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Found 1,677 Skills
Complete Hyperliquid playbook — perpetuals and spot trading, margin/leverage, TWAP, real-time WebSocket data, and historical candles. Use for any Hyperliquid task. Trading triggers: place perp/spot orders (Gtc/Ioc/Alo), market-like fills, take-profit/stop-loss grouping, modify or cancel orders, batch cancels, TWAP orders (place/track fills/terminate), change leverage (cross vs isolated), adjust isolated margin, transfer USDC between spot and perp accounts (usd_class_transfer), get the EVM deposit address to fund Hyperliquid. Data triggers: read account summary (perp margin, positions, liquidation price, unrealized PnL), spot balances, portfolio, open orders, historical orders, single order status, fills (latest or by time window), funding history, rate limits, market metas (perp + spot, szDecimals), perp-only metas, spot-only metas, mid prices for all coins, L2 orderbook per coin, spot token details, allDexsAssetCtxs snapshot (funding/OI/mark prices across assets). Real-time WebSocket: wss://api.hyperliquid.xyz/ws with channels allMids, allDexsAssetCtxs (backend manages a shared subscription — agent can subscribe/unsubscribe and read the cached snapshot), l2Book, trades, candle, orderUpdates, userFills, userFundings. Historical OHLCV candles via direct POST https://api.hyperliquid.xyz/info {type: 'candleSnapshot'} — supports 1m/3m/5m/15m/30m/1h/2h/4h/8h/12h/1d/3d/1w/1M intervals up to 5000 candles. Covers all routes under /agent/trading/* (market/metas|mids|perp-metas|spot-metas|l2-book|token|all-dexs-asset-ctxs, deposit-address, account, account/spot, portfolio, rate-limit, orders, orders/details, orders/history, orders/:oid/status, twap, twap/fills, twap/:id, fills, fills/by-time, funding, leverage, margin, transfer). Triggers on mentions of Hyperliquid, "HL", perp, perpetual, funding rate, TWAP, isolated margin, cross margin, "deposit to Hyperliquid", "HIP-3", "HLP", or "HL vault". Prerequisite: openfin-setup.
Fetch recent posts from one or more X/Twitter accounts through twitterapi.io, output structured JSON/CSV records, optionally sync records to Feishu/Lark Bitable through feishu-cli, and optionally guide recurring execution through OpenClaw, Codex automations, cron, or launchd. Use when the user wants to monitor X bloggers, collect recent tweets, export tweet metrics, append tweets to Feishu Bitable, or set up a scheduled Twitter/X account tracking workflow.
Validate domain boundaries -- detect cross-context import violations and aggregate invariant issues
What a knowledgeable local with great taste would tell you to walk to from here — fused across editorial, local-language, and crowd layers no single tool ranks together. Trigger phrases: `what should I walk to from here`, `near me with great taste`, `find the 3 places not the 40`, `kissaten near my hotel`, `viewpoint within walking distance`, `blue hour photo spot`, `use wanderlust-goat`, `run wanderlust-goat`.
Translate free-text tumor descriptions to OncoTree codes, look up cancer subtypes and tissue hierarchies, resolve UMLS/NCI cross-references, and obtain OncoKB-compatible tumor type codes for variant annotation. Use when asked to find the OncoTree code for a tumor type, enumerate subtypes of a cancer, list cancers by tissue of origin, or standardize tumor nomenclature for downstream precision oncology analysis.
Every Fireflies meeting feature, plus offline search, cross-meeting intelligence, and a local database no other tool... Trigger phrases: `find stale action items from meetings`, `search my meeting transcripts for`, `who talked most in recent meetings`, `sync fireflies meetings`, `use fireflies-pp-cli`, `run fireflies`, `what did we discuss with`.
Use when building or maintaining a persistent personal knowledge base (second brain) in Obsidian where an LLM incrementally ingests sources, updates entity/concept pages, maintains cross-references, and keeps a synthesis current. Triggers include "second brain", "Obsidian wiki", "personal knowledge management", "ingest this paper/article/book", "build a research wiki", "compound knowledge", "Memex", or whenever the user wants knowledge to accumulate across sessions instead of being re-derived by RAG on every query.
Helps EMs build a reliable relationship with their manager, navigate disagreements with leadership, and communicate upward effectively. Use when the user says "managing up," "my manager," "I disagree with a decision," "I need to push back," "my skip level," "communicating with leadership," "my manager committed my team without asking," "how do I tell my boss," or "senior leadership." Do NOT use for influencing peers or cross-functional stakeholders (use influence) or for general EM self-reflection (use managing-yourself).
Hedging strategy design framework — Beta hedge ratio (portfolio vs benchmark), option protection strategies (protective put / collar), tail-risk hedges (VIX-related / gold / treasuries), cross-asset hedges (currency risk), and hedge cost assessment (option premium vs protection value). Triggers: "对冲", "对冲策略", "Beta对冲", "保护性看跌", "领口策略", "尾部风险", "汇率对冲", "对冲比率", "對冲", "對冲策略", "Beta對冲", "保護性看跌", "領口策略", "尾部風險", "hedging", "hedge strategy", "beta hedge", "protective put", "collar strategy", "tail risk hedge", "currency hedge", "hedge ratio", "portfolio insurance".
Use when working with n8n workflows in any capacity. The always-on protocol for the n8n-skills plugin, loaded by the SessionStart hook every session. Routes to the right skill, summarizes every n8n MCP tool (closing the deferred-description gap), and lists the cross-cutting rules.
Generate a 15-second cinematic awards-ceremony video — a host announces a winner from the stage, a spotlight finds them in the crowd, they walk up to the podium, receive the award, and the LED display reveals their name and "THE BEST ACTOR".
Spatial data gridding and interpolation with a machine-learning style API. Process geographic and Cartesian point data onto regular grids. Use when Claude needs to: (1) Grid scattered spatial data onto regular grids, (2) Interpolate point data using splines, linear, or cubic methods, (3) Process geographic coordinates with projections, (4) Reduce large datasets using block averaging, (5) Remove polynomial trends from spatial data, (6) Cross-validate gridding parameters, (7) Create processing pipelines with Chain, (8) Grid vector data like GPS velocities.