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Found 2,503 Skills
Create a detailed execution plan for implementing features or refactors in a codebase by leveraging existing research in the specified `research` directory.
Quick pragmatic review of .NET test code for anti-patterns that undermine reliability and diagnostic value. Use when asked to review tests, find test problems, check test quality, or audit tests for common mistakes. Catches assertion gaps, flakiness indicators, over-mocking, naming issues, and structural problems with actionable fixes. Use for periodic test code reviews and PR feedback. For a deep formal audit based on academic test smell taxonomy, use exp-test-smell-detection instead. Works with MSTest, xUnit, NUnit, and TUnit.
Calculate Amazon shipping and fulfillment costs for FBA and FBM. Dimensional weight, storage fees, removal fees, and long-term storage cost estimation.
Generate and curate evaluation datasets — structured generation via dimensions-tuples-NL, quick from description, expansion from existing data, plus dataset maintenance through deduplication, rebalancing, and gap-filling. Use when creating eval data, expanding test coverage, or cleaning datasets. Do NOT use when sufficient real production data exists (use analyze-trace-failures instead). Do NOT use for evaluator creation (use build-evaluator).
Adapt an ML paper's writing, structure, positioning, and paragraph-level narrative to a target conference such as NeurIPS, ICML, ICLR, CVPR, ACL, EMNLP, or similar venues. Use this skill whenever the user wants to submit, rewrite, polish, restructure, or tailor a paper for a specific conference; asks what good accepted/oral papers at a venue look like; wants reviewer-friendly writing; or wants section-by-section or paragraph-by-paragraph paper guidance. This is a writing and presentation skill, not an experiment-design skill.
Use when extracting imperatives from agent instruction files, analyzing rule coverage, or preparing input for /policy-algebra and /distill.
Core technical-indicator signal engine for stocks listed in HK / US / A-share / Singapore via Longbridge Securities. Computes and interprets MACD, KDJ, RSI, Bollinger Bands, EMA, ADX, and OBV from OHLCV data; combines multi-dimensional votes (trend / mean-reversion / volume-price) to produce a composite buy / sell / neutral signal. Triggers: "技术指标", "MACD", "KDJ", "RSI", "布林带", "布林线", "EMA", "ADX", "OBV", "金叉", "死叉", "超买", "超卖", "技术分析", "趋势指标", "量价", "技術指標", "布林帶", "技術分析", "超買", "超賣", "technical indicator", "MACD signal", "KDJ overbought", "RSI oversold", "Bollinger Bands", "moving average", "golden cross", "death cross", "technical analysis".
Use when writing, fixing, or editing TypeScript code that touches APIs, JSON, environment variables, storage, databases, browser APIs, SDKs, generated clients, or other external boundaries.
Graham cigar-butt batch screener — runs Benjamin Graham's NCAV / net-net / defensive-investor hard filters across an index or market universe and returns a ranked candidate list with NCAV ratio, PE, PB, dividend yield, debt coverage, 5y earnings stability, Graham buy price, and a dynamic value-trap warning. Longbridge CLI/MCP first; WebSearch fills genuine gaps (PMI, sector outlook). Every figure footnoted to its source. Auto-switches model for banks / insurance / REITs and flags <2y IPOs and suspended names. Triggers: "格雷厄姆筛选", "格雷厄姆选股", "捡烟蒂榜单", "烟蒂股榜", "NCAV筛选", "NCAV排行榜", "净流动资产筛选", "防御型投资者选股", "撿煙蒂榜單", "煙蒂股榜", "NCAV篩選", "淨流動資產篩選", "防禦型投資者選股", "Graham screen", "Graham screener", "NCAV screen", "net-net screen", "net-net list", "cigar-butt screen", "defensive investor screen", "liquidation value screen", "Benjamin Graham screen".
Deep formal test smell audit based on academic research taxonomy (testsmells.org). Detects 19 categorized smell types — conditional logic, mystery guests, sensitive equality, eager tests, and more — with calibrated severity and research-backed remediation. Use for comprehensive test suite health assessments. For a quick pragmatic review, use test-anti-patterns instead. DO NOT USE FOR: writing new tests (use writing-mstest-tests), evaluating assertion quality specifically (use assertion-quality), or finding test duplication and boilerplate (use exp-test-maintainability).
Update Margin Dashboard with Fidelity balance data and calculate margin-living strategy metrics. Monitors margin balance, interest costs, coverage ratios, and scaling thresholds. Triggers safety alerts for large draws and provides time-based scaling recommendations. Use when updating margin, balances, coverage ratio, or margin strategy analysis.
Lets end users add, authenticate, and manage MCP servers from the browser in assistant-ui apps with @assistant-ui/react-mcp. Use when building user-managed MCP server UIs: mounting McpManagerResource via useAui({ mcp }), declaring presets with defineConnector, dropping in McpConfigDialog, or composing McpManagerPrimitive (Root, Connectors, CustomServers, AddCustomTrigger), McpServerPrimitive (Root, Name, Icon, Status, ConnectButton, DisconnectButton, OAuthLink, RemoveButton, Error), and McpAddFormPrimitive (NameField, UrlField, AuthSelect, AuthFields, Submit, Cancel). Covers auth modes none/bearer/oauth, the OAuth flow with McpOAuthCallback, connection states, storage via McpLocalStorage/McpMemoryStorage/McpCustomStorage, reading state with useAuiState (s.mcp, s.mcpServer), and imperative addCustomServer/connect/callTool. Distinct from developer-defined backend @ai-sdk/mcp tools in the tools skill. Reach for this when connected-server tools are missing, OAuth never completes, or servers do not persist.