Skills
96,981 packaged capabilities and playbooks for agents. Install any of them with one command.
Productivity
Score, compare, and prioritize product, growth, design, monetization, marketplace, operations, platform, and support opportunities. Use when deciding what to build next, ranking roadmap bets, comparing market opportunities, prioritizing experiments, or balancing impact, confidence, effort, risk, revenue, strategic fit, urgency, and learning value.
Use when analyzing failures, outages, incidents, or negative outcomes, conducting blameless postmortems, documenting root causes with 5 Whys or fishbone diagrams, identifying corrective actions with owners and timelines, learning from near-misses, establishing prevention strategies, or when user mentions postmortem, incident review, failure analysis, RCA, lessons learned, or after-action review.
Document any business process in a clear, structured format. Use when asked to document a process, write a process guide, create a workflow document, or map out how something works. Produces a complete process document with steps, roles, inputs, outputs, and edge cases.
Researches products, prices, sellers, and reviews across major online marketplaces and big-box/specialty retailers (Amazon, eBay, Shopify stores, Shop.app, Target, Costco, Walmart, Nike, Zara, Adidas, Best Buy, Home Depot, Sephora, SHEIN, IKEA, Chewy, and more) using the Crawlora API, returning clean JSON. Use when the user asks to find a product, compare prices or sellers, track listings, or pull marketplace/retailer reviews — instead of scraping store pages
When the user wants to do a quarterly review, reflect on the past quarter, plan the next quarter, reset strategic priorities, or says things like 'quarterly review,' 'end of quarter,' 'Q1/Q2/Q3/Q4 review,' 'quarterly planning,' 'what should we focus on next quarter,' 'strategic reset.' The 90-minute big sibling of weekly-review.
Meta-gateway for experience feedback. Collects from three sources (session reviews/article scans/manual input) → distills and anonymizes → categorizes → handles in three ways (publish an issue/store locally/do not store). Trigger terms: feedback experience, save experience, submit experience, experience review, capture lessons, lessons learned
Summarises the delta between a tool's latest release and the last summary the user saw. Use when the user asks about what's new, the latest release, release notes, or the changelog of one of the supported tools: Claude Code, OpenCode, llama-swap, or llama.cpp.
Append new items (research objects) to an in-progress research outline's `outline.yaml` — sourced from your direct input, a web-search agent, or both. Use mid-`/research-outline` when you've realised the items list is incomplete (a new competitor surfaced, an important historical entry was missed, a category needs broader coverage) before running `/research-deep`, so the new items are part of the parallel deep pass instead of needing a separate run.
Brainstorm and stress-test research ideas as a senior scholar colleague would. Runs a multi-turn dialogue that clarifies the seed question (or generates one from cold start), probes it conversationally, launches a parallel deep literature scan across published and working-paper sources, critiques the question adversarially, generates 2–3 alternative framings, assesses feasibility (delegating to the find-data skill when available), and writes a research brief to the working directory. Trigger when the user asks to brainstorm a research idea, stress-test a research question, workshop a project, develop a new paper idea, assess novelty of a question, evaluate whether an idea is worth pursuing, refine a research direction, or check whether an idea clears a top-journal bar. Also trigger on phrases like "brainstorm with me", "is this novel", "has anyone done this", "what should I work on", "help me think through this idea", "workshop this question", "stress-test this", "poke holes in this", "new research idea", "research project idea", or when the user describes a half-formed question and asks for feedback. Use regardless of field but tuned for empirical economics and adjacent social sciences.
Guide users to build Zaps that use the official ScraperAPI Zapier integration. Use this skill whenever the user wants to add web scraping, SERP data, or e-commerce data to a Zapier workflow through ScraperAPI — even when they don't say "skill" or name the integration. Triggers include: "build a Zap that scrapes Amazon prices and emails me", "connect ScraperAPI to Zapier", "automate a daily Google search scrape in Zapier", "use ScraperAPI in a Zap to enrich new leads from a webhook", "how do I add ScraperAPI as a step in my Zap", "Zapier workflow to crawl a site with ScraperAPI", "extract data from a URL inside Zapier". Produces a step-by-step build guide for the Zap editor, since Zapier integrations are assembled in the web UI (not imported as JSON). Note: Transmits user-supplied URLs, queries, and page content to ScraperAPI.
Explain the current topic, a status, or a concept as one designed diagram made with the diagram-design skill. Use when the user asks to see it as a diagram or with diagram-design. For a quick view in plain text, use show-me; for a report or decision page to read later, use show-me-artifact.
Interact with Slack via the Web API. Read, summarize, search, post messages, react, pin, and manage channels. Use when the user (1) shares a Slack URL, (2) asks to read or summarize a channel, (3) searches Slack messages, (4) asks to send/post a message, (5) asks to react to or pin a message, (6) looks up a user, or (7) mentions a Slack channel by name (e.g., "#channel-name"). Also triggers for Slack threads, daily standups, conversation digests, or any Slack interaction.
Use when "extract ideas from YouTube", "index YouTube video", "find startup ideas in video", "analyze YouTube for ideas", "what ideas are in this video", or mining video content for business opportunities. Do NOT use for general YouTube watching or content creation (/content-gen).
This skill should be used when generating lesson summaries for educational content. It extracts key concepts, mental models, patterns, and common mistakes from lesson markdown files using a Socratic extraction process. Use this skill when a lesson file needs a `.summary.md` companion file, or when reviewing/refreshing existing summaries.
Convert an informal mathematical idea into a precise theorem, lemma, or proof scaffold with explicit assumptions, dependency structure, and clearly marked gaps. Use when developing a new proof, formalizing intuition, planning a theorem structure, or evaluating whether an argument is actually complete.
Create a structured vendor evaluation framework for any procurement decision. Use when asked to evaluate vendors, compare suppliers, run an RFP scoring process, or assess a software or service provider. Produces a weighted scorecard, evaluation criteria, and recommendation framework.
Fetch article bodies from a single article URL or an article index/archive page and save them to local Markdown. Must be used first when the user mentions "save article", "save webpage", "batch fetch articles from a page", "pull the first N articles from this archive page", or "save to Obsidian / Clippings / local". Especially suited to public webpages, Substack, blog article pages, and article archive pages. When facing lazy-loaded lists, dynamic pages, or incomplete static fetching, first use browser to collect article URLs, then call the script to save them in batch, prioritizing success rate.
When the user wants to do a weekly review, check in on business progress, reflect on the week, plan next week's priorities, or says things like 'weekly review,' 'how did this week go,' 'what should I focus on next week,' 'end of week check-in,' 'Sunday review,' 'weekly retro.' A structured CEO operating rhythm in 15 minutes.
Chat with a wisdom mentor — 28 mentors from many fields (philosophy, business, spirituality, science, art). 2 modes: 1:1 (deep dialogue with one mentor) or 1:N (roundtable of 2-4 mentors who challenge and complement each other). Mentors fully role-play: they speak in first person, using their own worldview and characteristic vocabulary. Use when the user wants to ask a thinker's opinion, chat with a mentor, get advice from a philosophical/business/spiritual perspective, or says "hỏi Naval", "nói chuyện với Krishnamurti", "bàn tròn", "roundtable", "wisdom mentor", "người thầy", "muốn nghe góc nhìn của...", "nếu là X thì X nghĩ sao", "tư vấn như một...", "mentor nào phù hợp". Also use when the user needs multiple perspectives on a deep issue, or wants Socratic dialogue.
ES — Harshly critiques an idea, plan, pitch or whole project without validating or flattering: assumes it will fail and proves it across eight angles (premises, market, competition, viability, numbers, execution, pre-mortem and blind spot), researches real failures when tools are available, and returns a blunt verdict with a prioritized list of what to fix. Activate with /abogado-del-diablo, "hazme pedazos esto", "critica mi idea sin filtros", "dime por qué va a fallar", "destruye este plan", "segunda opinión brutal", "pre-mortem". EN — Harshly critiques an idea, plan, pitch, or whole project without validating; assumes it will fail and proves it across eight angles, then returns a blunt verdict with a prioritized fix list. Trigger on "devil's advocate", "red team this", "tear this apart", "why will this fail", "brutal second opinion", "pre-mortem".
Multi-perspective academic paper review with dynamic reviewer personas. Simulates 5 independent reviewers (EIC + 3 peer reviewers + Devil's Advocate) with field-specific expertise. Supports full review, re-review (verification), quick assessment, methodology focus, Socratic guided, and calibration modes. Triggers on: review paper, peer review, manuscript review, referee report, review my paper, critique paper, simulate review, editorial review, calibrate reviewer, reviewer calibration, measure reviewer accuracy.
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 9-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.
Academic research assistant for literature reviews, paper analysis, and scholarly writing. Use when: reviewing academic papers, conducting literature reviews, writing research summaries, analyzing methodologies, formatting citations, or when the user mentions academic research, scholarly writing, papers, or scientific literature.
Use this skill for any explicit wiki mutation in ai-memory: saving durable or time-bounded project knowledge, recording a rule or annotation, updating a note, or deleting a memory page. Trigger by semantic intent rather than exact wording; routine session capture is not a durable-page request.
Use this skill for any ai-memory knowledge-base maintenance request: consolidating observations, reviewing session lessons, proposing durable learnings, auditing or linting the wiki, finding contradictions, pruning stale memory, or running auto-improvement. Trigger by semantic intent rather than exact wording.
Use this skill for any request whose goal is read-only retrieval from ai-memory: project history, prior context, decisions, rules, gotchas, recent activity, full wiki pages, or status/briefing. Trigger by semantic intent rather than exact wording, including when ai-memory is not named.
This skill should be used when the user asks about "pre-production", "shot list", "storyboard", "shooting schedule", "call sheet", "script breakdown", "scene breakdown", "production planning", "act as a pre-production planner", "pre-production mode", "location scouting", "crew planning", "shooting day schedule", "camera setup list", or needs expertise in pre-production planning, shot design, script breakdowns, and shooting logistics. Part of the AlterLab FC Skills collection (Cinema & Digital Media department).
Compiles any research input — PDF papers, GitHub repositories, experiment logs, code directories, or raw notes — into a complete Agent-Native Research Artifact (ARA) with cognitive layer (claims, concepts, heuristics), physical layer (configs, code stubs), exploration graph, and grounded evidence. Use when ingesting a paper or codebase into a structured, machine-executable knowledge package, building an ARA from scratch, or converting research outputs into a falsifiable, agent-traversable form.
Answer questions from the perspective of Marcus Aurelius — Stoic philosophy, Meditations, self-discipline, and inner tranquility. Use when the user explicitly asks for this figure's perspective, mentions "aurelius-perspective", or wants to apply his core methods to analyze a problem; do not trigger automatically for general questions.
Observe the user's screen via screenpipe, detect repeated research workflows, match them against existing research-agent-skills, and draft new skills (or composition recipes that chain existing ones) for the patterns not yet covered. Use when the user asks to analyze their recent work and propose skills based on what they actually do. Requires the screenpipe daemon (https://github.com/screenpipe/screenpipe) running locally on port 3030 — the skill has no other data source and will refuse to run if screenpipe is unreachable. All detection runs locally; only redacted cluster summaries reach the LLM.
Use when the user has only a broad research area and no seed paper, and wants to understand the field, find an entry point, identify papers to read, or organize research ideas before drafting a proposal. Do not use when they already have a specific paper and want to expand through its citation relationships.
X/Twitter CLI tool for reading tweets, threads, replies, searching, managing bookmarks, and fetching news/trending topics. Use when the user needs to read tweets, search X/Twitter content, get user timelines, fetch bookmarks, or retrieve trending news from the command line. Supports cookie-based authentication from Safari or Chrome.
Books time-based services via USP from a Link wallet. Use when the user wants to book, schedule, reserve, or pay for a service from a business (haircut, lesson, repair, class, appointment, consult). The `booking-agent` CLI owns the booking state machine and refuses to proceed when human gates are skipped. Sign the user in to Link on your own, right after install and at the start of every booking (`booking-agent flow link-auth connect`, then start `booking-agent flow link-auth poll` in the background and post the sign-in URL in the same turn, exactly like `pay poll`); never wait for the user to ask to sign in or to say they approved. After `booking-agent flow business use`, follow `next_command` through `use-ucp-checkout-mode`; businesses without native checkout fail closed. Payment uses `booking-agent flow pay request` (default returns immediately with the approval URL), then start `booking-agent flow pay poll` in the background and post the approval URL to the user in the same turn; the poll finishes checkout once they approve. Confirm through `booking-agent flow book poll --wait`; never start an inbound webhook. Surface the approval URL exactly once. Personal identification (name, phone, email, address) must always come from the user's Link account via `link-cli`, never from chat or placeholders. Before any location-based search, the CLI proposes the Link shipping address and the user confirms it or gives another; online services skip this. Talk to the user in plain everyday language only; never expose CLI, UCP, auth, session, or other implementation details unless they explicitly ask.
Browse Bluesky content via API and firehose - search posts, fetch user activity, sample trending topics, read feeds and lists, analyze and categorize accounts. Supports authenticated access for personalized feeds. Use for Bluesky research, user monitoring, trend analysis, feed reading, firehose sampling, account categorization.
Fact-check claims and prove completed implementation against direct evidence. Use when claims need validation, cross-examination, or hardening, or completed work needs decisive command proof. Do not use as the owner of broad risk discovery, requirement conformance, or one-sided advocacy.
Vision-driven browser automation using Midscene Bridge mode. Operates entirely from screenshots — no DOM or accessibility labels required. Can interact with all visible elements on screen regardless of technology stack. This mode connects to the user's desktop Chrome browser via the Midscene Chrome Extension, preserving cookies, sessions, and login state. Use this skill when the user wants to: - Browse, navigate, or open web pages in the user's own Chrome browser - Interact with pages that require login sessions, cookies, or existing browser state - Scrape, extract, or collect data from websites using the user's real browser - Fill out forms, click buttons, or interact with web elements - Verify, validate, or test frontend UI behavior - Take screenshots of web pages - Automate multi-step web workflows - Check website content or appearance Powered by Midscene.js (https://midscenejs.com)
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.