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Found 1,126 Skills
Plan and run campaign-level marketing asset production with genmedia. Use this for launch kits, campaign matrices, paid social variants, landing-page visuals, email and banner imagery, hook/proof/conversion assets, creator ad packages, and channel-specific marketing deliverables.
Use when naming or renaming TypeScript identifiers, especially cryptic names, ambiguous parameters, I-prefixed interfaces, Hungarian notation, misleading side effects, or requests for clearer names.
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.
Modify an existing SigNoz dashboard — add or remove panels, edit a panel's query, threshold, or unit, rename the dashboard, change a panel type (graph ↔ table ↔ value), rearrange the layout, add or edit variables, or update tags. Make sure to use this skill whenever the user says "add a panel to my dashboard", "change the query on this panel", "remove the latency widget", "rename my dashboard", "update the filters", "rearrange the layout", "add a variable", "change panel type from graph to table", or otherwise asks to change something on a dashboard that already exists — even if they don't say "modify" or "edit" explicitly.
Design and engineer System Prompts, prompt templates, and multi-agent orchestration contracts for deterministic, leak-proof AI systems. Use when creating agents, writing skill definitions, designing prompt templates with safe variable injection, structuring I/O contracts, or building multi-agent pipelines.
Use when the user wants to author, refine, or audit a Product Requirements Document for AI coding agents. Walks through an 8-phase pipeline (Socratic discovery → PRD draft → acceptance criteria → adversarial review → task decomposition → AI-readiness gate → test generation → handoff). Triggers on "write a PRD", "spec this feature", "draft requirements", "prepare X for Claude/Cursor/Copilot/Windsurf/Aider to build", "audit my PRD", "is this PRD AI-ready", "score this spec".
Connect to MotherDuck from any application. Use when setting up database connectivity via the Postgres endpoint (recommended), pg_duckdb, native DuckDB API, or JDBC. Covers connection strings, authentication, SSL, and environment variable configuration.
Execute mcloud environments commands to list, get, create, delete, redeploy, or trigger builds for Cloud environments. Use when managing environment lifecycle, redeploying after variable changes, or starting new builds from source.
Turn vague product, offer, benchmark, or campaign inputs into high-quality short-form script objects for AI UGC videos and TikTok or Instagram slideshows. Use this when the user needs hook variants, script variants, slideshow flows, reveal timing, proof logic, and downstream handoff artifacts rather than one-off copy. This skill should guide weak inputs into testable scripts, not merely rewrite them more naturally.
Build and validate HelixDB dynamic inline-query requests for POST /v1/query. Use when the task involves dynamic queries, inline query JSON, the inline AST (steps, predicates, expressions, projections), parameter_types, DateTime coercion, query warming, or debugging a request body sent directly to the Helix gateway. See REFERENCE.md for every AST variant and EXAMPLES.md for copy-pasteable payloads.
Asset allocation and portfolio optimisation via Longbridge — efficient frontier (MPT), Black-Litterman model overview, risk parity / risk budgeting, all-weather strategy, and practical allocation recommendations based on the user's Longbridge account data. Triggers: "资产配置", "组合优化", "有效前沿", "Black-Litterman", "风险预算", "风险平价", "全天候策略", "大类资产", "資產配置", "組合優化", "有效前沿", "風險預算", "風險平價", "全天候策略", "大類資產", "asset allocation", "portfolio optimization", "efficient frontier", "Black-Litterman", "risk parity", "all-weather strategy", "mean-variance optimization", "strategic allocation".
Risk-return optimisation for investment portfolios via Longbridge — builds risk-adjusted return-optimal portfolios based on fund size, risk preference (conservative / balanced / aggressive), and investment horizon. Asset allocation across equities / bonds / cash / commodities / alternatives. Evaluates current portfolio efficiency versus the efficient frontier. Triggers: "风险收益优化", "组合效率", "有效前沿", "风险偏好配置", "最优组合", "风险调整收益", "大类资产配置", "投资组合优化", "風險收益優化", "組合效率", "有效前沿", "風險偏好配置", "最優組合", "risk-return optimization", "portfolio efficiency", "efficient frontier", "risk preference", "optimal portfolio", "risk-adjusted return", "asset class allocation", "portfolio optimisation", "mean variance".