Econometric Research Writing
franklee16/academic-research-skills
End-to-end econometric analysis and economics/management paper-writing workflow.
Agent skill
Auto Empirical Research Skills
by brycewang-stanford in brycewang-stanford/Auto-Empirical-Research-Skills
Route empirical-research requests through the Auto-Empirical Research Skills catalog when this whole repository is installed as one skill in Codex, CodeBuddy, Claude Code, or another IDE.
Install Auto Empirical Research Skills
$ npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill auto-empirical-research-skills -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install brycewang-stanford/Auto-Empirical-Research-Skills auto-empirical-research-skills --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
Claude Code skills documentation · loads skills from .claude/skills/
Install the "auto-empirical-research-skills" agent skill from https://github.com/brycewang-stanford/Auto-Empirical-Research-Skills/tree/main into .claude/skills/auto-empirical-research-skills/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "auto-empirical-research-skills", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill auto-empirical-research-skills -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install brycewang-stanford/Auto-Empirical-Research-Skills auto-empirical-research-skills --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "auto-empirical-research-skills" agent skill from https://github.com/brycewang-stanford/Auto-Empirical-Research-Skills/tree/main into .agents/skills/auto-empirical-research-skills/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "auto-empirical-research-skills", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill auto-empirical-research-skills -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install brycewang-stanford/Auto-Empirical-Research-Skills auto-empirical-research-skills --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "auto-empirical-research-skills" agent skill from https://github.com/brycewang-stanford/Auto-Empirical-Research-Skills/tree/main into .cursor/skills/auto-empirical-research-skills/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "auto-empirical-research-skills", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill auto-empirical-research-skills -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install brycewang-stanford/Auto-Empirical-Research-Skills auto-empirical-research-skills --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "auto-empirical-research-skills" agent skill from https://github.com/brycewang-stanford/Auto-Empirical-Research-Skills/tree/main into .gemini/skills/auto-empirical-research-skills/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "auto-empirical-research-skills", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install brycewang-stanford/Auto-Empirical-Research-Skills auto-empirical-research-skillsInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill auto-empirical-research-skills -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "auto-empirical-research-skills" agent skill from https://github.com/brycewang-stanford/Auto-Empirical-Research-Skills/tree/main into .github/skills/auto-empirical-research-skills/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "auto-empirical-research-skills", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill auto-empirical-research-skills -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install brycewang-stanford/Auto-Empirical-Research-Skills auto-empirical-research-skills --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "auto-empirical-research-skills" agent skill from https://github.com/brycewang-stanford/Auto-Empirical-Research-Skills/tree/main into .opencode/skills/auto-empirical-research-skills/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "auto-empirical-research-skills", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
auto-empirical-research-skills- GitHub stars
- 4.6k
- Token cost
- ~3.3k tokens
- SKILL.md length
- 1,257 words
- Files
- 1,849 (incl. scripts)
- Skills in repo
- 383
- Repo updated
- First seen
- Licence
- CC-BY-SA-4.0
At a glance
Route empirical-research requests through the Auto-Empirical Research Skills catalog when this whole repository is installed as one skill in Codex, CodeBuddy, Claude Code, or another IDE.
- Works in 5 steps: Classify the user's empirical-research… → Read only the selected child skill's… → If no child skill clearly matches, run… → …
- Choose and load the right vendored AERS skill for causal inference
- SKILL.md covers Workflow, Method → where to start, Full-pipeline trigger and Coverage Notes, plus 2 more sections
- Calls git and python3
What it does
Auto Empirical Research Skills is an agent skill from brycewang-stanford/Auto-Empirical-Research-Skills. Route empirical-research requests through the Auto-Empirical Research Skills catalog when this whole repository is installed as one skill in Codex, CodeBuddy, Claude Code, or another IDE. Use to choose and load the right vendored AERS skill for causal inference, econometrics, replication, data acquisition, manuscript writing, peer review and referee responses, citation checking, de-AIGC editing, or full empirical-paper workflows, or an end-to-end run from raw data all the way to a finished Word (.docx)…
Its SKILL.md is about 3.3k tokens, which your agent loads only when the skill is triggered. The skill folder holds 1852 other files, including scripts (for example `.claude-plugin/marketplace.json`, `.github/ISSUE_TEMPLATE/bug_report.yml` and `.github/ISSUE_TEMPLATE/config.yml`).
It sits in Research & Science, covering Econometrics and empirical research. It works with Microsoft Word. The repository describes itself as: 🔬 A curated collection of 23,000+ agent skills for empirical research across 8 social science disciplines. | 精选 23,000+ AI Agent 技能库，覆盖8大社会科学学科的实证研究。CoPaper.AI… The licence is CC-BY-SA-4.0.
When your agent uses it
- Choose and load the right vendored AERS skill for causal inference
- Data acquisition
- Manuscript writing
- Peer review and referee responses
Example prompts
- “/auto-empirical-research-skills”
Requirements
- Python 3
Workflow steps
5 steps, taken from the first numbered list in SKILL.md.
- Classify the user's empirical-research task by stage, then load the single best-matching skill
- Read only the selected child skill's SKILL.md, then follow its progressive-disclosure instructions for references/, scripts/, assets/, or…
- If no child skill clearly matches, run the ranked catalog search first — it takes English or Chinese task text
- For installation help, use docs/INSTALL.md for Codex-style copy installs and INSTALL.md for Claude Code marketplace/plugin installs.
- If editing this repository, keep parent and nested repos separate. In particular, inspect git status inside skills/69-Paper-WorkFlow/ (a…
What it can do on your machine
Read from SKILL.md and the folder at commit 9fa87d8. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
Ships 1 file in scripts/, which the agent can run.
Shell commands in SKILL.md call:
gitpython3
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md. Its commands use git, which can reach the network depending on how they are called.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Auto Empirical Research Skills loads about 3.3k tokens when it runs. Until then it costs about 149 tokens; SKILL.md has 1,257 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.
SKILL.md
The full file from brycewang-stanford/Auto-Empirical-Research-Skills at commit 9fa87d8, republished under its CC-BY-SA-4.0 licence (© brycewang-stanford). 1,257 words, ~3,331 tokens.
Download SKILL.mdSave it as
.claude/skills/auto-empirical-research-skills/SKILL.md (or your agent's skills folder). This skill also uses 1848 other files; get the full folder from GitHub.- name
- auto-empirical-research-skills
- description
- Route empirical-research requests through the Auto-Empirical Research Skills catalog when this whole repository is installed as one skill in Codex, CodeBuddy, Claude Code, or another IDE. Use to choose and load the right vendored AERS skill for causal inference, econometrics, replication, data acquisition, manuscript writing, peer review and referee responses, citation checking, de-AIGC editing, or full empirical-paper workflows, or an end-to-end run from raw data all the way to a finished Word (.docx) manuscript, without reading the entire repository at once.
- license
- CC-BY-SA-4.0
Auto-Empirical Research Skills Router
Use this root skill when the full AERS repository has been installed as a single skill folder. Treat it as a router and catalog, not as a request to load every vendored SKILL.md.
The catalog holds 1,107 skills across 77 vendored collections. Never read them all — route to one, then load only that skill's SKILL.md.
Workflow
Classify the user's empirical-research task by stage, then load the single best-matching skill:
- Full pipeline or orchestration: start with
skills/69-Paper-WorkFlow/or theskills/00*flagship analysis skills —skills/00-Full-empirical-analysis-skill_StatsPAI/(StatsPAI),skills/00.1-Full-empirical-analysis-skill_Python/(Python),skills/00.2-Full-empirical-analysis-skill_Stata/(Stata),skills/00.3-Full-empirical-analysis-skill_R/(R). Note the StatsPAI flagship has no dot in its prefix, so askills/00.*glob misses it. - Causal inference and econometrics: pick by method from the table below, or search
catalog/skills.json/docs/TAXONOMY.md. - AER or top economics journal work: start with
skills/50-brycewang-aer-skills/. - Replication, citation, or peer review: use
docs/SKILL_CATALOG.mdanddocs/GOLDEN_WORKFLOWS.mdto choose a focused skill. - Academic de-AIGC (English or Chinese) or academic rewriting: start with
skills/48-de-AIGC-skills/or nearby writing skills in the catalog.
- Full pipeline or orchestration: start with
Read only the selected child skill's
SKILL.md, then follow its progressive-disclosure instructions forreferences/,scripts/,assets/, or templates.If no child skill clearly matches, run the ranked catalog search first — it takes English or Chinese task text:
bash python3 scripts/find-skill.py "staggered difference-in-differences event study" python3 scripts/find-skill.py "降低中文论文 AIGC 率" -k 5It ranks by relevance, then by the routing tier in
catalog/curation.json: first-partycoreskills first, a single preferred copy for each duplicated name (the other copies are folded away), and natural-science / CS guides (out-of-domain) last unless the query names them. Take the top result unless its description clearly misfits, then read only thatSKILL.md. Its accuracy is measured bypython3 scripts/check-routing.pyagainstevals/routing-cases.json.If you need raw data instead,
catalog/skills.jsonhaspath,name,description,line_count, and a globally-uniquequalified_name;catalog/skills-enriched.jsonaddstier,tags,quality_score,license, andcommercial_use. Avoid broad recursive reads ofskills/.Both catalog JSON files are large (roughly 1 MB / 20k lines each) — query them instead of reading them whole. Example:
bash python3 -c "import json; [print(s['qualified_name'], '->', s['path']) for s in json.load(open('catalog/skills.json'))['skills'] if 'synthetic control' in (s['name'] + ' ' + s['description']).lower()]"A plain
grep -in "synthetic control" catalog/skills.jsonworks too when a rough match is enough.
For installation help, use
docs/INSTALL.mdfor Codex-style copy installs andINSTALL.mdfor Claude Code marketplace/plugin installs.If editing this repository, keep parent and nested repos separate. In particular, inspect
git statusinsideskills/69-Paper-WorkFlow/(a git submodule) before touching it.
Method → where to start
Match the user's identification strategy or task to a starting collection, then confirm against catalog/skills.json.
This table is a shortcut to the most common starting points, not a complete index — it names fewer than half of the vendored collections, and the rest are reachable only through catalog/skills.json. A task missing from this table is not a task without a skill: fall through to step 3 and search the catalog before concluding nothing matches.
| Task / method | Start here |
|---|---|
| Full paper pipeline (orchestrator) | skills/69-Paper-WorkFlow/ |
Data → full Word .docx manuscript (one run: analysis + writing + assembled deliverable) | skills/69-Paper-WorkFlow/ — pick manuscript.format = markdown at its Stage 0 when the deliverable is Word; Stage 9 assembles 09_submission/main.docx (body + tables + figures + references) and gates it |
Markdown / LaTeX → .docx conversion only (no analysis) | skills/67-econfin-workflow-toolkit/md-to-docx/, skills/08-ndpvt-web-latex-document-skill/ |
| Agent-native causal analysis (one call runs DiD / RD / IV / SCM / DML with automatic robustness gates) | skills/00-Full-empirical-analysis-skill_StatsPAI/ |
| DiD / staggered DiD / event study | skills/50-brycewang-aer-skills/, skills/10-Jill0099-causal-inference-mixtape/, skills/13-scunning1975-MixtapeTools/ |
| Instrumental variables (IV) | skills/50-brycewang-aer-skills/, skills/40-py-econometrics-pyfixest/ |
| Regression discontinuity (RDD) | skills/50-brycewang-aer-skills/, skills/10-Jill0099-causal-inference-mixtape/ |
| Synthetic control (SCM) | skills/50-brycewang-aer-skills/, skills/13-scunning1975-MixtapeTools/ |
| Panel fixed effects | skills/40-py-econometrics-pyfixest/, skills/39-vincentarelbundock-marginaleffects/ |
| Specification search / multiverse / p-hacking audit, honest p-values, p-curve, pre-registration | skills/73-brycewang-p-hacking-skills/ (start at skills/00-phack-router/; teaching & audit only) |
| Matching / propensity scores | skills/10-Jill0099-causal-inference-mixtape/, skills/11-James-Traina-compound-science/ |
| Structural estimation | skills/11-James-Traina-compound-science/, skills/14-luischanci-claude-code-research-starter/ |
| Time series / forecasting | skills/17-DAAF-Contribution-Community-daaf/, skills/43-wentorai-research-plugins/ |
| Text as data / NLP | skills/43-wentorai-research-plugins/ |
| Spatial / GIS analysis | skills/17-DAAF-Contribution-Community-daaf/, skills/43-wentorai-research-plugins/ |
| Experiments / RCT design | skills/11-James-Traina-compound-science/, skills/25-HosungYou-Diverga/ |
| Survey / questionnaire design | skills/43-wentorai-research-plugins/, skills/25-HosungYou-Diverga/ |
| DML / CATE / causal forests | skills/00.1-Full-empirical-analysis-skill_Python/, skills/63-tondevrel-scientific-agent-skills/ |
| Bayesian modeling | skills/23-Learning-Bayesian-Statistics-baygent-skills/, skills/51-pymc-labs-CausalPy/ |
| Python analysis (full pipeline) | skills/00.1-Full-empirical-analysis-skill_Python/, skills/40-py-econometrics-pyfixest/ |
| Stata analysis | skills/00.2-Full-empirical-analysis-skill_Stata/, skills/32-dylantmoore-stata-skill/, skills/64-tmonk-mcp-stata/ |
| R analysis | skills/00.3-Full-empirical-analysis-skill_R/, skills/55-ab604-claude-code-r-skills/ |
| Game theory / theory papers | skills/65-game-theory-paper-writer/ |
| Qualitative / thematic analysis | skills/53-keemanxp-thematic-analysis-skill/ |
| Data acquisition (Kaggle, SEC filings, open data) | skills/72-kaggle-research/, skills/57-dgunning-edgartools/, skills/59-shiquda-openalex-skill/ |
| Literature review | skills/36-taoyunudt-literature-review-skill/, skills/52-keemanxp-slr-prisma/, skills/59-shiquda-openalex-skill/ |
| Lit-review tool selection / PDF→Markdown / cited Q&A over PDFs / PRISMA screening runners | skills/71-brycewang-lit-review-agent-tools/ |
| Citation checking | skills/62-PHY041-claude-skill-citation-checker/ |
| Manuscript writing / proofreading | skills/04-K-Dense-AI-claude-scientific-writer/, skills/38-peternka-academic-proofreader/ |
| Peer review / referee reports / referee responses | skills/21-claesbackman-AI-research-feedback/, skills/12-pedrohcgs-claude-code-my-workflow/, skills/67-econfin-workflow-toolkit/ |
| LaTeX / Quarto compilation, slides | skills/08-ndpvt-web-latex-document-skill/, skills/60-regisely-superpapers/, skills/12-pedrohcgs-claude-code-my-workflow/ |
| De-AIGC / humanize | skills/48-de-AIGC-skills/, skills/45-stephenturner-skill-deslop/, skills/47-conorbronsdon-avoid-ai-writing/ |
| Chinese SSCI/CSSCI journal polishing | skills/70-ssci-polish/, skills/49-voidborne-d-humanize-chinese/ |
| Replication | skills/28-maxwell2732-paper-replicate-agent-demo/, skills/29-quarcs-lab-project20XXy/ |
| Open science / reproducibility | skills/54-scdenney-open-science-skills/, skills/29-quarcs-lab-project20XXy/ |
| Grant proposals / funding | skills/42-wanshuiyin-ARIS/, skills/43-wentorai-research-plugins/ |
| Conference posters / post-acceptance | skills/42-wanshuiyin-ARIS/, skills/33-Galaxy-Dawn-claude-scholar/ |
Show full SKILL.md (513 more words)Show less
Full-pipeline trigger
If the user is asking for a complete empirical paper from idea to submission, route to skills/69-Paper-WorkFlow/. The orchestrator loads the right skill at the right stage and stops for human decisions at the two hard gates (Method Gate after Stage 3, Draft Quality Gate after Stage 7).
Trigger phrases (any one is enough to dispatch to the orchestrator):
/paper-workflow- "帮我写一篇实证论文"
- "从选题到投稿"
- "end-to-end empirical paper"
- "完整复现"
- "from proposal to submission"
- "从数据到 docx 论文全文" / "一条龙" / "出一份 Word 版论文"
- "raw data to a finished Word manuscript"
The orchestrator is not the right entry point for a single-task ask (e.g. "fit a DiD", "recode this variable", "write a referee report") — those are listed in the Method → where to start table above.
Coverage Notes
skills/69-Paper-WorkFlow/is a git submodule. If its folder is empty, the copy or clone skipped submodules (git submodule update --initfixes a clone); fall back to theskills/00*flagship pipeline skills, which are vendored directly. Those end at publication-ready tables and figures plus a Step 8.5 handoff contract (exhibits_index.md+results_summary.json); pair them with a writing skill for the manuscript itself, since assembling and gating the full.docxlives in the orchestrator.- The vendored ARIS collection (
skills/42-wanshuiyin-ARIS/) also ships its skill set as OpenAI Codex CLI runtime ports (skills-codex*subtrees). Those stay on disk but are excluded fromcatalog/skills.json(seescripts/skill_discovery.py) — route Claude agents to the primaryskills/tree only.
Install Notes
- Whole-repo imports are supported by this root
SKILL.mdas a lightweight compatibility entry point. - Individual skill installs are still preferred when a runtime expects one folder per skill. Copy the folder that directly contains the target
SKILL.md. - Do not copy the repository root into a runtime and expect every child skill to become individually registered unless that runtime explicitly supports recursive skill discovery.
- Do not flat-install the whole catalog (e.g. symlinking every child folder into
~/.claude/skills). Every registered skill's description is loaded at session start — about 64k tokens for all 1,107 here — and runtimes truncate long skill listings, so matching gets worse, not better. Use a plugin, this router, or a handful of copied skills. - Name collisions: the catalog contains 47 bare
names shared across collections (e.g.data-analysis,lit-review,proofread);catalog/curation.jsonnames one preferred copy of each, whichscripts/find-skill.pyreturns. When a runtime registers skills by flat name, install one collection at a time, or disambiguate with the globally-uniquequalified_namefield incatalog/skills.json(<collection>::<name>, e.g.12-pedrohcgs-claude-code-my-workflow::data-analysis), or the fullskills/<collection>/.../SKILL.mdpath.
Key Files
catalog/skills.json: machine-readable list of vendored skills.catalog/skills-enriched.json: same list plustier,tags,quality_score,license, andcommercial_usefor filtering.catalog/curation.json: hand-curated routing tiers (core collections, the preferred copy of each duplicated name, out-of-domain prefixes). Ranking only — nothing is removed.scripts/find-skill.py: ranked search over the catalog (the router's search step).docs/SKILL_CATALOG.md: human-readable skill index.docs/TAXONOMY.md: task and method taxonomy.docs/GOLDEN_WORKFLOWS.md: ready-to-use empirical-research prompts.docs/INSTALL.md: runtime installation guidance for single-skill and whole-repo use.docs/CONTENT_ZH.mdandREADME-zh-CN.md: Chinese-language collection index and entry point. Prefer these when the user is working in Chinese — several collections (de-AIGC, SSCI/CSSCI polishing, Chinese academic writing) are documented there in more detail than in the English docs.
© brycewang-stanford, CC-BY-SA-4.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
SKILL.md and 1,848 other files (scripts) in the repository root of brycewang-stanford/Auto-Empirical-Research-Skills.
- SKILL.md
- .claude-plugin/marketplace.json
- .github/ISSUE_TEMPLATE/bug_report.yml
- .github/ISSUE_TEMPLATE/config.yml
- .github/ISSUE_TEMPLATE/feature_request.yml
- .github/ISSUE_TEMPLATE/skill_submission.yml
- .github/ISSUE_TEMPLATE/usage_question.yml
- .github/dependabot.yml
- .github/pull_request_template.md
- .github/workflows/check-external-links.yml
- .github/workflows/check-tools-links.yml
- .github/workflows/quality-evals.yml
- .github/workflows/refresh-star-history.yml
- .github/workflows/scorecard.yml
- .github/workflows/sync-aer-skills.yml
- .github/workflows/sync-statspai-skill.yml
- .github/workflows/validate-catalog.yml
- … and 1,832 more
Open the folder on GitHubat commit 9fa87d8
Compare with similar skills
Auto Empirical Research Skills next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Auto Empirical Research Skills this skillbrycewang-stanford/Auto-Empirical-Research-Skills | 4.6k | — | ~3.3k | Automated safety check: Pass | CC-BY-SA-4.0 | |
| Econometric Research Writingfranklee16/academic-research-skills | 223 | — | ~2.4k | Automated safety check: Pass | None | |
| Scholar Auto Researchjoshzyj/open-scholar-skill | 168 | — | ~21k | Automated safety check: Pass | Custom licence | |
| Academic Paper Writing PipelineImbad0202/academic-research-skills | 51k | — | ~16k | Automated safety check: Pass | Custom licence | |
| Autonomous Researchfedericodeponte/opendraft | 507 | — | ~8.2k | Automated safety check: Pass | Apache-2.0 | |
| Math Modeling Competition WorkflowXiaoMaColtAI/math-modeling-skill | 1.9k | — | ~1.2k | Automated safety check: Pass | None |
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brycewang-stanford/Auto-Empirical-Research-Skills
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brycewang-stanford/Auto-Empirical-Research-Skills
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brycewang-stanford/Auto-Empirical-Research-Skills
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brycewang-stanford/Auto-Empirical-Research-Skills
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Questions about Auto Empirical Research Skills
What does Auto Empirical Research Skills do?
Route empirical-research requests through the Auto-Empirical Research Skills catalog when this whole repository is installed as one skill in Codex, CodeBuddy, Claude Code, or another IDE. Auto Empirical Research Skills is an agent skill from brycewang-stanford/Auto-Empirical-Research-Skills. Route empirical-research requests through the Auto-Empirical Research Skills catalog when this whole repository is installed as one skill in Codex, CodeBuddy, Claude Code, or another IDE.
When should I use Auto Empirical Research Skills?
Auto Empirical Research Skills fits situations like: choose and load the right vendored AERS skill for causal inference; data acquisition; manuscript writing; peer review and referee responses.
How do I install Auto Empirical Research Skills in Claude Code?
Run `npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill auto-empirical-research-skills -a claude-code`. Or copy the skill folder (the brycewang-stanford/Auto-Empirical-Research-Skills repository) into .claude/skills/auto-empirical-research-skills in your project. Claude Code loads it when a task matches its description.
How do I install Auto Empirical Research Skills in Codex?
Run `npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill auto-empirical-research-skills -a codex`. Or copy the skill folder (the brycewang-stanford/Auto-Empirical-Research-Skills repository) into .agents/skills/auto-empirical-research-skills in your project. Codex loads it when a task matches its description.
Can I use Auto Empirical Research Skills in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill auto-empirical-research-skills -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/auto-empirical-research-skills, .gemini/skills/auto-empirical-research-skills, .github/skills/auto-empirical-research-skills and .opencode/skills/auto-empirical-research-skills in your project.
What does Auto Empirical Research Skills need to run?
Going by SKILL.md and its folder, Auto Empirical Research Skills needs the command-line tools its instructions call (git and python3). Our summary lists: Python 3.
Does Auto Empirical Research Skills access the network?
SKILL.md contains no URLs. Its commands use git, which can reach the network depending on how they are called. This is read from the text; nothing was executed.
Is Auto Empirical Research Skills safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.
What licence does Auto Empirical Research Skills use?
Auto Empirical Research Skills is published under the CC-BY-SA-4.0 licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Auto Empirical Research Skills use?
About 3.3k tokens (SKILL.md is roughly 13k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
What are the alternatives to Auto Empirical Research Skills?
Skills that share tags, products or a category with Auto Empirical Research Skills: Econometric Research Writing (franklee16/academic-research-skills, 223 stars), Scholar Auto Research (joshzyj/open-scholar-skill, 168 stars), Academic Paper Writing Pipeline (Imbad0202/academic-research-skills, 51k stars) and Autonomous Research (federicodeponte/opendraft, 507 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Auto Empirical Research Skills?
brycewang-stanford (a GitHub user) maintains it in brycewang-stanford/Auto-Empirical-Research-Skills, which has 4,556 GitHub stars. The repository holds 383 skills in this directory. The repository was last updated on October 5, 2026.
Source: brycewang-stanford/Auto-Empirical-Research-Skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.