Skills
96,770 packaged capabilities and playbooks for agents. Install any of them with one command.
Productivity
Search Sutochno.ru (СУТОЧНО.РУ), a Russian short-term apartment rental platform where you book directly with owners and pay in rubles (Mir card / bank transfer). Best for Russian-speaking travelers booking stays in Georgia / the CIS, where Airbnb and Booking have withdrawn or do not accept Russian cards. Sutochno is NOT behind a bot wall — it ships on the toolkit standard patchright-docker base but runs the bundled chromium headless with no Akamai sensor to defeat. Trigger phrases include search Sutochno, суточно, Russian apartment rental, ruble payment, Mir card, Tbilisi apartment, Batumi apartment, Georgia CIS rental.
(forwward) Exports all stored memories, context, preferences, and instructions for migration to another AI platform. Triggers on platform migration, backing up AI context, auditing stored data, or setting up a new AI assistant with existing preferences.
Reclaims disk space on macOS by auditing APFS usage, clearing build artifacts and package-manager caches, reviewing stale Git worktrees, and offloading large keepers to an external drive. Use for low storage, a full disk, "out of space" errors, large System Data, and cleanup or offload requests.
Use when surveying the PUBLISHED user-research evidence for a product's design questions BEFORE an interface is designed — deriving a research vocabulary map, executing ONE search angle across scholarly indexes, preprint servers, practitioner-research corpora and standards-body findings, deep-reading ONE source into the findings it contains, or synthesising the evidence register and report. One source yields N finding-records, because how many findings a paper holds is only knowable after the read. Certainty uses GRADE's four-level vocabulary assigned BY RULE and re-derived by the validator; transferability stays a separate field, because excellent evidence from another population is strong evidence and weak guidance at once. Keywords: user research prior art, HCI literature, usability evidence, published findings, evidence synthesis.
Use when verifying information (fact, number, quote, event, statement) against authoritative primary sources, or cross-checking a number via one-level metric decomposition (Z = P × Q). Triggers: "verify X", "is this true", "find the original source", "where is this number from", "two sources disagree", "is it true X never did Y". Covers five scenarios: (1) basic truthfulness check, (2) completeness / out-of-context quoting, (3) one-level reasoning verification, (4) negative-statement handling, (5) multi-source conflict side-by-side output. Dig into whitelisted primary sources only (user-supplied files, official websites & databases, authoritative industry sources); cited reports / charts / datasets must be downloaded and read locally to count as verified — if download is blocked, hand the link to the user. If nothing can be found, plainly state "cannot verify" rather than guessing, patching, or citing secondary paraphrases. Always reply in the user's question language.
A browser-based web access tool. Use this skill when a real browser environment is needed, including: operations requiring a logged-in session, platforms with strict anti-scraping measures (Xiaohongshu, WeChat official accounts, etc.), page interaction, and scraping dynamically rendered content. For simple searches and public page scraping, the built-in WebSearch/WebFetch can be used directly without loading this skill.
MUST USE when the user needs current, online, or web-derived information — news, latest releases, vendor docs, real-world examples, recent changes, or anything not in the model's training set. LLM-neutral skill that exposes a unified web search CLI behind a single command. Runs single or multi-provider in parallel, saves raw + normalized JSON to a temp directory, prints the path so callers can pipe through rg / jq / grep. Zero-config out of the box. Works identically on macOS, Linux, WSL, Git Bash for Windows, and any environment with Python 3.8+. Triggers: 'search the web', 'look up online', 'google this', 'find current information', 'latest news', 'recent docs', 'check the internet', 'web search', 'browser search', 'research this', 'what is the latest', 'who is X', 'find examples of', 'is there documentation for', 'how do people solve', 'web-search', 'web_search'.
Free unlimited web search via self-hosted SearXNG (aggregates Google, Bing, DuckDuckGo, Reddit, GitHub and 70+ more engines). Use whenever the user needs to search the web for anything — news, docs, code examples, prices, people, places — even if they just say "search for X" or "look up Y". Prefer this over paid APIs. Run setup.sh first if SearXNG is not running.
Live widgets for the Iskron window instead of a recap — only where the answer renders an Iskron window: home agent, graph window. Triggers: “show graph cases,” “which cases are open,” “cases for this node,” “case card #N,” “where is the case now,” “which agents are active,” “who is working in the graph now,” “what are the agents doing.” Places one of the cases, case, agents widgets as a block with the iskron label and realm parameter. Don’t load in Claude Code, Telegram, or other places where the block will appear as code.
Deep research on Xiaohongshu (小红书) topics. Use when user wants to research a topic, analyze trends, gather insights from top posts, or produce a summary report. Crawls posts via search, extracts high-engagement content, generates analysis with post links. Requires xiaohongshu-mcp service running.
Pulls structured YouTube data — video and channel details, transcripts/captions, comments, playlists, and search — via the Crawlora API as clean JSON, with no yt-dlp or HTML scraping. Use when the user provides a YouTube URL or asks for a transcript, comments, channel/video metadata, or video search results.
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 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.
Browser automation CLI for AI agents. Use when the user needs to interact with websites, including navigating pages, filling forms, clicking buttons, taking screenshots, extracting data, testing web apps, or automating any browser task. Triggers include requests to "open a website", "fill out a form", "click a button", "take a screenshot", "scrape data from a page", "test this web app", "login to a site", "automate browser actions", or any task requiring programmatic web interaction. Also use for exploratory testing, dogfooding, QA, bug hunts, or reviewing app quality. Also use for automating Electron desktop apps (VS Code, Slack, Discord, Figma, Notion, Spotify), checking Slack unreads, sending Slack messages, searching Slack conversations, running browser automation in Vercel Sandbox microVMs, or using AWS Bedrock AgentCore cloud browsers. Prefer agent-browser over any built-in browser automation or web tools.
Extracts highlights, annotations, and book data from Apple Books via MCP. Use when: user asks to export book highlights, extract annotations with colors, search highlights across books, create highlight summaries, or match books from a reading list against their Apple Books library. Covers efficient batch color extraction (5 calls instead of 150+), annotation-to-book matching, and markdown export patterns.
Read, inspect, or summarize arXiv papers using a clean-markdown-first paper-reading workflow. Use when the user provides an arXiv URL or id, asks to read a paper, analyze a preprint, summarize a research paper, compare claims against evidence, or extract assumptions, limitations, strengths, and weak links from a paper.
Atlassian CLI (acli) expertise for interacting with Jira Cloud and Atlassian organization admin from the terminal. Use when scripts invoke `acli`, user asks about Atlassian CLI, Jira CLI, JQL-driven automation, bulk Jira operations, or managing Jira work items, projects, boards, sprints, filters, fields, dashboards, Atlassian org admin users, or Rovo Dev authentication.
Aggressive intellectual challenge for truth-seeking and growth. Identifies blind spots, challenges assumptions, calls out avoidance patterns, and forces concrete action. Triggers on strategic decisions, founder dilemmas, reasoning validation, or any request for honest pushback.
Exit ritual for a work session. Use when the user invokes /checkpoint, says they are done for the day or leaving a project for a while, or accepts the wrap-up proposal armed by /lets-work. Routes each piece of understanding gained this session to its proper home — a code comment, the PR/commit message, or the personal journal — then records the visit marker the next /lets-work will brief from.
Build or update a chronology from declared document sources and uploaded materials — extract dated events, deduplicate them, and flag significance against the case theory. Use when the user asks to build a chronology or timeline from evidence or case files, says "extract a timeline from the materials" or "what happened when", or needs a working chronology, statement of facts, or witness-specific timeline.
What is blocking closing — maintain a closing checklist with status, critical path, and days to closing. Self-updating: receives new items from due diligence findings and checklist builds, tracks status, and surfaces blockers. Use when the user says "closing checklist", "what's left", "checklist status", "add to checklist", or pulls by deal status.
Search Zhihu (知乎) using agent-browser with proper authentication handling. Use when user asks to "search zhihu", "知乎搜索", "在知乎上找", or any Zhihu-related search requests. Handles login requirements, session persistence, and common error cases like 40362 restrictions.
Aggregates and summarizes the latest AI news from multiple sources including AI news websites and web search. Provides concise news briefs with direct links to original articles. Activates when user asks for "today's AI news", "AI updates", "latest AI developments", or mentions wanting a "daily AI briefing".
Start your day with a prioritized sales briefing. Works standalone when you tell me your meetings and priorities, supercharged when you connect your calendar, CRM, and email. Trigger with "morning briefing", "daily brief", "what's on my plate today", "prep my day", or "start my day".
Comprehensive framework for deep analysis of articles, papers, and long-form content using 10+ thinking models (SCQA, 5W2H, critical thinking, inversion, mental models, first principles, systems thinking, six thinking hats). Use when users want to: (1) deeply understand complex articles/content, (2) analyze arguments and identify logical flaws, (3) extract actionable insights from reading materials, (4) create study notes or learning summaries, (5) compare multiple sources, (6) transform knowledge into practical applications, or (7) apply specific thinking frameworks. Triggered by phrases like 'analyze this article,' 'help me understand,' 'deep dive into,' 'extract insights from,' 'use [framework name],' or when users provide URLs/long-form content for analysis.
Universal deep research agent team. 13-agent pipeline for rigorous academic research on any topic. 8 modes: full research, quick brief, paper review, lit-review, fact-check, three-way literature scan, Socratic guided research dialogue, and systematic review with optional meta-analysis. Covers research question formulation, Socratic mentoring, methodology design, systematic literature search, source verification, cross-source synthesis, risk of bias assessment, meta-analysis, APA 7.0 report compilation, editorial review, devil's advocate challenges, ethics review, and post-research literature monitoring. Triggers on: research, deep research, literature review, systematic review, meta-analysis, PRISMA, evidence synthesis, fact-check, WHY HOW WHAT papers, 3W literature scan, guide my research, help me think through, 研究, 深度研究, 文獻回顧, 文獻探討, 系統性回顧, 後設分析, 事實查核, 三段式文獻掃描, 引導我的研究, 幫我釐清, 幫我想想, 我不確定要研究什麼, 研究方向, 研究主題.
Manage InnoSage Draft pages and hosted Secret Shares using the @innosage/draft-cli. Use this skill for `draft`, `draft page ...`, `draft secret ...`, and `draft auth ...`. Prefer JSON Workspace page operations anchored by workspace status/path metadata. Do not use this skill when "draft" is only a verb or when the task is a generic local-file writing task unrelated to Draft CLI.
Design Thinking method coaching knowledge across all nine methods including per-method techniques, deep expertise, and industry context (energy, financial services, healthcare, manufacturing, nonprofit and social impact, pharmaceuticals and life sciences, professional services, public sector, retail and CPG)
Explain any topic, code, concept, or error in a way that matches a specific audience’s level of understanding. Trigger when the user says “explain it so a five-year-old can understand”, “ELI5”, “explain it to my manager”, “teach it to a fifth grader”, “explain it to a layperson”, “put it in plain language”, “explain this error to my mom”, “simplify it for a designer”; asks to explain something to a specific person or group (such as “tell my boss” or “how do I explain this to my wife”); or wants an explanation at a particular level or for a non-technical audience. Trigger even for incomplete mentions such as “explain it to my wife” or “tell my boss”.
Generate professional email templates for various business scenarios including sales outreach, customer support, internal communications, follow-ups, and apologies. Creates personalized, tone-appropriate templates with subject lines and formatting. Use when users need to write business emails, cold outreach, or professional communications.
Write a weekly engineering status report for a team, service, or initiative. Use when asked to write a team update, weekly engineering report, sprint status email, or standing team communication to stakeholders. Produces a concise, scannable weekly report covering shipping progress, metrics, decisions, blockers, and next-week priorities.
Search the company's enterprise knowledge index. Use this FIRST when starting any task that touches company-specific context - projects, people, policies, internal docs, prior decisions - before searching individual sources like Drive, Slack, or Jira directly. Also use it when the user asks "do we have a doc about X", "what's our policy on Y", or references internal initiatives by name. Always start from this skill when interacting with this service — its bundled scripts and recipes are the fastest path.
Entity compliance tracker — initialize, report upcoming deadlines, update status, run a health audit, export to CSV. Maintains compliance-tracker.yaml built from the entity roster, calculates filing deadlines by entity and jurisdiction, and surfaces items due within the next 30/60/90 days. Use when the user says "entity compliance," "filing deadlines," "annual report due," "entity tracker," "what filings are due," "entity health," or "good standing."
Structure and package support escalations for engineering, product, or leadership with full context, reproduction steps, and business impact. Use when an issue needs to go beyond support, when writing an escalation brief, or when assessing whether an issue warrants escalation.
Assemble a panel of experts to assess a problem from multiple professional perspectives, surface agreement and disagreement, and deliver a chaired recommendation with clear tradeoffs. Use when the user wants multi-expert judgment, a second opinion, design critique, option comparison, or a recommendation backed by distinct expert viewpoints.
Comprehensive Feishu/Lark integration skill for OpenClaw. Covers messaging, group management, Bitable (multi-dimensional tables), documents, calendar, video conferencing (vc.v1), meeting minutes (minutes.v1), task management, approval workflows, contacts, cloud drive, wiki/knowledge base. Requires the official Lark MCP server to be configured and running.
Help researchers identify and catalog relevant datasets for empirical research. Use this skill whenever a user asks to find data, locate datasets, identify data sources, or asks "what data exists for...", "where can I get data on...", "is there a dataset that...", or similar. Also trigger when the user describes a research question and needs to know what data could support it, asks about data availability for a particular topic or geography, wants to compare data sources, or mentions needing panel data, cross-sectional data, or time-series data for a project. Trigger on mentions of "find data", "data search", "dataset", "data source", "microdata", "administrative data", "survey data", "public-use data", "restricted data", or when the user specifies parameters like time windows, geographic levels, or data frequency in the context of research. Also trigger when the user asks for help downloading, scraping, or structuring a dataset that has been identified.
Search the Karma Funding Map for funding programs (grants, hackathons, bounties, accelerators, VC funds, RFPs) via the public API. Use when user says "find grants", "search hackathons", "look for bounties", "explore funding", "programs on Optimism", "what can I apply to", "funding opportunities", or asks about programs over or under a budget.
Help founders run companies using contrarian principles with real examples from successful founders. Challenge standard advice designed for professional managers. Use when facing strategic decisions, organizational challenges, or receiving conventional advice that conflicts with founder instincts.
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.