Skills
99,719 packaged capabilities and playbooks for agents. Install any of them with one command.
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Forensically preserve memory and disk, collect ransom notes and encrypted file samples, and identify the ransomware variant using tools such as ID Ransomware, Volatility, and Chainsaw/Hayabusa to determine the initial access vector and recovery options. Use immediately after discovering ransomware encryption, when scoping the incident forensically, or when documenting evidence for law enforcement and insurance claims.
Select and use companion engineering tools; install, update, reconcile, configure, verify, or remove tools, installed skills, host instructions, and native agent declarations. Use for non-obvious capability selection, source retrieval or measurement semantics, and environment readiness; exclude routine reads, skill authoring, engineering verdicts, and implementation.
Activates when the user asks to write, draft, translate, or revise Italian texts for public, editorial, blog, social media, newsletter, marketing, fiction, nonfiction, or informational use. It also activates when the user asks to humanize Italian texts, remove AI patterns, correct chatbot-like wording, capture or calibrate an author's voice based on a corpus of their texts, respond to an automatic detector that flagged human-written text as generated, or revise Italian text generated by language models.
Full lifecycle management of JeecgBoot Online forms (cgform) — automatically create/edit database tables and form configurations via API, supporting single tables, master-detail tables, tree tables, 26 control types, plus JS/Java/SQL enhancements, permission configuration, data CRUD, and Jimu report integration. Use this skill whenever the user's intent involves "Online forms", including but not limited to: creating or configuring database tables ("create a leave request table", "create an online table", "make a table with a dropdown", "low-code form", "online form", "configure a table"); modifying existing Online table fields ("add a field", "change a field type", "add a subtable", "delete a field"); configuring form enhancements ("JS enhancement", "custom button", "form linkage", "Java enhancement", "SQL enhancement"); configuring permissions ("field permission", "button permission", "data permission", "grant to role"); managing form data ("insert data", "query records", "export CSV", "generate test data"); and linking Jimu reports ("add a report to this table", "integrated printing"). Even if the user only describes business requirements without saying "online" (e.g. "build an employee information management feature with name, department dropdown, and hire date"), as long as it involves metadata-driven form configuration, this skill should be triggered. Note: do not confuse with the "designer form" (desform) — desform is a drag-and-drop form designer handled by the jeecg-desform skill; do not confuse with "Online report" (cgreport) or "Online chart" (onlchart) either — they are SQL-driven read-only displays.
Create or migrate to a justfile (casey/just command runner) for any project. Use this skill when the user asks to add a justfile, replace a Makefile, set up project commands, create task runners, or mentions "just" in the context of build/dev workflows. Also trigger when you see a project with a Makefile that would benefit from just's simpler syntax, or when setting up a new project that needs common dev commands (build, test, lint, fmt). Covers Rust, Python, TypeScript/JavaScript, Go, and Ruby ecosystems. Do NOT use for CI pipeline configuration, Dockerfiles, or actual build system setup (cargo, webpack, etc.).
Review Kafka Connect connector configurations for common misconfigurations using the Lenses MCP server. Checks error handling, DLQ setup, converters, transforms, task count and task health. Use when user says "review connectors", "check connector configs", "why is my connector failing" or asks about Kafka Connect configuration. Do NOT use for creating, deploying or controlling connectors.
Web crawling and URL discovery with katana. Use when you need to crawl all pages and endpoints of a target site, discover hidden API paths, endpoints in JavaScript, or extract forms. katana is a next-generation crawling framework from ProjectDiscovery that supports standard mode and headless browser mode and can parse JavaScript to discover dynamic endpoints. This skill should be used for any scenario involving web crawling, URL discovery, JS endpoint extraction, form discovery, or sitemaps
Multi-step KEGG bioinformatics workflows — pathway enrichment from gene lists, drug-target investigation, cross-species metabolic comparison, and compound-reaction network exploration. Guides Claude through the full analytical pipeline using KEGG MCP tools.
Build a prioritized keyword cluster map using the 6 Circles Method — keywords at the intersection of positioning alignment, customer language, competitor blind spots, workable search volume, real expertise, and business intent. Use when the user asks 'what keywords should I target', 'what should I write about', 'find SEO opportunities', 'plan my content strategy', 'what does my audience search for', or before any SEO content is written. Produces a Keyword Map: scored keywords grouped into topic clusters, each cluster mapped to the article that should target it, ready to hand to content production.
KODIAK v7.0.0 — SOL alpha hunter, senpi_runtime_helpers migration. Plumbing-only flip from openclaw-CLI subprocess + mcporter subprocess to in-process SenpiClient (direct HTTPS for MCP, direct HTTP POST to runtime /signals, long-lived producer_daemon). Thesis preserved verbatim from v6.0.1: SOL alpha hunter, single-asset focus, v5.1 base-tech-score floor with multi-factor scoring (SM consensus, trend structure, momentum, funding, OI, BTC correlation, RSI), conviction-tiered leverage (5x default, 6x conviction at score 11+, 7x apex at score 13+), 240-min asset cooldown.
Write high-converting landing page copy using proven frameworks like PAS (Problem-Agitate-Solution), AIDA, and StoryBrand. Creates headlines, value propositions, CTAs, and full page sections optimized for conversion. Use when users need landing page copy, sales page content, or marketing website text.
Invoke this skill when you need human-in-the-loop approval, custom middleware, or structured output. Covers HumanInTheLoopMiddleware for human approval of dangerous tool calls, creating custom middleware with hooks, Command resume patterns, and structured output with Pydantic/Zod.
Builds, reviews, debugs, migrates, secures, tests, and implements Filament 5.x using the project's installed version and official components before custom Blade or CSS. Use for Filament resources, schemas, infolists, forms, tables, actions, widgets, relation managers, panels, tenancy, imports/exports, plugins, APIs, namespaces, Artisan commands, upgrades, and security reviews. Do not trigger for visual-only polish, layout or composition decisions, theme-preserving UI presentation work, or an isolated mention of admin panel, dashboard, or badge without another Filament signal.
When the user wants to plan a product launch, feature announcement, or release strategy. Also use when the user mentions 'launch,' 'Product Hunt,' 'feature release,' 'announcement,' 'go-to-market,' 'beta launch,' 'early access,' 'waitlist,' or 'product update.' This skill covers phased launches, channel strategy, and ongoing launch momentum.
Read and explain the actual communication history for one Nexor lead across phone-call transcripts, email bodies and delivery events, SMS, and WhatsApp. Use when someone asks what was said, sent, received, promised, answered, or left unanswered for a specific lead, or asks for a chronological lead conversation summary grounded in Nexor MCP data.
Provider-neutral deep-research orchestration for brainstorming, technology choices, comparisons, and state-of-the-art surveys. The Research Lead makes scope and decision calls while native subagents scout, search, verify, synthesize, audit, write, and commit every research artifact.
Build and maintain a data inventory (mapa de dados) of all personal data processing activities in the project. Use when the user asks “mapa de dados,” “data mapping LGPD,” “que dados pessoais coletamos,” or “inventário de tratamento,” or as part of an LGPD audit pipeline. Produces `.lgpd/data-map.md`. Especially important for legacy systems where the inventory is reverse-engineered from code (Prisma schemas, API endpoints, third-party SDKs, log statements)
Light research mainline step 2 · data engineering: **findable and affordable data** (source/license/version/size/split) + **judge data feasibility before proposing an idea** (is the data enough to support the research/statistical power) + **prevent data leakage** (a frequent rejection landmine at top conferences.) When to use: the user wants to find/choose/download public datasets, or has data and asks "can I do research with this/is it enough/is the quality OK" / needs cleaning, handling missing values and outliers, feature engineering, dataset splitting, data augmentation / building a dataset (collection, annotation guidelines, privacy compliance, release) / suspects train-test contamination (leakage) / wants to assess the data basis before proposing an idea. Trigger words: is the data enough / data feasibility / data quality / data leakage / preventing leakage / train-test overlap / how to split / cross-validation / annotation guidelines / inter-annotator agreement IAA / building a dataset / is the sample size enough / statistical power / find a dataset / data license / dataset search / data leakage / feasibility / data split / annotation. Core discipline: **data leakage = critical, an outright veto** (standardization before splitting / temporal leakage / entity overlap / target-encoding leakage); **data insufficient to support the idea = block before the idea (back edge 2⊣3, get more data/change the idea)**; power is an empirical threshold, not a power analysis; leakage detection is heuristic and bounded — do not claim "everything was checked".
Build and maintain software architecture as code with LikeC4 DSL. Use when tasks mention architecture diagrams, C4/context/container/component views, system landscape, dependency/integration maps, or when the user wants architecture generated/evolved from code. Apply for creating new `.c4`/`.likec4` models, updating existing models, validating with LikeC4 CLI, and preparing preview/build/export outputs.
Logseq Datascript schema, built-in properties/classes, and :db/ident discovery for composing or reviewing Datascript queries about blocks/pages/tags/properties/classes. Use whenever editing or reviewing Datascript pull selectors or queries, or any code that adds/removes attributes in pull patterns, or touches property namespaces/identifiers, or requires reasoning about property value shapes/ref/cardinality in Logseq.
Use when the user wants to query Lore git trailers from commit history — surface constraints, rejected alternatives, directives, test gaps, and other decision context. Triggers on "최근 제약조건 확인", "리젝된 대안 보여줘", "check recent constraints", "show directives", or explicit skill invocation (/lore-query in Claude Code, $lore-query in Codex CLI, /skill:lore-query in Kimi Code, lore-query in Qwen Code).
CRITICAL: Use for Makepad 2.0 app structure and Rust integration. Triggers on: makepad app, makepad getting started, app_main!, App::run, MatchEvent, AppMain, handle_event, handle_actions, ScriptVm, from_script_mod, makepad boilerplate, makepad new project, makepad cargo, Cargo.toml setup, hot reload, --hot, live reload, wasm deploy, cargo makepad, media plugin, audio_output, audio_input, AudioBuffer, cx.audio, makepad audio, 音频, 应用结构, 入门, 新项目, 脚手架, 启动, 热重载, 部署
CRITICAL: Use for Makepad 2.0 troubleshooting and common mistakes. Triggers on: makepad error, makepad bug, makepad problem, makepad issue, makepad not working, text invisible, widget not showing, click not working, height zero, makepad pitfall, makepad gotcha, makepad FAQ, makepad help, script_mod error, compile error, widget not found, render not updating, hot reload not working, wasm build error, port conflict, server lock, IME popup, selection handle, popup window crash, canvas splash, POST splash loop, 100% CPU, set_visible not working, on_render empty, event bridge unreliable, float time display, fn tick not called, on_audio not called, button click through, 常见错误, 问题排查, 故障排除, 不显示, 不工作, 看不见, 热重载, 编译错误
CRITICAL: Use for Makepad 2.0 widget catalog and usage. Triggers on: makepad widget, makepad View, makepad Button, makepad Label, makepad TextInput, makepad PortalList, makepad Dock, makepad Modal, makepad Image, makepad CheckBox, makepad Slider, makepad DropDown, widget catalog, widget reference, widget list, SolidView, RoundedView, ScrollYView, FoldHeader, Splitter, FileTree, 组件, 控件, 视图, 按钮, 标签, 输入框, 列表, 模态框
Mall skill: recognizes shopping/buying/product-selection intent, displays the product catalog, guides the user to choose products and quantities, and after summarizing the order calls the payment skill to complete payment. TRIGGER when: the user says "买东西", "购物", "我想买", "有什么可以买", "看看商品", "买手机", "买水果", "买菜", "逛商场", "下单", "选购", etc., indicating shopping-related intent. DO NOT TRIGGER when: the user only says "支付", "付款", "打赏", etc., without any intent to select products.
Manual for the marginaleffects R and Python package, and guide to the book "Model to Meaning". Use when users ask about predictions, comparisons, slopes, marginal effects, average treatment effects (ATE/ATT/CATE), hypothesis testing, contrasts, counterfactuals, risk ratios, odds ratios, causal inference with G-computation, or need help with marginaleffects functions like predictions(), comparisons(), slopes(), hypotheses(), datagrid(), avg_predictions(), avg_comparisons(), avg_slopes(), or plot functions.
Build, refactor, audit, and validate marketing websites and public product pages. Use this skill whenever the user asks for landing pages, product pages, brand pages, venue pages, campaign pages, conversion flows, hero sections, CTA hierarchy, social proof, metadata, responsive storytelling, media-heavy public pages, SEO-facing UI, or launch pages. Do not use for private dashboards, admin panels, CRM screens, or dense app workflows.
Complete usage guide for the MarkItDown command-line tool (`markitdown` command), covering all CLI options (`-o/-x/-m/-c/-d/-e/-p/--use-cu/--cu-endpoint/--cu-analyzer/--cu-file-types/--list-plugins/--keep-data-uris`), input and output modes (files/pipes/stdin), pipeline composition, integration with shell toolchains (jq/grep/xargs/tee/find), and typical examples (batch conversion, Azure backend switching, enabling plugins, streaming input). Use this skill when users ask how to use the markitdown command, how to batch-convert to PDF, how to pipe in stdin, how to list installed plugins, or how to configure Azure Document Intelligence CLI. For OCR via LLM Vision, use the sibling skill `markitdown-ocr`.
Guides LLMs to use LLM Vision via the `markitdown-ocr` plugin (official plugin repository: microsoft/markitdown/packages/markitdown-ocr) to extract OCR text from embedded images and scanned pages in PDF / DOCX / PPTX / XLSX files, using OpenAI-compatible models such as gpt-4o, Azure OpenAI, Gemini, and other OpenAI-compatible services. Covers installation, configuration (`OPENAI_API_KEY` / Azure credentials / custom endpoint), Python API and CLI wrappers, full-page rendering fallback for scanned PDFs, OCR behavior differences by format (inline insertion / append after tables / top-level descriptions), custom prompts, and troubleshooting costs and limits. Use this skill when users ask how to convert a scanned PDF to markdown, extract text from images in a PPT, use GPT-4o for OCR, install the `markitdown-ocr` plugin, or configure markitdown with Azure OpenAI. For ordinary CLI usage or a MarkItDown overview, use the sibling skills `markitdown-cli` and `markitdown-awesome`
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.