science by brycewang-stanford
因果识别策略（cre-identification） brycewang-stanford/cre-identification
Use when the empirical identification strategy is the bottleneck for a 《中国农村经济》 manuscript — micro-household / village-level quasi-experimental designs (DID, IV, RDD, PSM). Stress-tests the design and the rural-specific endogeneity before drafting tables.
What it changes View full report → Passed 18 of 22 test cases with the skill, and 5 of 22 without it.
Without skill 23%
With skill 82%
Checks it passed that the model alone missed and 1 more in the full report
15 fixed3 passed either way2 still failing2 broke
Pass-rate lift +59 pp
Tokens +42%
Agent turns 0%
Response time -8% Model gemini-3.6-flashMeasured 9/1/2026 v1 18 of 22 cases passed with skill
Use this skill Claude Code DecimalAI agent CLI & files
Save it into your project's skills folder. Claude Code picks it up in its next session.
curl -fsSL --create-dirs -o .claude/skills/brycewang-stanford-cre-identification/SKILL.md https://app.decimal.ai/s/brycewang-stanford-cre-identification/SKILL.md Copy command Copy SKILL.md
Want it pinned and updatable? pip install "decimalai>=0.15", then decimalai skills add brycewang-stanford-cre-identification, and start Claude Code with claude --plugin-dir "$(git rev-parse --show-toplevel)/.agents"
Linked stays up to date: your agents get the author's new versions automatically.
Editable copy is yours to change; the author's updates won't reach it.
Install linked skill Create editable copy
1 · One-time — install the CLI (
docs ↗ )
$ pip install "decimalai>=0.15"Copy
2 · Get the skill — writes .agents/skills/brycewang-stanford-cre-identification/ and pins it in .decimal/skills.lock
$ decimalai skills add brycewang-stanford-cre-identificationCopy
Copy link Copy README badge Copy SKILL.md No CLI? Get the same file — curl · raw file $ curl -fsSL --create-dirs -o .claude/skills/brycewang-stanford-cre-identification/SKILL.md https://app.decimal.ai/s/brycewang-stanford-cre-identification/SKILL.mdCopy
Safety checks: 3 of 3 passed
Code scan Clean Intent Passed Content Clean
Overview Benchmark Contents Activity Versions 1 Ratings 0
See it in action One of 15 test cases the skill fixed. Same model, same prompt, with and without the skill.
Prompt 课题组要评估一项在县级层面有明确划定贫困线门槛的补贴政策。小王建议做普通的倾向得分匹配（PSM），小李建议做断点回归（RDD）。如果论文的目标是投递国内权威农村经济期刊，根据识别策略的偏好优先级，应该优先选用哪种策略？请按规定格式输出诊断信息。
What was checked, without and with the skill Checked Without skill With skill The output designates Regression Discontinuity Design as higher priority than standard PSM for sharp policy cutoffs The output specifies cre-mechanism as the next workflow step
Show both answers
What's inside The instructions your model reads when the skill loads.
SKILL.md 108 lines single file
因果识别策略（cre-identification）
触发时机
实证主体仅有描述统计 + OLS + 控制变量
自变量是农户的自选择行为 （入合作社、外出务工、采用新技术、参与流转），但没处理自选择内生性
DID 用了 TWFE 但没回应近年异质性处理批评（Goodman-Bacon, de Chaisemartin, Sun-Abraham, Callaway-Sant'Anna）
IV 第一阶段 F 弱 / 工具变量排他性疑虑
PSM 只做了匹配但没讨论"不可观测的选择性"
设计优先级
《中国农村经济》编委对农村微观研究的偏好排序（强 → 弱）：
农村政策冲击 + DID（含 staggered / continuous treatment） ——如某项试点改革、确权、补贴政策的分批推行断点回归 ——清晰的政策门槛（如贫困县划定线、补贴资格线、年龄门槛）工具变量 ——强工具 + 排他性论证（处理农户自选择的核心武器）倾向得分匹配 + DID（PSM-DID） ——农村横截面 / 短面板的常见组合合成控制法 ——村级 / 县级政策评估OLS + 严密的自选择讨论（仅在有强外生性论证或结构 / 理论实证时可接受）
农村数据的内生性专项
农村微观研究最常见的内生性来源，审稿人必查：
自选择进入处理 ：是否更"能干 / 风险偏好 / 资源禀赋好"的农户才入社 / 流转 / 务工？反向因果 ：是收入高才参与，还是参与带来收入？测量误差 ：农户自报的收入 / 土地面积 / 用工常有偏差遗漏的村级 / 家庭固定特征 ：村庄区位、宗族网络、家庭社会资本
针对性策略至少给出一条：固定效应 + IV / 准实验冲击 / 匹配 + 安慰剂 / 双稳健（Heckman 仅作辅助，不能单独立住识别）。
分支路径
分支 A：DID
是否 staggered？→ 必须用 Goodman-Bacon 分解 + Callaway-Sant'Anna 或 Sun-Abraham
平行趋势检验：事件研究图必须画
安慰剂：随机分配处理村 / 处理户 500–1000 次
是否报告 Bacon 分解的"坏比较"权重？
Track record Benchmark 18 / 22
test cases passed, vs 5 / 22 without
Adoption
Users 0
Times used 0 View activity → Safety and source details
SkillSafety ✓ 3 of 3 passed ✓ Code scan 15 of 15 checks clean
0 critical · 0 warning · 0 info — scanner v4 — 8/10/2026
View 15 scanner checks live_secret remote_code_execution reverse_shell data_exfiltration ssrf_metadata agent_snooping anti_refusal destructive_commands obfuscated_unicode unicode_homoglyph opaque_blob suspicious_url tool_overreach trigger_abuse prompt_injection_phrasing
✓ Intent Safe
LLM judge · does the skill do what it claims
✓ Content Clean
LLM judge · policy & harmful-content review
Source Imported brycewang-stanford / awesome-journal-skills
China-Rural-Economy-Skills/skills/cre-identification/SKILL.md
View on GitHub ↗ License MITImported 8/10/2026Version v1