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DataStata

ASQ Data Analysis

by brycewang-stanford

ASQ Data Analysis is a Data skill for Claude Code, published by brycewang-stanford in Awesome-Journal-Skills.

779 stars96 forkson brycewang-stanford/Awesome-Journal-SkillsAdded 2026/07/14Repository updated 2026/07/09
academic-researchacademic-writingagent-skillsai-agentsanthropicawesome-listcausal-inferenceclaudeclaude-codeeconometricseconomicsempirical-researchfinancejournalllmmcppeer-reviewreplicationresearch-toolsscholarly-publishing
Install in seconds
Install ASQ Data Analysis
Copy ASQ Data Analysis into your Claude Code skills folder. Run the command in your terminal, or review the source on GitHub before installing.
terminal
npx degit https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/Administrative-Science-Quarterly-Skills/skills/asq-data-analysis ~/.claude/skills/asq-data-analysis

Requires Node.js. Downloads this skill only โ€” not the rest of the repository โ€” into your Claude Code skills folder.

Without Node.js

git clone https://github.com/brycewang-stanford/Awesome-Journal-Skills.git

Clones the whole repository, then copy the skillโ€™s own directory into your skills folder yourself.

In this catalog

Source file
Administrative-Science-Quarterly-Skills/skills/asq-data-analysis/SKILL.md in brycewang-stanford/Awesome-Journal-Skills
Installs to
~/.claude/skills/asq-data-analysis
Collection
One of 53 skills cataloged from this repository
Category
Data โ€” 812 skills

What ASQ Data Analysis does

Executes and reports qualitative or quantitative analysis for ASQ manuscripts, making the evidence-to-theory link transparent. Covers coding, data-to-theory tables, robustness checks, and mechanism evidence.

ASQ Data Analysis is cataloged under Data on DirSkills. ASQ Data Analysis comes from a repository tagged academic-research, academic-writing, agent-skills, ai-agents and anthropic.

Documentation

README

Data Analysis & Evidence (asq-data-analysis)

When to trigger

  • You have data but the path from data to theory is opaque
  • Qualitative: your quotes are decorative, not evidentiary; coding is undocumented
  • Quantitative: main results exist but robustness/alternative explanations are thin
  • Reviewers ask "how did you get from your data to these constructs?"

This is the opening of the README. Read the full README on GitHub.

Frequently asked about ASQ Data Analysis

  • What else does brycewang-stanford publish alongside ASQ Data Analysis?

    ASQ Data Analysis is one of 53 skills that DirSkills catalogs from brycewang-stanford/Awesome-Journal-Skills, the repository it ships in. Its siblings there include AAAI Artifact Evaluation, AAAI Author Response and AAAI Camera Ready. Each one is a separate skill with its own page in this directory, installs the same way ASQ Data Analysis does, and is maintained by brycewang-stanford in that same repository. The rest of the collection is listed on the brycewang-stanford/Awesome-Journal-Skills page.

  • How does ASQ Data Analysis compare to other Data skills?

    ASQ Data Analysis ranks #517 by stars among the 812 Data skills in this catalog. The most-starred ones next to it are Benchmark Methodology, Jupyter Notebook and Solana. DirSkills ranks by the star count of the repository each skill ships in, so that order reflects how popular those repositories are rather than any review of ASQ Data Analysis against them. Open each page to compare what they document and how they install.

More from brycewang-stanford/Awesome-Journal-Skills

ASQ Data Analysis is one of 53 skills cataloged on DirSkills from brycewang-stanford/Awesome-Journal-Skills.

See all 53 skills โ†’
๐Ÿ“ฆ
2026/07/20

AAAI Artifact Evaluation

Prepare AAAI artifact packages (code, data, appendices) for reproducibility while maintaining double-blind submission rules. Avoid common mistakes that lead to summary rejection.
Quality
974114
๐Ÿ“
2026/07/20

AAAI Author Response

Helps draft AAAI author responses under strict rebuttal limits. Use it to prioritize factual corrections, handle AI-generated review points, and stay within AAAI rules on length, URLs, and new results.
Writing
974114
๐Ÿ“„
2026/07/20

AAAI Camera Ready

Use when preparing an accepted AAAI paper for camera-ready submission. It covers page limits, template compliance, deanonymization, copyright transfer, registration, and final source-file checks.
Writing
974114
๐Ÿงช
2026/07/20

AAAI Experiments

Audit AAAI experiments for baselines, ablations, significance, robustness, human evaluation, and reproducibility checklist alignment, helping papers survive Phase-1 review by the broad-AI program committee.
AI Engineering
974114
๐Ÿ“
2026/07/20

AAAI Related Work

Guides writing the related work section for AAAI papers by clearly positioning novelty against archival and contemporaneous work, while adhering to AAAIโ€™s dual-submission and AI-as-source policies.
Writing
974114
๐Ÿ”
2026/07/20

AAAI Reproducibility

Audit an AAAI paper's reproducibility checklist, experimental traceability, seed/hyperparameter reporting, compute disclosure, dataset licensing, and code readiness to survive AAAI's Phase-1 rigor review.
Quality
974114