Skills
96,981 packaged capabilities and playbooks for agents. Install any of them with one command.
Productivity
Assists in writing high-quality content by conducting research, adding citations, improving hooks, iterating on outlines, and providing real-time feedback on each section. Transforms your writing process from solo effort to collaborative partnership.
Automate Electron desktop apps (VS Code, Slack, Discord, Figma, Notion, Spotify, etc.) using agent-browser via Chrome DevTools Protocol. Use when the user needs to interact with an Electron app, automate a desktop app, connect to a running app, control a native app, or test an Electron application. Triggers include "automate Slack app", "control VS Code", "interact with Discord app", "test this Electron app", "connect to desktop app", or any task requiring automation of a native Electron application.
Web toolkit powered by Exa, tuned for scientific and technical content. Use this skill when the user needs to search the web or fetch/extract URL content. Covers: web search (semantic lookups, research, current info — with optional research-paper category and academic domain filtering) and URL extraction (fetching pages, articles, academic PDFs in batch). Use this skill for web-related tasks when the user wants high-quality search or scholarly filtering via category=research paper. Triggers on requests to search, look up, fetch a page, or extract an article.
Capture how the system feels — energy, momentum, burnout, breakthrough. Emotional intelligence for Oracle-human collaboration. Use when user says 'feel', 'how are we', 'energy check', 'burnout', 'momentum', or wants emotional awareness of the work.
Fetch and summarize Feishu group chat history. Use when the user asks to read, review, or summarize messages from a Feishu group chat. Triggers: "看群聊记录", "群里聊了啥", "帮我看看这个群", "群消息历史", "chat history", "what did the group discuss". NOT for: sending messages (use message tool), reading documents (use feishu-doc skill), or wiki operations (use feishu-wiki skill).
Search, scrape, and interact with the web via the Firecrawl CLI. Use this skill whenever the user wants to search the web, find articles, research a topic, look something up online, scrape a webpage, grab content from a URL, get data from a website, crawl documentation, download a site, or interact with pages that need clicks or logins. Also use when they say "fetch this page", "pull the content from", "get the page at https://", or reference external websites. This provides real-time web search with full page content and interact capabilities — beyond what Claude can do natively with built-in tools. Do NOT trigger for local file operations, git commands, deployments, or code editing tasks.
Write, rewrite, edit, humanize, or post text in the user's own voice without AI tells. Use when the user asks you to write as them, polish their prose, humanize or de-slop text, draft essays, posts, emails, notes, explanations, or research writing, or produce any outward-facing text where their identity, tone, or writing preferences matter.
Generates in-depth research reports for a specified industry based on the East Money database. This Skill should be triggered when a user's question contains an identifiable industry/sector/domain subject and the intent is industry understanding, industry analysis or writing a research report. Common phrasings include "XX industry research", "XX industry report", "help me analyze industry XX", "in-depth research on industry XX", "market analysis of domain XX", etc. Even if the user does not explicitly say "report", it also applies whenever an industry is the core subject and systematic or in-depth research/analysis is requested.
Teach Claude ANY topic - code libraries, APIs, concepts, tools, methodologies, or domains. Researches via web and docs, then retains knowledge as a permanent skill. Use when user says "/learn <topic>", "learn about X", "teach yourself Y", "become an expert on Z". Examples - "/learn stripe" for payments, "/learn GTD" for productivity, "/learn israeli-tax-law" for domain knowledge.
Generate measurable learning outcomes aligned with Bloom's taxonomy and CEFR proficiency levels for educational content. Use when educators need to define what students will achieve, create learning objectives for curriculum planning, or ensure objectives are specific and testable rather than vague.
Generate a deliverable markdown report by merging all /money-save snapshots for a project. Produces a shareable, dated document at ~/.smtm/reports/{project}/. Useful for sharing progress with co-founders, advisors, investors, or for personal review weeks/months later. Use when the user wants to package up accumulated state into a readable artifact. Triggered by: 'package this up', 'make me a report', 'export for partner', 'give me the deliverable', '出报告', '打包', '整理一份', '给合伙人看的'.
This skill should be used when the user asks to maintain an Obsidian knowledge base for a research project, import an existing research repository into Obsidian, keep project memory or daily notes synchronized, summarize project context into durable notes, or update experiments, results, papers, writing, and plans in an Obsidian vault without requiring MCP.
Transforms, restructures and exports all research output (abstract, literature review, comparison matrix, hypotheses) into Obsidian-native Markdown files complete with structured YAML Frontmatter, bidirectional links ([[WikiLinks]]), tags, and ready-to-use Dataview queries.
Create a structured 30/60/90-day onboarding plan for any new hire. Use when asked to write an onboarding plan, new hire plan, 30-60-90 day plan, or first 90 days roadmap. Produces a week-by-week plan with milestones, meetings, learning goals, and success criteria.
Self-hosted, open-source alternative to Google NotebookLM for AI-powered research and document analysis. Use when organizing research materials into notebooks, ingesting diverse content sources (PDFs, videos, audio, web pages, Office documents), generating AI-powered notes and summaries, creating multi-speaker podcasts from research, chatting with documents using context-aware AI, searching across materials with full-text and vector search, or running custom content transformations. Supports 16+ AI providers including OpenAI, Anthropic, Google, Ollama, Groq, and Mistral with complete data privacy through self-hosting.
Runs the parallel-cli tool for web workflows: web search, URL and PDF extraction, deep research reports, structured data enrichment of supplied rows, FindAll entity discovery, and recurring web monitors. Prefers primary literature and institutional sources for scientific queries. Use when looking up current web evidence or a bounded research question. Use when fetching content from a known URL, PDF, or JavaScript-rendered page. Use when adding web-sourced fields to a list of companies, people, or products. Use when discovering entities that match natural-language criteria. Use when an explicitly exhaustive multi-source report is requested. Use when tracking web changes on a recurring schedule. Not for one-time checks of a known page that need no CLI, or for offline literature databases.
Perform AI-powered web searches with real-time information using Perplexity models via LiteLLM and OpenRouter. This skill should be used when conducting web searches for current information, finding recent scientific literature, getting grounded answers with source citations, or accessing information beyond the model's knowledge cutoff. Provides access to multiple Perplexity models including Sonar Pro, Sonar Pro Search (advanced agentic search), and Sonar Reasoning Pro through a single OpenRouter API key.
Get research-backed architecture advice for your knowledge system. Describe your use case, constraints, and goals — get specific recommendations grounded in TFT research with rationale for each decision. Triggers on "/recommend", "what would you recommend", "architecture advice", "knowledge system for".
Use when the user explicitly asks to "check/optimize the in-text citations of the review `{topic}_review.tex`", "run research-citation-check", or requests the old name check-review-alignment skill. It checks citation by citation, through the host AI's semantic understanding, whether citations match the literature content; only when a fatal citation error is found does it minimally rewrite the "sentence containing the citation", and it prefers reusing the rendering scripts of `research-literature-review` to output PDF/Word, with a fallback to the old name systematic-literature-review permitted during the transition. Core principle: do not change for the sake of changing; when it cannot be determined whether an error is fatal, keep it as is and warn in the report. ⚠️ Not applicable: the user merely wants to generate the review body (use research-literature-review); the user merely wants to add/verify BibTeX entries (use a dedicated bib management workflow).
Changes an RHDH Jira issue you already have a key for, in RHIDP, RHDHPLAN, RHDHBUGS, or RHDHSUPP: post a progress comment, transition status, add an issue link or a web link to a PR, close with a resolution and rationale, and pick and set the assignee from team roster, recent expertise, and sprint capacity. Use for "update jira", "update RHIDP-1234", "log my progress on this", "move this to Review", "close this out", "who should take this", or "assign RHIDP-1234". Edits existing work — it does not create issues, audit a backlog, or build a sprint.
Reports what is still open against an RHDH release from Jira RHIDP, RHDHPLAN, RHDHBUGS, and RHDHSUPP: issue counts by type, blocker bugs, CVEs, Engineering EPICs, per-team breakdowns, release-note lifecycle, Post Code Freeze scope, and any query in the RHIDP Operational Rich Filter export. Also reports readiness at the Feature and Program Increment level: PI funnel, feature status matrix, stretch features, epic roll-up, cross-team dependency map, per-Feature coherence, and risk assessment. Use for "release status for 1.10", "what's blocking 1.10.3", "are we ready to ship 1.10", or "PI funnel for 2.1".
Use when a founder wants a hard business decision debated by a council of world-class operators, says "roast room", "put this in the Roast Room", "founder council", "convene the council", "take this to the board", "what would Hormozi, Bezos, or Buffett say", "should I do X", or can't make up their mind on pricing, hiring, raising money, a new product, a partnership, a pivot, an event, or spending. A board of sub-agents, each built from one expert's public work (Bezos, Paul Graham, Hormozi, Gary Vaynerchuk, Dan Martell, Gino Wickman, and Buffett out of the box, plus any seat added with /newroaster), argue it over three rounds, then a Chair returns a scored verdict, the reasoning, the dissent, and next steps. Also does a one-seat consult ("ask the Hormozi seat"). Not /roast (generic personas, idea validation).
Search the web using a local SearXNG instance. Use for web searches, finding current information, researching topics, checking news, looking up documentation, or finding recent events. Supports categories: general, news, images, videos, it, science, social media.
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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.