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Found 36 Skills
Evaluate investment performance on a risk-adjusted basis using industry-standard ratios and capture analysis. Use when the user asks about Sharpe ratio, Sortino ratio, Information Ratio, Treynor ratio, Calmar ratio, Omega ratio, or upside/downside capture. Also trigger when users mention 'risk-adjusted returns', 'return per unit of risk', 'M-squared', 'is this fund worth the volatility', 'how to compare two managers', 'capture ratio', or ask which investment performed better after accounting for risk.
Orchestrates comprehensive performance audits across full-stack monorepos. Coordinates performance-expert, design-consistency-auditor, accessibility, security-expert, and qa-reviewer skills to audit frontend, backend, database, browser extensions, and shared packages.
Run the trigger evaluation pipeline — classify, analyze, and optionally compare against a baseline. Only run when explicitly asked — evals are expensive.
Reflect, Evaluate, Fine-tune, Learn, Evolve, Correct, Transform — nightly automated performance review
Monitor application errors, performance, and issues on Sentry
Monitor Render services in real-time. Check health, performance metrics, logs, and resource usage. Use when users want to check service status, view metrics, monitor performance, or verify deployments are healthy.
Manage power and performance metrics and diagnostic logs using the `asc` CLI tool. Use this skill when: (1) Listing performance metrics for an app: "asc perf-metrics list --app-id <id>" (2) Listing performance metrics for a build: "asc perf-metrics list --build-id <id>" (3) Filtering metrics by type: "asc perf-metrics list --app-id <id> --metric-type LAUNCH" (4) Listing diagnostic signatures for a build: "asc diagnostics list --build-id <id>" (5) Filtering diagnostics: "asc diagnostics list --build-id <id> --diagnostic-type HANGS" (6) Viewing diagnostic logs: "asc diagnostic-logs list --signature-id <id>" Also trigger when the user mentions: performance metrics, launch time, hang rate, disk writes, memory usage, battery life, termination, animation hitches, diagnostic signatures, call stacks, power metrics, app performance monitoring, "why is my app slow", "check hangs", "check launch time"
Expert data analysis and manipulation for customer support operations using pandas
Backtest crypto and traditional trading strategies against historical data. Calculates performance metrics (Sharpe, Sortino, max drawdown), generates equity curves, and optimizes strategy parameters. Use when user wants to test a trading strategy, validate signals, or compare approaches. Trigger with phrases like "backtest strategy", "test trading strategy", "historical performance", "simulate trades", "optimize parameters", or "validate signals".
Use when the user asks to "analyze influencer campaign performance", "compare influencers", or "find what content worked"; produces metric scorecards vs target and benchmark, platform/influencer/content rankings, engagement-quality and sentiment reads, conversion-attribution breakdowns, and ranked learnings. Not for dollar-level return math — use roi-calculator. 达人营销效果分析/投放复盘
Agent skill for performance-analyzer - invoke with $agent-performance-analyzer
搜索和分析TikTok视频数据，按区域、达人、商品、类目、播放量、时长、发布时间、是否带货/投流/AI视频等条件筛选视频，返回播放量、点赞、评论、分享、收藏、视频销量与GMV等指标，覆盖16个TikTok Shop站点。当用户提到TikTok视频搜索、TikTok视频列表、TikTok带货视频、TikTok视频数据、TikTok视频播放量、TikTok视频销量、TikTok视频分析、EchoTik视频、TikTok video search, TikTok video list, TikTok video analytics, TikTok promotional videos, TikTok video views, TikTok video engagement时触发此技能。即使用户未明确提及"EchoTik"或"TikTok"，只要其需求涉及按条件搜索或分析TikTok视频表现指标，也应触发此技能。