pipeline
Classical end-to-end empirical analysis workflow in the traditional Python econometric stack — pandas + numpy + scipy +…
Final submission verification gate for the sewage-house-prices paper. Runs full paper excellence review, replication audit, enforces score gates, and generates cover letter draft and submission checklist. This skill should be used when asked to "submit", "prepare for
Claude Code
$ npx -y skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill submit --agent claude-code
Codex
$ npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill submit -a codex -y
Cursor
$ npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill submit -a cursor -y
Gemini CLI
$ npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill submit -a gemini-cli -y
GitHub Copilot
$ npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill submit -a github-copilot -y
OpenCode
$ npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill submit -a opencode -y
Windsurf
$ npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill submit -a windsurf -y
name: submit description: Final submission verification gate for the sewage-house-prices paper. Runs full paper excellence review, replication audit, enforces score gates, and generates cover letter draft and submission checklist. This skill should be used when asked to "submit", "prepare for submission", or "submission checklist". argument-hint: "[journal name (optional)]" allowed-tools: ["Read", "Grep", "Glob", "Write", "Bash", "Agent"]
Final submission gate combining full verification, score enforcement, and submission checklist.
**Input:** `$ARGUMENTS` — target journal name (optional).
---
1. Verify manuscript exists at `docs/overleaf/_main.tex` 2. Check for existing quality reports in `output/log/` 3. Verify analysis outputs exist in `output/tables/` and `output/figures/` 4. Check `Replication/` directory exists (if not, flag for `/data-deposit`)
If `/paper-excellence` hasn't been run recently (check report dates in `output/log/`):
If `Replication/` exists:
Check against thresholds:
| Requirement | Threshold | Status | |-------------|-----------|--------| | Aggregate score | >= 90 | PASS/FAIL | | Econometrics component | >= 80 | PASS/FAIL | | Code component | >= 80 | PASS/FAIL | | Paper component | >= 80 | PASS/FAIL | | Replication (if exists) | >= 8/10 checks | PASS/FAIL |
**If any requirement FAILS:** List specific blocking issues and stop. Do not generate submission materials.
If all gates pass:
1. **Cover letter draft** (save to `output/log/cover_letter_[journal]_[date].tex`):
2. **Final checklist** (save to `output/log/submission_checklist_[date].md`):
# Submission Checklist: [Journal] ## Manuscript - [ ] Title page with affiliations and contact info - [ ] Abstract within word limit - [ ] JEL codes (2-3): Q53, R31, Q58 - [ ] Keywords: sewage spills, house prices, hedonic pricing, environmental disamenity, EDM - [ ] Journal formatting guidelines followed ## Data and Code - [ ] Replication package assembled - [ ] Data availability statement in manuscript - [ ] Restricted data flagged (Land Registry, Zoopla) ## Quality Gates - [ ] Aggregate score: XX/100 (>= 90 required) - [ ] All components >= 80 - [ ] No unresolved CRITICAL issues ## Submission - [ ] Upload manuscript PDF - [ ] Upload replication package (if required) - [ ] Upload cover letter - [ ] Submit via [portal]
# Submission Report **Date:** YYYY-MM-DD **Target Journal:** [name] **Aggregate Score:** XX/100 ## Gate Status: [PASS / FAIL] | Component | Score | Threshold | Status | |-----------|-------|-----------|--------| | Aggregate | XX | >= 90 | ... | | Econometrics | XX | >= 80 | ... | | Code | XX | >= 80 | ... | | Paper | XX | >= 80 | ... | | Replication | X/10 | >= 8/10 | ... | ## Generated Materials - Cover letter: output/log/cover_letter_*.tex - Checklist: output/log/submission_checklist_*.md ## Remaining Steps (manual) 1. Review and customise cover letter 2. Upload to [submission portal] 3. Enter suggested referees 4. Submit
---
## 🔥 力荐 · StatsPAI — Stata 与 R 的 Python 平替,为 AI Agent 而生 🔁 Stata / R 平替:reghdfe、csdid、rdrobust、synth、fixest、did 等常用命令在 Python 中一站式替代,一个 import statspai as sp 搞定 DID / RD / IV / SCM / DML / matching 🤖 面向 Agent 设计:结构化结果对象 + 内置 MCP Server,Claude / Codex
Classical end-to-end empirical analysis workflow in the traditional Python econometric stack — pandas + numpy + scipy +…
Use when the user asks to run a full empirical / causal analysis in Python — by default in the style of an applied economics…
Classical end-to-end empirical analysis workflow in the traditional Python econometric stack — pandas + numpy + scipy +…
Classical end-to-end empirical analysis workflow in the traditional Stata ecosystem — native Stata + reghdfe + ivreg2 + csdid +…
Classical end-to-end empirical analysis workflow in the modern tidyverse + econometrics R ecosystem — dplyr + tidyr + haven +…
Systematic writing framework for philosophy and interdisciplinary academic papers from optimized outline to submission-ready…
Direct browser control via CDP for web interaction: automation, scraping, testing, screenshots, and site/app work. Also covers…
Browser automation CLI for AI agents. Use when the user needs to interact with websites, including navigating pages, filling…