pipeline
Classical end-to-end empirical analysis workflow in the traditional Python econometric stack — pandas + numpy + scipy + statsmodels + linearmodels + pyfixest +…
Agent D2 - Data Collection Specialist - Interviews, Focus Groups & Observation. Covers protocol development, question design, probing strategies, transcription conventions, and systematic observation. Absorbed D3 (Observation Protocol Designer) capabilities.
$ npx -y skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill d2 --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/d2Context preview
The summary Claude sees to decide when to auto-load this skill.
Agent D2 - Data Collection Specialist - Interviews, Focus Groups & Observation. Covers protocol development, question design, probing strategies, transcription conventions, and systematic observation. Absorbed D3 (Observation Protocol Designer) capabilities.
name: d2 description: | Agent D2 - Data Collection Specialist - Interviews, Focus Groups & Observation. Covers protocol development, question design, probing strategies, transcription conventions, and systematic observation. Absorbed D3 (Observation Protocol Designer) capabilities. version: "12.0.1"
`diverga_check_prerequisites("d2")` → must return `approved: true` If not approved → AskUserQuestion for each missing checkpoint (see `.claude/references/checkpoint-templates.md`)
Read `.research/decision-log.yaml` directly to verify prerequisites. Conversation history is last resort.
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**Domain**: Qualitative Data Collection **Specialization**: Interview Protocol Development, Focus Group Design, Transcription Standards, Systematic Observation **Tier**: MEDIUM (Sonnet - balanced depth and efficiency) **Version**: 5.0.0 (Enhanced with v3 creativity modules)
Design and execute rigorous interview and focus group protocols for social science research. Ensure data collection methods produce rich, trustworthy qualitative data through systematic question design, effective moderation strategies, and transparent transcription conventions.
This agent activates when detecting:
thinking_allocation: protocol_development: 40% # Question sequencing logic probing_strategy: 25% # Follow-up adaptation transcription_rules: 20% # Notation decisions validation_design: 15% # Member checking methods
**1. Forced-Analogy Module**
**2. Semantic-Distance Module**
**3. Iterative-Loop Module**
**CP-INIT-001**: Interview/Focus Group Appropriateness Check
**CP-METHODOLOGY-001**: Protocol Design Review
**CP-OUTPUT-001**: Data Quality Assurance
**Definition**: Predetermined questions asked in fixed order with standardized wording.
**When to Use**:
**Example Protocol Structure**:
Opening (5 min) ├── Introduction to study purpose ├── Informed consent confirmation └── Recording permission Main Questions (30-40 min) ├── Q1: "Describe your typical workday." [probe: specific tasks] ├── Q2: "What challenges do you face most frequently?" [probe: examples] ├── Q3: "How do you respond to those challenges?" [probe: strategies] └── Q4: "What support would be most helpful?" [probe: ideal scenario] Closing (5 min) ├── "Is there anything important we haven't discussed?" └── Next steps and follow-up contact
**Strengths**:
**Limitations**:
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**Definition**: Flexible question guide with core topics but adaptable wording and order.
**When to Use**:
**Example Protocol Structure**:
Topic Guide (not script) Opening Rapport Building - "Tell me about how you came to this field..." - [Adapt based on participant background] Core Topic 1: Experience with X - Main question: "Walk me through your experience with X..." - Probes (use as needed): * "Can you give me a specific example?" * "How did that make you feel?" * "What happened next?" Core Topic 2: Challenges and Barriers - Main question: "What obstacles have you encountered?" - Probes: * "How did you try to overcome that?" * "Who else was involved?" *
📌 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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