alterlab-ssci-design-gate

name	alterlab-ssci-design-gate
description	Routes a social-science study to its research design — true experiment, quasi-experiment (difference-in-differences, instrumental variables, regression discontinuity, interrupted time series, fixed effects), observational/correlational, qualitative, or mixed — by walking the random-selection and random-assignment decisions, then PINS the identifying assumption the causal claim will rest on (parallel trends, exclusion restriction, continuity at the cutoff, selection-on-observables, or qualitative saturation logic) before any analysis begins. Use when choosing a study design, asking what design to use, framing a causal question from observational data, or deciding experiment vs quasi-experiment vs observational. For executing the analysis prefer alterlab-statistical-analysis; for qualitative design depth prefer alterlab-qualitative-methods; for choosing the statistical test downstream prefer alterlab-test-selection-guard. Part of the AlterLab Academic Skills suite.
license	MIT
allowed-tools	Read Bash(python:*)
compatibility	No API key required. A discipline-enforcing design-routing skill; the optional decision-tree helper runs locally via `uv run python` (standard library only).
metadata	{"skill-author":"AlterLab","version":"1.0.0","depends_on":"alterlab-qualitative-methods, alterlab-mixed-methods, alterlab-statistical-analysis, alterlab-test-selection-guard; hands the pinned assumption to alterlab-ssci-inference-gate"}

Design Gate — Pin the Identifying Assumption Before Anything Else

Skill type: DISCIPLINE-ENFORCING. This is the entry point of the social-science methods spine, not an analysis engine. It routes a study to the right design family and forces the one decision every downstream gate depends on: what identifying assumption licenses the causal claim? It does not run models — for execution it hands off to the analysis skills.

The Core Rule

A CAUSAL CLAIM IS ONLY AS GOOD AS ITS IDENTIFYING ASSUMPTION — NAME IT FIRST.

Design is chosen by the question and the data-generating process — who was selected, who was assigned, what varies and when — not by which method is fashionable or convenient. A quasi-experiment is an observational design that earns a causal interpretation only by committing, up front, to an assumption that makes the effect identified. State that assumption before touching an estimator; if you cannot defend one, the claim is associational, not causal.

When to Use This Skill

Trigger the design gate whenever a design is being chosen, defended, or implied by a claim:

• "What research design should I use for this question?"
• "I have observational survey data and want to claim X improves Y." (← pin the assumption)
• "Should this be an experiment or a quasi-experiment?"
• "Can a difference-in-differences / IV / regression-discontinuity design answer this?"
• "Is my before/after comparison enough to claim the program worked?"

Does NOT Trigger

Route these adjacent requests to the real sibling skill. This gate picks the design and pins the assumption; it does not execute, choose the test, or write.

The request is really about…	Route to	Why not this skill
Running the analysis / a specific model once the design is fixed	alterlab-statistical-analysis / alterlab-statsmodels	Execution, not design choice.
Which statistical test to use (t-test vs Mann-Whitney, etc.)	alterlab-test-selection-guard	Test choice is downstream of design.
Deep qualitative design (grounded theory, phenomenology, coding)	alterlab-qualitative-methods	This gate only routes to qual; that skill does it.