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Found 185 Skills
Creates and configures Home Assistant graph visualizations using history-graph, statistics-graph, mini-graph-card, and apexcharts-card with time ranges, aggregations, and multi-sensor support. Use when displaying sensor data over time, creating trend charts, comparing historical data, or building energy/climate/air quality dashboards.
Make sure to use this skill whenever the user mentions anything related to Danish property data, housing prices, real estate statistics, sold homes, property history, BBR data, or the Danish housing market — even if they don't mention boliga.dk explicitly. Also invoke this skill for questions about specific Danish addresses, zip codes, or municipalities in a housing context. Trigger phrases include: danish property, danish real estate, danish housing market, boliga, bolig til salg, solgte boliger, boligpriser, ejendomspriser, ejendom, ejerlejlighed, villa, rækkehus, sommerhus, fritidshus, andelsbolig, helårsgrund, landejendom, BBR data, bygningsregistret, property for sale denmark, sold homes denmark, house prices denmark, apartment prices copenhagen, aarhus housing, odense real estate, housing statistics denmark, quarterly price index denmark, most viewed properties denmark, property valuation denmark, ejendomsvurdering, salgspris, kvadratmeterpris, days on market, dage til salg, boligsøgning, address lookup denmark, property history denmark.
Analyze wallet portfolios on supported blockchains: view token holdings with current values, track transaction activity and history, check PnL (profit and loss) statistics over different time windows, and query total wallet net worth. Also supports querying the authenticated user's own LiberFi TEE wallet portfolio without needing to provide a wallet address — use the `me` commands when the user wants to check their own LiberFi account's holdings, activity, stats, or net worth. Trigger words: wallet, portfolio, holdings, my tokens, my coins, my balance, what do I hold, what tokens do I have, wallet balance, wallet holdings, wallet activity, transaction history, recent transactions, transfers, swaps, trade history, wallet stats, PnL, profit and loss, profit, loss, gains, returns, performance, how much did I make, how much did I lose, win rate, net worth, total value, portfolio value, total balance, how much is my wallet, wallet overview, wallet summary, wallet analysis, check wallet, view wallet, my portfolio, account balance, my LiberFi wallet, my TEE wallet, my account portfolio, check my account, my holdings without address. Chinese: 钱包, 持仓, 我的代币, 我持有什么, 余额, 钱包余额, 交易记录, 交易历史, 最近交易, 转账记录, 钱包统计, 盈亏, 利润, 亏损, 收益, 收益率, 胜率, 净值, 总价值, 钱包总价值, 钱包概览, 钱包分析, 查看钱包, 我的LiberFi钱包, 我的TEE钱包, 我的账户持仓, 不知道地址查我的钱包. CRITICAL: Always use `--json` flag for structured output. CRITICAL: Public `wallet` commands require both chain and wallet address — always ask the user for these if not provided. CRITICAL: `me` commands do NOT require a wallet address — they use the authenticated user's TEE wallet automatically. They DO require authentication (run `lfi status` first, then `lfi login key` if needed). Do NOT use this skill for: - Token search, info, security audit, K-line → use liberfi-token - Trending tokens or new token rankings → use liberfi-market - Swap quotes, trade execution, or transaction broadcast → use liberfi-swap - Token holder analysis (for a specific token) → use liberfi-token Do NOT activate on vague inputs like "wallet" alone without a wallet address or clear intent to check portfolio data.
Create production-quality data visualizations including charts, dashboards, and infographics. Use when the user asks to visualize data, create charts, build dashboards, make infographics, plot statistics, or transform datasets into visual representations. Supports React/Recharts artifacts, static images (PNG/PDF via Python), and interactive HTML. Triggers include "visualize this data", "create a chart", "build a dashboard", "make a graph", "plot this", "infographic", or any request to represent data visually.
Use this skill for Hugging Face Dataset Viewer API workflows that fetch subset/split metadata, paginate rows, search text, apply filters, download parquet URLs, and read size or statistics.
Reviews, curates, and maintains the Forge library of agents, skills, and templates. Performs deduplication analysis, staleness detection, quality promotion, and orphan reference checking. Produces structured review reports with actionable recommendations for merging, archiving, or promoting library items. Use this skill when the user wants to review the library, clean up agents or skills, check what's available, find duplicates, trim unused items, see library statistics, or says "what's in my library?" Also triggers on scheduled review intervals or when the library grows beyond 20 items. Do NOT use for creating new agents (use Agent Creator), creating skills (use Skill Creator), or planning teams (use Mission Planner).
Convert webinar recordings into blog posts, social snippets, email series. Extract key quotes, statistics, and soundbites.
Orchestrate multi-simulation campaigns — generate parameter sweep configurations (grid, linspace, or Latin Hypercube sampling), initialize and track batch job campaigns, monitor job completion status, and aggregate results with summary statistics across all runs. Use when running a parameter study across dt, kappa, or other simulation inputs, managing dozens or hundreds of simulation configurations, combining outputs from completed batch runs to find the best result, or automating the generate-run-collect workflow for systematic studies, even if the user only says "I need to try many parameter combinations" or "how do I organize a sweep."
Analyze multi-round evaluation score data, count various indicators, and calculate rating levels. Suitable for analyzing score trends and calculating S/A/B ratings
End-to-end epidemiological data analysis — from research question to statistical report. Covers study design assessment, dataset discovery and download, data wrangling, confounder adjustment, regression modeling, sensitivity analysis, visualization, and biological interpretation. Integrates ToolUniverse tools for dataset discovery, literature search, and biological context with Python code execution for data analysis. Use whenever users ask to analyze health data, study disease risk factors, assess exposure-outcome relationships, or conduct observational epidemiology. Also use when users want to run regression on clinical/survey data, calculate odds ratios or hazard ratios from a dataset, adjust for confounders, or produce a Table 1. If the task involves downloading a health dataset and running statistical analysis on it, this is the right skill.
This skill should be used when the user asks for 'TRX price', 'TRON token price', 'price chart on TRON', 'K-line data for USDT/TRX', 'TRON trade history', 'TRON whale activity', 'large transfers on TRON', 'smart money on TRON', 'TRON DEX volume', or mentions checking real-time prices, candlestick data, trading volume, whale monitoring, or smart money signals on the TRON network. For token search and metadata, use tron-token. For swap execution, use tron-swap.
CoinGecko crypto price data, charts, market discovery, and global stats