controlling a table from outside (scrolling, actions), (7) migrating from TableVirtuoso, or any task involving VirtuosoDataTable, DataTable, DataTableColumn, localModel, remoteModel, or engine refs like scrollToRow$ and dispatchModelAction$.
Data validation patterns including schema validation, input sanitization, output encoding, and type coercion. Use when implementing validate, validation, schema, form validation, API validation, JSON Schema, Zod, Pydantic, Joi, Yup, sanitize, sanitization, XSS prevention, injection prevention, escape, encode, whitelist, constraint checking, invariant validation, data pipeline validation, ML feature validation, or custom validators.
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.
