pipeline
Classical end-to-end empirical analysis workflow in the traditional Python econometric stack — pandas + numpy + scipy + statsmodels + linearmodels + pyfixest +…
Explore methodological approaches through structured analysis before planning implementation
$ npx -y skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill workflows-brainstorm --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/workflows-brainstormContext preview
The summary Claude sees to decide when to auto-load this skill.
Explore methodological approaches through structured analysis before planning implementation
name: workflows:brainstorm description: Explore methodological approaches through structured analysis before planning implementation argument-hint: "<research question or methodological problem>" allowed-tools: Read, Glob, Bash
**Pipeline mode:** This command operates fully autonomously. All decisions are made automatically.
Brainstorming helps answer **WHAT** approach to take through structured analysis. It precedes `/workflows:plan`, which answers **HOW** to implement it.
**Process knowledge:** See `references/brainstorming-techniques.md` for detailed question techniques, approach exploration patterns, and parsimony principles.
<feature_description> #$ARGUMENTS </feature_description>
**If the research question above is empty:** Infer the question from recent context — open files, recent conversation, or the project's estimation code. If no context is available, state "No research question provided" and stop.
Evaluate whether brainstorming is needed based on the research question.
**Clear requirements indicators:**
**If requirements are already clear:** Skip brainstorming and note: "Requirements are detailed enough to proceed directly to planning. Run `/workflows:plan` to continue." Then stop.
**If requirements need exploration:** Proceed to Phase 1.
Run a targeted scan to understand existing patterns and related methods:
Focus on: existing estimation code, identification strategies used in this project, methodology documented in papers or notes.
Analyze the research question systematically without user interaction:
1. **Core question**: What is the fundamental methodological decision being made? 2. **Constraints**: What data limitations, computational budgets, or identification requirements constrain the choice? 3. **Prior art**: What has this project already done that's similar? What methods are established in the literature? 4. **Success criteria**: What would a good solution look like? (e.g., consistent estimation, reasonable computational cost, testable identification)
Document findings from the research agent and decomposition. If the question is ambiguous, pick the most natural interpretation given the project context and note the assumption.
Propose **2-3 concrete methodological approaches** based on research and analysis.
For each approach, provide:
| Criterion | Approach A | Approach B | Approach C | |-----------|-----------|-----------|-----------| | **Description** | 2-3 sentence summary | 2-3 sentence summary | 2-3 sentence summary | | **Theoretical properties** | Consistency, efficiency, robustness to misspecification | ... | ... | | **Identification requirements** | What assumptions are needed? How testable are they? | ... | ... | | **Computational cost** | Estimation time, convergence difficulty, parallelizability | ... | ... | | **Data requirements** | Sample size needs, variable availability, panel structure | ... | ... | | **Software availability** | Packages (Python/R/Julia), maturity, documentation | ... | ... | | **Monte Carlo evidence** | Finite-sample performance from methodology literature | ... | ... |
**Recommendation:** Select the simplest approach that satisfies the identification requirements. Apply parsimony — prefer well-understood methods with established software implementations over novel approaches unless the research question specifically demands novelty.
Document why the recommended approach was chosen and what conditions would favor the alternatives.
**Entry condition:** Phase 2 comparison table is complete with all criteria filled for all approaches. **Exit condition:** Document written to docs/brainstorms/ with all required YAML frontmatter fields.
Write the brainstorm output to `docs/brainstorms/<topic>-requirements.md` with YAML frontmatter:
--- status: active date: YYYY-MM-DD topic: <descriptive topic> ---
If `docs/brainstorms/` contains a recent document matching this topic, ask the user: "Found existing brainstorm on this topic. Continue from it, or start fresh?"
Write a brainstorm document to `docs/brainstorms/YYYY-MM-DD-<topic>-brainstorm.md`.
Ensure `docs/brainstorms/` directory exists before writing.
**Document structure:**
--- title: [Brainstorm Topic] date: YYYY-MM-DD status: complete recommended-approach: [Name of recommended approach] --- # [Brainstorm Topic] ## Research Question [The question being explored] ## Problem Decomposition - Core question: [...] - Key constraints: [...] - Prior art in this project: [...] - Success criteria: [...] ## Approaches Compared ### Approach A: [Name] - **Description:** [...] - **Theoretical properties:** [...] - **Identification requirements:** [...] - **Computational cost:** [...] - **Data requirements:** [...] - **Software:** [...] - **Monte Carlo evidence:** [...] - **Verdict:** [...] ### Approach B: [Name] [Same structure] ### Approach C: [Name] (if applicable) [Same structure] ## Recommendation **Selected: [Approach Name]** [Why this approach. What conditions would favor alternatives. Key tradeoffs accepted.] ## Key Decisions - [Decision 1 and rationale] - [Decision 2 and rationale] ## Assumptions Made - [Any assumptions made during autonomous analysis] ## Open Questions - [Questions that should be resolved during planning or implementation] ## References - [Methodological papers cited] - [Software doc
📌 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 |
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