Results for “design-metrics”

Design DEI strategies with metrics. TRIGGERS - Use when user needs help with dei-strategy related tasks.

Design DEI strategies with metrics. TRIGGERS - Use when user needs help with dei-strategy related tasks.

Design production-ready observability strategies combining metrics, logs, and traces, including SLI/SLO design, golden-signals monitoring, and alert optimization.

Lead customer experience with journey mapping, voice of customer programs, service design, and experience metrics.

Designs an A/B test or experiment with clear hypothesis, variants, success metrics, sample size, and duration. Use when planning experiments to validate product changes or test hypotheses.

Author/validate/export Google's DESIGN.md token spec files.

Author/validate/export Google's DESIGN.md token spec files.

Author, lint, diff, and export Google's DESIGN.md design token spec files, including WCAG contrast validation.

Design MOOCs with scalable engagement. TRIGGERS - Use when user needs help with mooc-design related tasks.

Design, prioritize, and evaluate product experiments with clear hypotheses and defensible decisions, including A/B testing, sample size estimation, and statistical interpretation.

Author/validate/export Google's DESIGN.md token spec files.

Calculate portfolio risk metrics including VaR, CVaR, Sharpe, Sortino, and drawdown analysis. Use when measuring portfolio risk, implementing risk limits, or building risk monitoring systems.

Design MOOCs with scalable engagement. TRIGGERS - Use when user needs help with mooc-design related tasks.

Design decentralized exchanges. TRIGGERS - Use when user needs help with dex-design related tasks.

Design decentralized exchanges. TRIGGERS - Use when user needs help with dex-design related tasks.

Design 360-degree feedback programs with surveys. TRIGGERS - Use when user needs help with 360-feedback related tasks.

Design pricing, packaging, and monetization strategies that capture value and align with customer willingness to pay.

ateam-design

阶段② 详细设计。根据 design.md 第一章补全第二章各模块设计 + 第四章 ADR。

Defines a testable hypothesis with clear success metrics and validation approach. Use when forming assumptions to test, designing experiments, or aligning team on what success looks like.

Structures product requirements into a single-page spec with problem, success metrics, scope, user stories, design notes, and rollout plan.

Build reproducible ML experiment plans with hypotheses, metrics, and ablations. Use when: (1) planning experiments, (2) comparing variants, (3) defining acceptance thresholds. NOT for: long-running experiment execution.

World-class level design expertise - spatial storytelling, player flow, blockout methodology, and the invisible hand that guides players without them knowingUse when "level design, blockout, graybox, whitebox, player flow, level layout, combat arena, exploration space, map design, multiplayer map, pacing, weenie, landmark, gating, metroidvania, open world design, linear level, environmental storytelling, teaching through design, playtesting, heatmap, metrics, sightlines, level-design, game-development, spatial-design, blockout, graybox, player-flow, pacing, environmental-storytelling, combat-design, multiplayer-maps, open-world, linear-design, metroidvania" mentioned.

Design value-based pricing, packaging, and monetization strategies for SaaS products, including tier structures, value metrics, and price optimization.

Use this skill when the user asks how to design or improve a fleet safety scorecard — what KPIs to track, how to weight them, telematics signals vs document compliance vs roadside outcomes, monthly cadence, driver-facing vs admin-facing dashboards, gamification considerations, peer-comparison metrics, and how a scorecard ties to insurance premiums + retention. Reference SMS Methodology v3.20 for industry-standard weights.

Comprehensive QA and testing skill for quality assurance, test automation, and testing strategies for ReactJS, NextJS, NodeJS applications. Includes test suite generation, coverage analysis, E2E testing setup, and quality metrics. Use when designing test strategies, writing test cases, implementing test automation, performing manual testing, or analyzing test coverage.

Write a rigorous, decision-grade experiment spec — falsifiable hypothesis, primary metric, guardrails, randomisation unit, exposure definition, method (A/B, holdout, switchback, quasi-experiment, MAB), MDE/duration plan, peek policy, validity threats, and pre-committed decision rule. Platform-agnostic. Load when the user has a candidate experiment and needs to spec it before launch, or says "spec this experiment", "write the test plan", "design this A/B test", "what's the hypothesis", "how big a sample do we need", "how long should we run this", "define the metrics for this test", or when the experimentation orchestrator routes here.