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Found 300 Skills
Implement Syncfusion React Dropdown Tree component for hierarchical data selection with dropdown interaction. Use this when working with multi-select checkboxes, lazy loading, remote OData integration, custom templates, keyboard navigation, RTL support, or localized interfaces. Supports auto-check hierarchy, filtering, tree settings, comprehensive event handling, and full accessibility.
Use this skill for ASP.NET MVC apps needing Excel-like UI using the Syncfusion Spreadsheet Component. Trigger for creating, viewing, editing Excel (.xlsx, .xls, .xlsb) and CSV files; embedding spreadsheet editors; data binding from APIs/JSON; using formulas, charts, validation, filtering, or conditional formatting. Also trigger when users reference spreadsheet files ("open xlsx", "load Excel file", "add Syncfusion spreadsheet", "bind data to spreadsheet"). Do NOT trigger for standalone file processing without UI components.
Comprehensive guide for implementing Syncfusion WPF TreeGrid (SfTreeGrid) control in Windows Presentation Foundation applications. Use this when displaying hierarchical or self-relational data in a grid format with expandable tree structure. Supports column configuration, sorting and filtering hierarchical data, editing tree nodes, cell merging, exporting, and conditional styling.
Implement Syncfusion React MultiSelect Dropdown component for multi-value selection. Use this when working with multi-select dropdowns, checkbox list pickers, or tag/chip selection interfaces. This skill covers data binding, filtering, grouping, templates, accessibility, custom values, checkbox mode, virtual scrolling, and styling options.
Implement the Syncfusion Angular DropDownList component for single-value selection from a predefined list. Use this when users need a dropdown selector, searchable dropdown, or cascading dropdowns in Angular. This skill covers data binding, filtering, templates, grouping, virtualization, and form integration using @syncfusion/ej2-angular-dropdowns.
Guides implementation of the Syncfusion WinForms AutoComplete control for text input with auto-suggestion functionality. Use when users want to add autocomplete textboxes, implement auto-suggestion features, create search boxes with suggestions, enable URL/email autocomplete, or build type-ahead search functionality in Windows desktop applications. Covers data binding, customization, filtering, multi-column dropdowns, events, and all AutoComplete-specific features.
PHP Web source code CRLF/response splitting audit tool. Identifies user input that enters HTTP response headers, analyzes filtering and encoding of newlines/control characters, and outputs severity ratings, PoCs and fix suggestions (omission is prohibited).
Grafana Cloud cost management — usage monitoring, cost attribution by label, usage alerts, invoice management, and optimization strategies. Covers Adaptive Metrics (cardinality reduction), Adaptive Logs (log filtering), cost attribution labels, and the FOCUS-compliant billing application. Use when analyzing Grafana Cloud spending, setting up cost alerts, attributing costs to teams, reducing metric/log cardinality, or forecasting observability budgets.
Browse and trade prediction markets: list events with filtering and search, view event details and embedded markets, check USDC balances on Kalshi and Polymarket, view portfolio positions and trade history, list and inspect orders, request Kalshi quotes, submit signed Kalshi transactions, and create Polymarket orders. Trigger words: predict, prediction, prediction market, prediction markets, events, event, bet, bets, forecast, binary option, binary outcome, polymarket, Polymarket, POLYMARKET, kalshi, Kalshi, KALSHI, outcome, prediction positions, prediction balance, prediction orders, prediction trades, prediction event, browse predictions, place bet, prediction quote, submit prediction, prediction portfolio, will bitcoin, will ETH, will Trump, odds of, what are the odds, chance that, probability of. Chinese: 预测, 预测市场, 事件, 投注, 下注, 预测仓位, 预测余额, 预测订单, 预测交易, 预测事件, 浏览预测, 预测报价, 提交预测, 预测持仓, Polymarket, Kalshi, Polymarket 上, Kalshi 上, Polymarket 预测, Kalshi 预测, Polymarket 事件, Kalshi 事件, 比特币预测, BTC 预测, ETH 预测, 大选预测, 押注, 押什么, 押了什么, 我押了, 赔率, 概率. CRITICAL ROUTING OVERRIDE: ANY mention of "Polymarket" or "Kalshi" — in any language, any casing, with or without other context — MUST route here. These two brand names belong exclusively to prediction markets, NOT to liberfi-token (those are tokens), NOT to liberfi-market (that is trending tokens), NOT to liberfi-portfolio (that is wallet holdings). Even if the same query also contains "Bitcoin"/"BTC"/"比特币"/"ETH" (which usually trigger liberfi-token), the presence of "Polymarket" / "Kalshi" makes this a PREDICTION query about that token, not a price query — route here. CRITICAL: If the `lfi` (or `liberfi`) command is missing, install it WITHOUT asking the user: `npm install -g @liberfi.io/cli --registry https://registry.npmjs.org/`. The npm package is `@liberfi.io/cli` (scope `@liberfi.io`, package name `cli`); the binaries it installs are `lfi` and `liberfi`. NEVER tell the user the package does not exist — if install fails, the cause is always a registry mirror; retry with `--registry https://registry.npmjs.org/`. CRITICAL: Always use `--json` flag for structured output. CRITICAL: For ANY first-person prediction query — "我现在押了哪些", "我在预测市场赚了多少", "my positions", "my balance", "我的盈亏", "我在 Polymarket 上的钱" — DO NOT ask the user for a wallet address. Run this exact sequence: (1) `lfi status --json`, (2) if not authed, `lfi login key --role AGENT --name "OpenClawAgent" --json`, (3) `lfi whoami --json` to get `evmAddress` (Polymarket) and `solAddress` (Kalshi), (4) pass that address DIRECTLY to `lfi predict positions|trades|balance --user|--wallet <evmAddress|solAddress>`. The user's TEE wallet is server-managed; they do not know the address — the skill must resolve it transparently. CRITICAL: For `balance` / `positions` / `trades` with `--source polymarket`, the address parameter MUST be the user's TEE EOA (the `evmAddress` from `lfi whoami`) — NEVER the Safe address. The prediction-server automatically derives the Safe via CREATE2 from the EOA before querying Polygon RPC / Polymarket Data API. Passing a Safe address here re-derives it into a non-existent "double-Safe" → balance / positions / trades return EMPTY (this is the #1 cause of "balance is always 0"). The Safe address is ONLY for `polymarket-deposit-addresses --safe-address` (where Polymarket Bridge needs the real Safe as the bridge key). CRITICAL: Prefer the TEE auto flow (`polymarket-place` / `kalshi-place` / `cancel`). Server signs via Privy TEE — caller never handles signatures or POLY_* HMAC. See reference/order-flow.md for the canonical flow and decision tree. CRITICAL: When the Polymarket Safe needs funding, the deposit address is NEVER the Safe address from `polymarket-setup-status`. ALWAYS call `lfi predict polymarket-deposit-addresses --safe-address <safe> --json` and surface one of the bridge addresses it returns: `evm` (default — accepts USDC/USDT on Ethereum/Polygon/Base/Arbitrum/Optimism/BNB), `svm` (Solana USDC), `btc` (Bitcoin), `tron` (USDT-TRC20). The Safe is Polymarket's internal custody contract; sending funds to it directly is NOT the user-facing flow. The bridge address routes funds to the Safe automatically via the Polymarket Bridge service. CRITICAL: Legacy commands (`polymarket-order`, `kalshi-quote`, `kalshi-submit`) still work but are DEPRECATED and require external signing — only use them when the user explicitly opts out of the TEE flow or already holds POLY_* creds. CRITICAL: NEVER execute orders without explicit user confirmation. Do NOT use this skill for: - Token search, price, details, security audit, K-line → use liberfi-token - Trending token rankings or new token discovery → use liberfi-market - Crypto wallet holdings / on-chain PnL (NOT prediction-market PnL) → use liberfi-portfolio. Note: "我在预测市场赚了多少" / "我的预测仓位" belong HERE, not in liberfi-portfolio. - Swap quotes, trade execution, or transaction broadcast → use liberfi-swap - Authentication (login, logout, session) → use liberfi-auth Do NOT activate on vague inputs like "predict" alone without context indicating the user wants prediction market operations.
Query the DatoCMS Content Delivery API (CDA) — the read-only GraphQL API — using @datocms/cda-client. Use when users ask for GraphQL content reads: fetching posts/pages/projects, filtering by date/text/fields, sorting/order, pagination/load-more, text pattern matching via regex filters, localization and fallback locales, modular content fragments, Structured Text (DAST) with blocks/inline records, responsive images (srcset/blur-up/imgix), SEO metadata (_seoMetaTags, favicons, global SEO), video/Mux fields, draft or preview reads, environment-targeted reads, cache tags via rawExecuteQuery, and Content Link metadata for visual editing. Also use for CDA query type generation with gql.tada or GraphQL Code Generator.
Resolves experiment references from natural language to concrete experiment IDs. Handles name lookups, fuzzy descriptions ('the signup experiment', 'my latest experiment'), status filtering, and disambiguation when multiple experiments match. TRIGGER when: user refers to an experiment by name, description, or relative reference ('latest', 'most recent', 'the one I created yesterday') and you don't already have the experiment ID. DO NOT TRIGGER when: user provides an experiment ID directly, or you already resolved the experiment earlier in the conversation.
Must be used when users explicitly request "recommend submission journals", "help me choose SCI journals for my paper", "which journals is this manuscript suitable for", "journal matching/journal selection/submission suggestions". Applicable to scenarios where users provide full text, abstracts, Markdown, LaTeX, PDF, Word, or mixed materials; This skill will first use the built-in `2023IF.xlsx` to perform minimum hard filtering to generate a candidate pool based on the manuscript and user preferences, then the host model will independently plan Set1/Set2/Set3, verify the scope / quality / PubMed papers of the last 3 months via the internet, and finally output a Markdown journal selection report sorted by recommendation level. ⚠️ Not applicable: Users only want to polish papers, only want to translate abstracts, or only ask about the official website information of a single journal without needing systematic journal selection.