Skills
96,770 packaged capabilities and playbooks for agents. Install any of them with one command.
Documents
Converts a markdown PR writeup or code review (one with ```diff fenced blocks and severity-tagged GFM callouts [!BLOCKER]/[!MAJOR]/[!MINOR]/[!NIT] callouts) into a single-file 2-column HTML review — unified-diff on the left, severity-tagged annotation cards on the right, top jump-nav listing every finding, mandatory named reviewer footer. Triggers when the markdown-html-orchestrator classifies an input as REVIEW, or when invoked directly via /cs-md-review. Refuses without explicit --reviewer (a code review must name a human), refuses if no diff hunks present (route to md-document instead), and refuses to encode severity in color only (every badge ships color + icon + aria-label per WCAG 1.4.1). Use after orchestrator routing.
Screen incoming NDAs and classify them as GREEN (standard), YELLOW (needs review), or RED (significant issues). Use when a new NDA comes in from sales or business development, when assessing NDA risk level, or when deciding whether an NDA needs full counsel review.
When the user wants to apply NLP to supply chain, extract information from documents, analyze supplier communications, classify items, or process unstructured text. Also use when the user mentions "natural language processing," "NLP," "text mining," "document extraction," "supplier sentiment analysis," "product classification from text," "BERT," "transformers for text," or "chatbots for supply chain." For general ML, see ml-supply-chain.
Use this skill to query your Google NotebookLM notebooks directly from Claude Code for source-grounded, citation-backed answers from Gemini. Browser automation, library management, persistent auth. Drastically reduced hallucinations through document-only responses.
Structured manuscript/grant review with checklist-based evaluation. Use when writing formal peer reviews with specific criteria methodology assessment, statistical validity, reporting standards compliance (CONSORT/STROBE), and constructive feedback. Best for actual review writing, manuscript revision. For evaluating claims/evidence quality use scientific-critical-thinking; for quantitative scoring frameworks use scholar-evaluation.
Reads and writes Zotero libraries from Python with pyzotero 1.13.0 and the Zotero Web API v3: items, collections, tags, attachments, saved searches, full-text content, and BibTeX, CSL-JSON, and bibliography export. Also covers the pyzotero CLI and MCP server for a local Zotero 7. Use when fetching or searching library items programmatically; when creating, updating, or deleting references, collections, or tags; when uploading PDF attachments or downloading files; when exporting citations as BibTeX or CSL-JSON; when building research automation around a Zotero user or group library. Not for formatting citations in a manuscript or verifying references against external databases.
Review vendor agreements, NDAs, or SaaS subscriptions against the review guidelines. Identify the agreement structure from its title, route to the correct review skill, and consolidate the output into a single memo. Use when the user says "review this contract", "check this master agreement", "is this NDA okay", "look at this SaaS agreement", or attaches an inbound agreement for review.
Set up @turbodocx/html-to-docx to convert HTML to Microsoft Word (.docx) documents in a Node.js project. Use this skill when the user wants to generate DOCX files from HTML, add document generation to their app, convert HTML templates to Word documents, or integrate TurboDocx html-to-docx into their project. Also trigger for mentions of HTML-to-Word, HTML-to-DOCX, document generation, report generation from HTML, or any request involving the @turbodocx/html-to-docx package.
Reference: review inbound vendor agreements against the team's review guidelines. Flag deviations, assess risk, generate concrete redline language, and route to the appropriate approver. Loaded when /commercial-legal:review detects a vendor master agreement, services agreement, or similar contract.
Prepare journal manuscripts, conference papers, research posters, and grant documents using venue-specific formatting guidance and bundled LaTeX scaffolds. Use when selecting an official template, checking current page or anonymity rules, adapting academic writing to a venue, or inspecting a submission PDF.
Design and review visual content for developer documentation, including screenshots, architecture diagrams, boxes-and-arrows diagrams, flowcharts, swimlanes, video decisions, accessibility, performance, annotations, and visual maintenance. Use when creating or auditing diagrams, screenshots, visual explanations, or media in technical docs.
Creates product documentation systems with help pages, AI-generated screenshots, Remotion product tours, GSAP animation, narration scripts, TTS, background music, README visuals, and deployment steps. Use when the user asks for product docs, help pages, documentation videos, narrated tours, screenshots, README media, Remotion docs workflows, or webconsulting-style documentation assets.
Prose rules per surface, and the loop that writes, rewrites and reviews prose against them. Use when writing or rewriting docs, code comments, commit messages, tickets, pull request bodies, review comments, skill files or CLAUDE.md, or when reviewing any of them for prose.
This skill should be used when a team wants to create or refine the technical guidelines document — for example "create the tech steering doc", "document our tech stack", "write the technical guidelines", "document our architecture decisions", "set up the tech steering", or "update the tech doc". Generates docs/steering/TECH.md as a living document capturing the stack, architecture patterns, constraints, commands, and ADRs. Generated once and refined — not regenerated from scratch.
Orchestrator for the full academic research pipeline: research -> write -> integrity check -> review -> revise -> re-review -> re-revise -> final integrity check -> finalize. Coordinates deep-research, academic-paper, and academic-paper-reviewer into a seamless 10-stage workflow with mandatory integrity verification, two-stage peer review, and reproducible quality gates. Triggers on: academic pipeline, research to paper, full paper workflow, paper pipeline, end-to-end paper, research-to-publication, complete paper workflow.
Process and generate multimedia content using Google Gemini API. Capabilities include analyze audio files (transcription with timestamps, summarization, speech understanding, music/sound analysis up to 9.5 hours), understand images (captioning, object detection, OCR, visual Q&A, segmentation), process videos (scene detection, Q&A, temporal analysis, YouTube URLs, up to 6 hours), extract from documents (PDF tables, forms, charts, diagrams, multi-page), generate images (text-to-image, editing, composition, refinement). Use when working with audio/video files, analyzing images or screenshots, processing PDF documents, extracting structured data from media, creating images from text prompts, or implementing multimodal AI features. Supports multiple models (Gemini 2.5/2.0) with context windows up to 2M tokens.
This skill should be used when the user asks about "academic writing", "scholarly writing", "journal article", "research paper writing", "IMRAD structure", "literature review writing", "thesis writing", "dissertation writing", "peer review response", "revision letter", "hedging language", "academic vocabulary", "cohesion devices", "argument structure", "paragraph structure", "topic sentences", "signposting", "academic tone", "act as an academic writer", "academic writer mode", "scholarly tone", "writing productivity", "manuscript preparation", "abstract writing", "discussion section", "methods section writing", "APA style writing", "Swales CARS model", "reverse outline", "writer's block", "revision strategy", or needs expertise in academic writing craft, scholarly manuscript development, and publication strategy. Part of the AlterLab FC Skills collection (Research Methods & Academic Writing department).
Design, write, review, and test code samples in developer documentation, including executable examples, explanatory snippets, request and response pairs, placeholders, outputs, language choice, sandboxing, and autogenerated samples. Use when docs include API examples, SDK snippets, CLI commands, config examples, tutorials, or code blocks readers may copy.
Generate a deep, code-first project wiki and VitePress documentation site (DeepWiki-style) for a repository. Use when asked to create a complete wiki/manual for a new codebase, build a code-first documentation site, or generate a `codewiki/` folder with structured Markdown, diagrams, and navigation based on the source code (not existing docs).
Audit, organize, and redesign developer documentation information architecture, including content inventory, navigation, landing pages, sequences, hierarchies, webs, breadcrumbs, sidebars, metadata, redirects, migration, platform/tool selection, and maintainable IA decisions. Use when restructuring docs sites, improving findability, planning doc migration, evaluating docs tooling, or organizing large documentation sets.
Build editable business PPTX decks in an editorial minimalist style — white background, Georgia serif titles, a single red accent bar, and full-height photo section dividers. Exports a real editable .pptx (native text boxes) from HTML slides. Use when the user asks for a business report / pitch deck / PPT / PPTX in this clean editorial or "photo-divider" style, or references this skill.
Financial analysis and research workflows for market research, equity research, comparable companies, precedent transactions, and DCF valuation. Use when asked to build or critique DCF models, comps/precedents tables, competitor or strategy analysis, market sizing, or to deliver analyst-ready outputs in Excel, PowerPoint, or Markdown from CSV/Excel/SQL/API/web data.
Generates a professionally designed case study PDF for B2B SaaS sales and marketing. Supports 7 page layouts, 9 style presets, 1-4 page output. Trigger when user says "create a case study", "write a customer story", "make a case study PDF", "design a success story", "turn this customer win into a PDF".
Run a one-question-at-a-time research grilling session that sharpens AI research terminology, thesis, hypotheses, experiments, and decisions, then preserves the durable parts as project-owned research docs. Use when the user wants to stress-test a research direction, align vocabulary with an agent, clarify a paper or project thread, scope experiments before committing crew time, or preserve research context, especially for projects run through a Nemo firstmate.
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.