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Found 2,399 Skills
Decision-grade entity research skill — produces a hypothesis-tested dossier on a specific company, person, nonprofit, or government org, not a generic profile. Forcing intake makes the user state their hypothesis upfront (what they already believe and want to verify or disprove) so the dossier tests it rather than confirms it. Output is an editable Word document (.docx) with verdict on the hypothesis, identity facts, 12-month activity timeline, network signals, reputation signals, red flags, 3-5 conversation hooks tied to specific findings, and source-provenance audit log. Uses WebSearch + WebFetch + free APIs (SEC EDGAR, GitHub, ProPublica Nonprofit Explorer) as workhorses; optional BYOK MCPs (LinkedIn, Crunchbase, Apollo, Pitchbook, SimilarWeb) enhance coverage. Triggers: 'research [company]', 'dossier on [person/company]', 'background check on [entity]', 'prep me for a meeting with [person/company]', 'due diligence on [company]', 'what should I know about [entity]', 'research [person] before I [meet/hire/invest]', 'competitor research on [company]', 'investor diligence [company]', 'interview prep for [company]'. Honors sensitivity exclusions for journalism + personal-vetting contexts.
Generate AI-agent-first CLIs from any API (OpenAPI, GraphQL, or browser-sniffed) with SQLite sync, compound commands, and MCP servers
Analyze Israeli bank transactions, spending patterns, and financial data across Israeli banks and credit card companies. Use when user asks about bank transactions, spending analysis, "cheshbon bank", budget tracking, or needs to categorize Israeli banking data. Pairs with israeli-bank-mcp and il-bank-mcp servers (which wrap the israeli-bank-scrapers library) to add financial-analysis workflows. Supports Hapoalim, Leumi, Discount, Mercantile, Mizrahi-Tefahot, First International (FIBI), Otsar HaHayal, Pagi, Union, Yahav, Massad, OneZero, Visa Cal, Max, Isracard, and Amex. Do NOT use for payment initiation, money transfers, or investment advice.
Connect to IDA databases and bootstrap sessions. Use when starting analysis, routing to other skills, or setting up CLI/HTTP/MCP connections.
Execute the /integrate command for LLM agents. Triggers when the user types `/integrate`, `/integrate --product`, or asks to "integrate a Juspay product", "set up payments", "add payment SDK", or any variation of setting up a Juspay product into their app or codebase. This skill drives a fully guided, doc-driven wizard: it reads product summaries locally, probes candidates via MCP, then fetches actual documentation pages and generates complete integration code.
OpenAI Agents SDK for JavaScript/TypeScript (text + voice agents). Use for multi-agent workflows, tools, guardrails, or encountering Zod errors, MCP failures, infinite loops, tool call issues.
CLI-first web research and source retrieval through the local smart-search command. Use when Codex needs current web search, source-backed fact checking, URL fetching, site mapping, official/API/documentation search, or reproducible search evidence via Skill + CLI instead of MCP tools.
HK IPO Subscription Analysis — A "Four-Dimensional Evaluation" framework to diagnose whether Hong Kong new stocks are worth subscribing (Pricing Rationality / Issue Quality / Market Timing / Fundamental Outlook). Outputs three-tier ratings: Recommend / Neutral / Avoid, plus prospectus highlights, risk warnings, and subscription references. It is retail-investor friendly with conclusions upfront. Covers three scenarios: in-depth evaluation of a single new stock, browsing recent IPO subscription calendars, and judging whether to chase newly listed stocks after missing the subscription. Prioritizes data from Longbridge CLI (ipo detail / ipo subscriptions / ipo wait-listing / ipo listed / peer-comparison / news / quote / kline / index-quote, etc.); uses MCP fallback for data missing from CLI; uses WebSearch as a last resort for data still unavailable (prospectus TAM, original cornerstone announcement, claw-back ratio, grey market price, underwriter industry ranking). **The report must end with a fixed "Data Source Details" appendix**, where every figure can be traced to line number + capture time + period. Only covers Hong Kong Main Board and GEM; does not involve US / A-share IPOs; must actively prompt leverage risks when margin financing (孖展) is involved. Triggers: "打新", "港股打新", "新股申购", "新股申購", "新股", "打新分析", "新股分析", "招股", "招股书", "招股書", "基石投资者", "基石投資者", "国际配售", "國際配售", "公开发售", "公開發售", "暗盘", "暗盤", "回拨机制", "回撥機制", "孖展", "新股盈亏", "新股盈虧", "次新股", "破发", "破發", "中签率", "中籤率", "新股几手", "新股幾手", "新股值不值得打", "新股能不能打", "港股 IPO 推荐", "港股 IPO 推薦", "近期港股新股", "HK IPO analysis", "hong kong IPO worth it", "HK new listing", "cornerstone investor", "prospectus highlights", "grey market premium", "subscription ratio", "claw-back", "margin financing IPO", "0700.HK", "09988.HK", "01024.HK"
Use this skill when working with Xquik's X Twitter Scraper API for tweet search, user lookup, follower extraction, media workflows, monitors, webhooks, MCP tools, SDKs, and confirmation-gated X account actions. Triggers on Twitter API alternatives, X API automation, scrape tweets, profile tweets, follower export, send tweets, post replies, DMs, and X/Twitter data pipelines.
Search Mobbin for real app UI screenshots and visually analyze them. Required before calling the `search_screens` MCP tool — this skill defines how to plan searches, respond, and build HTML evidence boards when the screens are the answer. Use whenever the user asks about UI/UX design patterns, wants to see how other apps handle a screen or flow, needs design inspiration or references, asks to compare UI approaches across apps, mentions Mobbin, or whenever `search_screens` would be relevant. Trigger aggressively for any design-related question — even if screenshots aren't explicitly requested.
This skill should be used when the user wants to interact with their paper database — listing papers, searching content, showing paper details, adding papers, or exporting context. Matches queries like "search papers for X", "add this arXiv paper", "show equations from paper Y", "what papers do I have". Prefer CLI over MCP RAG tools for direct lookups.
Pull Bigdata.com (RavenPack) financial and news data through the official `bigdata-client` SDK and its public `/v1/*` REST endpoints when the Bigdata MCP server returns only pre-synthesized tearsheets but you need the machine-readable substrate underneath. MCP search returns prose chunks (text + relevance only — no per-chunk sentiment, no entity spans); its tearsheets give only aggregate values, not computable time series or per-field JSON. This skill bundles a verified, cost-guarded toolkit over the official REST API: annotated chunk search, entity/ISIN resolution, analyst estimates, calendar/surprise/ ratings/targets, financial statements, TTM metrics & ratios, prices, dividends, revenue segments, a daily entity-sentiment series, co-mention graph, screener, and batch search. Use it whenever the user mentions Bigdata.com, RavenPack, a `bd_v2_` key, the bigdata MCP, rp_entity_id, chunk/query_unit cost, or wants structured financials, fundamentals, prices, sentiment, or annotated news.