本文へ移動
cccskills
無料GitHub で公開

designing-experiments

Design experiments and quasi-experiments before analysis. Use when choosing study design, treatment/control structure, outcomes, assumptions, validation plans after scientific experiment failure, or which of DiD, ITS, synthetic control, or regression discontinuity fits the research question. For fitting models or estimating effects on existing data, use performing-causal-analysis instead.

インストール方法を見る

含まれるファイル(1)

  • SKILL.md2.3 KB

SKILL.md(原文)

インストールする前に、エージェントに与えられる指示の中身を確認できます。

Designing Experiments

Helps choose and specify a research design before data analysis starts. This skill owns study-design decisions: what is treated, what is compared, what outcome is measured, which assumptions are required, which validation or recovery experiment should follow a failed scientific experiment, and which design is defensible.

It does not fit causal models, estimate treatment effects, interpret fitted model output from existing data, or debug software/build failures.

Decision Framework

  1. Control Group?

    • Yes: Go to Step 2.
    • No: Consider Interrupted Time Series (ITS).
  2. Unit Structure?

    • Single Treated Unit:
      • With multiple controls: Synthetic Control (SC).
      • No controls: ITS.
    • Multiple Treated Units:
      • With control group: Difference-in-Differences (DiD).
  3. Time Structure?

    • Panel Data (Multiple units over time): Required for DiD and SC.
    • Time Series (Single unit over time): Required for ITS.

Method Quick Reference

  • Difference-in-Differences (DiD): Compares trend changes between treated and control groups. Assumes Parallel Trends.
  • Interrupted Time Series (ITS): Analyzes trend/level change for a single unit after intervention. Assumes Trend Continuity.
  • Synthetic Control (SC): Constructs a synthetic counterfactual from weighted control units. Assumes Convex Hull (treated unit within range of controls).

Failed Experiment Recovery

When a scientific experiment or optimization plan produces weak or contradictory results, use the same design surface to:

  • Separate implementation or measurement errors from design-assumption failures.
  • Identify which assumption should be tested next.
  • Define a minimal validation experiment before abandoning the approach.
  • State the decision rule for continuing, revising, or stopping the line of work.

レビュー

まだレビューはありません。使ってみた感想をお寄せください。

同じリポジトリのスキル

概要と使いどころ

adaptyv

無料

Cloud laboratory platform for automated protein testing and validation. Use when designing proteins and needing experimental validation including binding assays, expression testing, thermostability measurements, enzyme activity assays, or protein sequence optimization. Also use for submitting experiments via API, tracking experiment status, downloading results, optimizing protein sequences for better expression using computational tools (NetSolP, SoluProt, SolubleMPNN, ESM), or managing protein design workflows with wet-lab validation.

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。

foryourhealth111-pixel/Vibe-Skills3,6742026年8月31日 更新

aeon

無料

This skill should be used for time series machine learning tasks including classification, regression, clustering, forecasting, anomaly detection, segmentation, and similarity search. Use when working with temporal data, sequential patterns, or time-indexed observations requiring specialized algorithms beyond standard ML approaches. Particularly suited for univariate and multivariate time series analysis with scikit-learn compatible APIs.

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。

foryourhealth111-pixel/Vibe-Skills3,6742026年8月31日 更新

Creating algorithmic art using p5.js with seeded randomness and interactive parameter exploration. Use this when users request creating art using code, generative art, algorithmic art, flow fields, or particle systems. Create original algorithmic art rather than copying existing artists' work to avoid copyright violations.

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。

foryourhealth111-pixel/Vibe-Skills3,6742026年8月31日 更新

Access real-time and historical stock market data, forex rates, cryptocurrency prices, commodities, economic indicators, and 50+ technical indicators via the Alpha Vantage API. Use when fetching stock prices (OHLCV), company fundamentals (income statement, balance sheet, cash flow), earnings, options data, market news/sentiment, insider transactions, GDP, CPI, treasury yields, gold/silver/oil prices, Bitcoin/crypto prices, forex exchange rates, or calculating technical indicators (SMA, EMA, MACD, RSI, Bollinger Bands). Requires a free API key from alphavantage.co.

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。

foryourhealth111-pixel/Vibe-Skills3,6742026年8月31日 更新

Implement proven backend architecture patterns including Clean Architecture, Hexagonal Architecture, and Domain-Driven Design. Use when architecting complex backend systems or refactoring existing applications for better maintainability.

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。

foryourhealth111-pixel/Vibe-Skills3,6742026年8月31日 更新

astropy

無料

Comprehensive Python library for astronomy and astrophysics. This skill should be used when working with astronomical data including celestial coordinates, physical units, FITS files, cosmological calculations, time systems, tables, world coordinate systems (WCS), and astronomical data analysis. Use when tasks involve coordinate transformations, unit conversions, FITS file manipulation, cosmological distance calculations, time scale conversions, or astronomical data processing.

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。

foryourhealth111-pixel/Vibe-Skills3,6742026年8月31日 更新

foryourhealth111-pixel のスキルをすべて見る

このスキルの問題を報告する