「outcomes」の検索結果

Define UX metrics and KPIs that connect design decisions to measurable business and user outcomes.

日本語の概要は準備中です。原文の説明を表示しています。

Communicate design's contribution to business and user outcomes in terms that resonate with stakeholders.

日本語の概要は準備中です。原文の説明を表示しています。

Facilitate structured design critiques with clear feedback frameworks and actionable outcomes.

日本語の概要は準備中です。原文の説明を表示しています。

Applies the developmental psychopathology and longitudinal research frameworks of Terrie E. Moffitt (psychologist, Duke University). Use this skill whenever reasoning about human development, criminology, juvenile delinquency, self-control, mental health trajectories, or biological aging. Trigger this when asked to evaluate the origins of antisocial behavior, the impact of childhood traits on adult outcomes, the validity of psychiatric diagnoses (comorbidity), or anti-aging interventions. Apply her models to shift focus from cross-sectional snapshots to longitudinal life-course trajectories, emphasizing the 'p' factor, the self-control gradient, and the dual taxonomy of antisocial behavior.

日本語の概要は準備中です。原文の説明を表示しています。

Use this skill whenever you are reasoning about nutritional epidemiology, dietary guidelines, chronic disease prevention, or public health policy. It channels the thinking of Meir J. Stampfer, epidemiologist and nutrition expert at Harvard University. Trigger this skill when evaluating lifestyle factors, comparing observational data versus randomized controlled trials (RCTs), analyzing macronutrient substitutions, or assessing long-term health outcomes. Stampfer's approach is essential when users ask about "good" vs. "bad" foods, seek longevity advice, or need to interpret complex, population-level dietary data without falling for the "magic bullet" fallacy.

日本語の概要は準備中です。原文の説明を表示しています。

Inspect repository session replay and verify configured MetaHarness field memory boundaries before reusing outcomes.

日本語の概要は準備中です。原文の説明を表示しています。

Transform research into Opportunity Solution Tree (Teresa Torres method). Map outcomes, opportunities, solutions, and experiments.

日本語の概要は準備中です。原文の説明を表示しています。

Create structured records of decisions with expected outcomes, probabilities, and quit conditions. Use for important decisions.

日本語の概要は準備中です。原文の説明を表示しています。

Inspect repository session replay and verify configured MetaHarness field memory boundaries before reusing outcomes.

日本語の概要は準備中です。原文の説明を表示しています。

Before writing any implementation code, define the acceptance criteria and test cases that the code must satisfy. Agents then write code to pass these tests — not to match a vague description. Eliminates "it works on my machine" and "I think this is what you wanted" outcomes.

日本語の概要は準備中です。原文の説明を表示しています。

Generate a session report with token usage estimates, work summary, and outcomes

日本語の概要は準備中です。原文の説明を表示しています。

Use this when summarizing analysis results, writing reports, documenting experiment outcomes, or presenting model evaluation — including structuring findings in Japanese with conclusions, facts, assumptions, interpretations, and caveats.

日本語の概要は準備中です。原文の説明を表示しています。

Map evidence-based connections between a wellbeing initiative and specific academic learning outcomes. Use when justifying wellbeing programmes, integrating SEL, or linking pastoral and academic work.

日本語の概要は準備中です。原文の説明を表示しています。

Plan a unit using backwards design from desired outcomes through assessment evidence to learning activities. Use when starting a new unit or redesigning an existing one from standards.

日本語の概要は準備中です。原文の説明を表示しています。

Run metric-driven optimization loops. Use when improving measurable outcomes such as search relevance, clustering quality, build performance, prompt quality, or scored behavior through experiments.

日本語の概要は準備中です。原文の説明を表示しています。

Recommends team composition based on outcomes and mode. Invoked by launch commands during team setup.

日本語の概要は準備中です。原文の説明を表示しています。

General mode operational spec for the team lead. Returns lead identity, facilitator identity, suggest-members guidance, and phase arc for general-purpose teams. The silent fallback when outcomes fit no specific mode, and a wrapper base for custom workflows — it has no shortcut command.

日本語の概要は準備中です。原文の説明を表示しています。

Inspect repository session replay and verify configured MetaHarness field memory boundaries before reusing outcomes.

日本語の概要は準備中です。原文の説明を表示しています。

Schema for tracking code review outcomes to enable feedback-driven skill improvement. Use when logging review results or analyzing review quality.

日本語の概要は準備中です。原文の説明を表示しています。

Causal reasoning in historical analysis. Covers distinguishing immediate from underlying causes, tracing chains of causation across time scales, identifying unintended consequences, and applying counterfactual reasoning to assess causal significance. Use when analyzing why historical events occurred, evaluating the relative weight of causes, or assessing whether outcomes were inevitable or contingent.

日本語の概要は準備中です。原文の説明を表示しています。

A/B testing, randomization, sample size calculation, confounding control, and causal inference for data science. Covers the full experimental lifecycle from hypothesis formulation through power analysis, randomization strategies, blocking, factorial designs, sequential testing, and the potential outcomes framework for causal claims. Use when designing experiments, planning A/B tests, calculating sample sizes, or reasoning about causation from data.

日本語の概要は準備中です。原文の説明を表示しています。

Structured approaches to decisions under uncertainty and complexity. Covers expected value, decision trees, multi-criteria decision analysis, System 1 vs System 2 allocation, pre-mortems, reversible vs irreversible decisions, and the distinction between good decisions and good outcomes. Use when choosing among alternatives with uncertain or multi-dimensional consequences, especially when the stakes justify a deliberate rather than intuitive process.

日本語の概要は準備中です。原文の説明を表示しています。

Generate professional clinical decision support (CDS) documents for pharmaceutical and clinical research settings, including patient cohort analyses (biomarker-stratified with outcomes) and treatment recommendation reports (evidence-based guidelines with decision algorithms). Supports GRADE evidence grading, statistical analysis (hazard ratios, survival curves, waterfall plots), biomarker integration, and regulatory compliance. Outputs publication-ready LaTeX/PDF format optimized for drug development, clinical research, and evidence synthesis.

日本語の概要は準備中です。原文の説明を表示しています。

Certifies that a feature achieves its original objectives via goal-backward verification (SAM Stage 7). Use when all tasks pass forensic review — starts from expected outcomes, works backwards to verify each was achieved, and returns CERTIFIED or NOT_CERTIFIED with specific gaps.

日本語の概要は準備中です。原文の説明を表示しています。