/strategize
Design identification strategy or pre-analysis plan. Dispatches Strategist (proposer) and strategist-critic (validator). Replaces /identify and /pre-analysis-plan.
$ npx -y skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill strategize --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
- Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
- You can call itInvoke it directly when you want it.
- Slash command
/strategize
Context preview
The summary Claude sees to decide when to auto-load this skill.
Design identification strategy or pre-analysis plan. Dispatches Strategist (proposer) and strategist-critic (validator). Replaces /identify and /pre-analysis-plan.
SKILL.md
strategize.SKILL.mdname: strategize
description: Design identification strategy or pre-analysis plan. Dispatches Strategist (proposer) and strategist-critic (validator). Replaces /identify and /pre-analysis-plan.
argument-hint: "[mode: strategy | pap | pap interactive] [research question or spec path]"
allowed-tools: Read,Grep,Glob,Write,Task
Strategize
Design an identification strategy or pre-analysis plan by dispatching the **Strategist** (proposer) and **strategist-critic** (validator).
**Input:** `$ARGUMENTS` — mode keyword followed by research question or path to research spec.
---
Modes
`/strategize [question]` or `/strategize strategy [question]` — Identification Strategy
Design the causal identification strategy.
**Agents:** Strategist → strategist-critic **Output:** Strategy memo + robustness plan + falsification tests
Workflow: 1. Read research spec, literature review, and data assessment if they exist 2. Read .claude/references/domain-profile.md for common identification strategies in the field 3. Dispatch Strategist to produce:
- Strategy memo: design choice, estimand, assumptions, comparison group
- Pseudo-code: implementation sketch
- Robustness plan: ordered list of checks with rationale
- Falsification tests: what SHOULD NOT show effects
- Referee objection anticipation: top 5 objections with responses
4. Dispatch strategist-critic to review through 4 phases:
- Phase 1: Claim identification (design, estimand, treatment, control)
- Phase 2: Core design validity (assumption checks, sanity checks)
- Phase 3: Inference soundness (clustering, multiple testing)
- Phase 4: Polish and completeness (robustness, citations)
5. If CRITICAL issues found, iterate (max 3 rounds per three-strikes) 6. Save memo to `quality_reports/strategy_memo_[topic].md` 7. Save review to `quality_reports/strategy_memo_[topic]_review.md`
`/strategize pap [spec]` — Pre-Analysis Plan
Draft a pre-analysis plan following AEA/OSF/EGAP standards.
**Input:** `$ARGUMENTS` — path to research spec file, a topic, or `interactive` for guided interview.
- If `$ARGUMENTS` includes a file path: read it (research spec from `/discover interview`)
- If `$ARGUMENTS` includes `interactive`: conduct the guided PAP interview (see below)
- Otherwise: treat as topic and draft with ASSUMED placeholders marked clearly
**Agents:** Strategist (in PAP mode), optionally strategist-critic **Output:** Pre-analysis plan document
Interactive PAP Interview (6-Question Guided Flow)
When invoked as `/strategize pap interactive`, ask these questions one at a time before drafting:
1. **What is the research question?** 2. **What is the study design?** (RCT / natural experiment / quasi-experimental / observational) 3. **What are the primary outcome variables?** (names, measurement, data source) 4. **What is the identification strategy?** (randomization mechanism / treatment assignment / source of variation) 5. **What subgroup analyses are pre-specified?** (with justification for each) 6. **What multiple testing concerns exist?** (number of primary outcomes, family-wise error rate plan)
After all 6 answers are collected, proceed to PAP drafting.
PAP Sections
Dispatch Strategist in PAP mode to produce all standard sections:
1. **Study overview** — research question, design, treatment, control 2. **Outcomes** — primary, secondary, mechanism variables with measurement details 3. **Estimating equations** — with full notation protocol 4. **Subgroup analyses** — pre-specified, with justification for each 5. **Multiple testing correction** — Bonferroni / Benjamini-Hochberg / Romano-Wolf (specify which and why) 6. **Power calculations** — MDE, baseline statistics, sample size, assumptions stated explicitly with sensitivity 7. **Sample and exclusion rules** — inclusion criteria, attrition handling, outlier treatment 8. **Data and analysis** — sources, software, randomization/assignment mechanism 9. **Timeline** — data collection, analysis, registration dates 10. **Deviations log** — empty template for tracking post-registration changes
Platform-Specific PAP Templates
Ask the user which registry platform they plan to use (if unclear from context):
**AEA RCT Registry:**
- Most structured format. All fields required.
- Must be registered before intervention begins.
- Strict section ordering: hypotheses → outcomes → analysis → power.
- Requires IRB information and funding sources.
**OSF (Open Science Framework):**
- More flexible format. Good for observational studies and natural experiments.
- Allows iterative updates with version history.
- Less rigid section structure — can adapt to study design.
- Supports pre-registration of observational/archival studies.
**EGAP (Evidence in Governance and Politics):**
- Development economics and political science focused.
- Additional governance and ethics questions required.
- Emphasizes pre-specification of heterogeneous treatment effects.
- Requires description of implementing partners and field conditions.
Observational Study PAP Adaptation
For observational, quasi-experimental, or natural experiment designs, adapt the PAP template:
- **Identification strategy replaces randomization** — describe the source of exogenous variation
- **Comparison group replaces control group** — define who is compared to whom and why
- **Identification assumption discussion** — explicitly state and defend each assumption
- **Placebo and falsification tests** — pre-specify what SHOULD NOT show effects
- **Robustness to specification choices** — pre-commit to bandwidth, functional form, sample restrictions
- **Treatment of endogeneity concerns** — document known threats and planned diagnostics
ASSUMED Placeholder Safety
**CRITICAL: Flag every ASSUMED item clearly. The researcher must review and approve before registration.**
When drafting a PAP from a topic (without a full research spec or interactive interview), many details will be assumed. For each
Read more
name: strategize description: Design identification strategy or pre-analysis plan. Dispatches Strategist (proposer) and strategist-critic (validator). Replaces /identify and /pre-analysis-plan. argument-hint: "[mode: strategy | pap | pap interactive] [research question or spec path]" allowed-tools: Read,Grep,Glob,Write,Task
Strategize
Design an identification strategy or pre-analysis plan by dispatching the **Strategist** (proposer) and **strategist-critic** (validator).
**Input:** `$ARGUMENTS` — mode keyword followed by research question or path to research spec.
---
Modes
`/strategize [question]` or `/strategize strategy [question]` — Identification Strategy
Design the causal identification strategy.
**Agents:** Strategist → strategist-critic **Output:** Strategy memo + robustness plan + falsification tests
Workflow: 1. Read research spec, literature review, and data assessment if they exist 2. Read .claude/references/domain-profile.md for common identification strategies in the field 3. Dispatch Strategist to produce:
- Strategy memo: design choice, estimand, assumptions, comparison group
- Pseudo-code: implementation sketch
- Robustness plan: ordered list of checks with rationale
- Falsification tests: what SHOULD NOT show effects
- Referee objection anticipation: top 5 objections with responses
4. Dispatch strategist-critic to review through 4 phases:
- Phase 1: Claim identification (design, estimand, treatment, control)
- Phase 2: Core design validity (assumption checks, sanity checks)
- Phase 3: Inference soundness (clustering, multiple testing)
- Phase 4: Polish and completeness (robustness, citations)
5. If CRITICAL issues found, iterate (max 3 rounds per three-strikes) 6. Save memo to `quality_reports/strategy_memo_[topic].md` 7. Save review to `quality_reports/strategy_memo_[topic]_review.md`
`/strategize pap [spec]` — Pre-Analysis Plan
Draft a pre-analysis plan following AEA/OSF/EGAP standards.
**Input:** `$ARGUMENTS` — path to research spec file, a topic, or `interactive` for guided interview.
- If `$ARGUMENTS` includes a file path: read it (research spec from `/discover interview`)
- If `$ARGUMENTS` includes `interactive`: conduct the guided PAP interview (see below)
- Otherwise: treat as topic and draft with ASSUMED placeholders marked clearly
**Agents:** Strategist (in PAP mode), optionally strategist-critic **Output:** Pre-analysis plan document
Interactive PAP Interview (6-Question Guided Flow)
When invoked as `/strategize pap interactive`, ask these questions one at a time before drafting:
1. **What is the research question?** 2. **What is the study design?** (RCT / natural experiment / quasi-experimental / observational) 3. **What are the primary outcome variables?** (names, measurement, data source) 4. **What is the identification strategy?** (randomization mechanism / treatment assignment / source of variation) 5. **What subgroup analyses are pre-specified?** (with justification for each) 6. **What multiple testing concerns exist?** (number of primary outcomes, family-wise error rate plan)
After all 6 answers are collected, proceed to PAP drafting.
PAP Sections
Dispatch Strategist in PAP mode to produce all standard sections:
1. **Study overview** — research question, design, treatment, control 2. **Outcomes** — primary, secondary, mechanism variables with measurement details 3. **Estimating equations** — with full notation protocol 4. **Subgroup analyses** — pre-specified, with justification for each 5. **Multiple testing correction** — Bonferroni / Benjamini-Hochberg / Romano-Wolf (specify which and why) 6. **Power calculations** — MDE, baseline statistics, sample size, assumptions stated explicitly with sensitivity 7. **Sample and exclusion rules** — inclusion criteria, attrition handling, outlier treatment 8. **Data and analysis** — sources, software, randomization/assignment mechanism 9. **Timeline** — data collection, analysis, registration dates 10. **Deviations log** — empty template for tracking post-registration changes
Platform-Specific PAP Templates
Ask the user which registry platform they plan to use (if unclear from context):
**AEA RCT Registry:**
- Most structured format. All fields required.
- Must be registered before intervention begins.
- Strict section ordering: hypotheses → outcomes → analysis → power.
- Requires IRB information and funding sources.
**OSF (Open Science Framework):**
- More flexible format. Good for observational studies and natural experiments.
- Allows iterative updates with version history.
- Less rigid section structure — can adapt to study design.
- Supports pre-registration of observational/archival studies.
**EGAP (Evidence in Governance and Politics):**
- Development economics and political science focused.
- Additional governance and ethics questions required.
- Emphasizes pre-specification of heterogeneous treatment effects.
- Requires description of implementing partners and field conditions.
Observational Study PAP Adaptation
For observational, quasi-experimental, or natural experiment designs, adapt the PAP template:
- **Identification strategy replaces randomization** — describe the source of exogenous variation
- **Comparison group replaces control group** — define who is compared to whom and why
- **Identification assumption discussion** — explicitly state and defend each assumption
- **Placebo and falsification tests** — pre-specify what SHOULD NOT show effects
- **Robustness to specification choices** — pre-commit to bandwidth, functional form, sample restrictions
- **Treatment of endogeneity concerns** — document known threats and planned diagnostics
ASSUMED Placeholder Safety
**CRITICAL: Flag every ASSUMED item clearly. The researcher must review and approve before registration.**
When drafting a PAP from a topic (without a full research spec or interactive interview), many details will be assumed. For each
📌 文档结构(2026-07-22 起): 本文件是中文默认入口 —— banner + badges + 信任面 + 9 阶段流水线速览 + 76 行合集总表。 每个合集的完整描述、按用途分组、精确数字、验证方法在 docs/CONTENT_ZH.md(扩展正文,总表行内的 → 直接跳转到对应锚点)。 English version: README-en.md · 中文扩展正文:docs/CONTENT_ZH.md · README-zh-CN.md 已弃用(重定向占位) 🌐 语言: English |
Other skills on auto-empirical-research-skills.
- /pipeline
Classical end-to-end empirical analysis workflow in the traditional Python econometric stack — pandas + numpy + scipy + statsmodels + linearmodels + pyfixest + rdrobust + econml + causalml + matplotlib/seaborn. **Defaults to economics empirical-paper style** (AER / QJE / AEJ) —
Open skill - /pipeline
Classical end-to-end empirical analysis workflow in the modern tidyverse + econometrics R ecosystem — dplyr + tidyr + haven + fixest + sandwich + lmtest + clubSandwich + AER + ivreg + did + bacondecomp + HonestDiD + eventstudyr + rdrobust + rddensity + Synth + gsynth + synthdid
Open skill - /pipeline
Classical end-to-end empirical analysis workflow in the traditional Stata ecosystem — native Stata + reghdfe + ivreg2 + csdid + did_imputation + eventstudyinteract + sdid + rdrobust + rddensity + synth + synth_runner + psmatch2 + teffects + ebalance + coefplot + esttab + asdoc +
Open skill - /00-Full-empirical-analysis-skill_StatsPAI
Use when the user asks to run a full empirical / causal analysis in Python — by default in the style of an applied economics paper (AER / QJE / JPE / ReStud / AEJ) with DID / RD / IV / SCM / DML / matching, written-out estimating equation + identifying assumption, Table 1 /
Open skill - /00.1-Full-empirical-analysis-skill_Python
Classical end-to-end empirical analysis workflow in the traditional Python econometric stack — pandas + numpy + scipy + statsmodels + linearmodels + pyfixest + rdrobust + econml + causalml + matplotlib/seaborn. **Defaults to economics empirical-paper style** (AER / QJE / AEJ) —
Open skill - /00.2-Full-empirical-analysis-skill_Stata
Classical end-to-end empirical analysis workflow in the traditional Stata ecosystem — native Stata + reghdfe + ivreg2 + csdid + did_imputation + eventstudyinteract + sdid + rdrobust + rddensity + synth + synth_runner + psmatch2 + teffects + ebalance + coefplot + esttab + asdoc +
Open skill

