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DSH PluginsSkill
Auto-Empirical-Research-Skills
brycewang-stanford/Auto-Empirical-Research-Skills
Auto-Empirical-Research-Skills is a tool for DeepSeek Harness. ð¬ A curated collection of 23,000+ agent skills for empirical research across 8 social science disciplines. | Curated library of 23,000+ AI Agent skills covering empirical research across 8 social science disciplines. CoPaper.AI completes a reproducible, standards-compliant empirical paper in 20 minutes, and supports user-uploaded Skills.-- Maintained by CoPaper.AI from Stanford REAP.
- Stars
- 3.8k
- Forks
- 475
- Issues
- 1
- Update
- 54 days
REVIEW SCORECARD
Review Scorecard
7.5/10Average
License compliance6.0
Engineering quality9.0
Content completeness8.0
Repository scale7.0
Maintenance activity8.0
â No risk detected · Automated scan results are for reference only, not an official endorsement
AI DEEP REVIEW
Worth AI Review
8.0/10Recommended
A large, actively maintained empirical-research skill library with strong rigor tooling, CI validation, and clear instal
Code quality8
README shows a validate-catalog CI workflow, OpenSSF Scorecard badge, benchmark/eval-harness directories with 19 benchmark tasks and 42 eval scenarios, and a pip-installable aers-score scorer, indicating real engineering rigor.
Security7
README advertises a 'baseline 52/52 CLEAN' security audit and an OpenSSF Scorecard badge, but the license is NOASSERTION and no permission model is described, so risk is only partially evidenced.
Utility9
It targets a concrete, common pain point (reproducible empirical social-science research pipelines) with 1,096 skills across Stata/Python/R and a 9-stage workflow from data cleaning to journal submission.
Maintenance8
Last updated 2026-09-07, not archived, with active CI badges, a maintained catalog, and multi-language READMEs indicating ongoing upkeep.
Documentation8
README provides 30-second install paths, plugin-marketplace and manual copy instructions, scope tables, usage examples, and links to INSTALL.md and extended docs, though the excerpt is truncated mid-sentence.
Generated by AI after reading the project README â a decision aid, not an endorsement. Neutral scores are given when information is limited.
PROJECT READMEREADMEExpandCollapse
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Open repositoryINSTALL REFERENCE
Install reference
claude plugin marketplace add brycewang-stanford/Auto-Empirical-Research-SkillsThis command was extracted from an explicit README install reference and is display-only; the DSH host will not execute it automatically.
PROJECT TOPICS
Project topics
VALIDATION LADDER
Validation progress
01Store discoveryPassed
02ClassificationPassed
03Structure checkPending
04Sandbox validationPending
FAQ
Frequently Asked Questions
What is Auto-Empirical-Research-Skills used for?
ð¬ A curated collection of 23,000+ agent skills for empirical research across 8 social science disciplines. | Curated library of 23,000+ AI Agent skills covering empirical research across 8 social science disciplines. Co
How popular is Auto-Empirical-Research-Skills?
Auto-Empirical-Research-Skills has 3,769 stars and 475 forks on GitHub, last updated 2026-09-07.
Is Auto-Empirical-Research-Skills compatible with DeepSeek Harness?
Auto-Empirical-Research-Skills is listed in the DSH Universe directory as a tool for DeepSeek Harness. This plugin is listed in the DSH Universe directory and covered by its validation pipeline.
CLASSIFICATION EVIDENCE
Classification evidence
Project typeSkill
Feature categoryDSH Plugins
Rule confidenceHigh
The system checks GitHub Topics against the site taxonomy and keyword rules. Current matches:agent-skillsãskills-libraryã
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