Exploratory Data Analysis
spacering-net/codeg
Perform comprehensive exploratory data analysis on scientific data files across 200+ file formats.
A skill your agent uses when the execution and credibility of the analysis is the bottleneck for a Journal of Management Studies (JMS) manuscript — regression/SEM and robustness for quantitative…
Install Jms Data Analysis
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill jms-data-analysis -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills jms-data-analysis --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/brycewang-stanford/Awesome-Journal-Skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/Journal-of-Management-Studies-Skills/skills/jms-data-analysis .claude/skills/jms-data-analysis && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "jms-data-analysis" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/Journal-of-Management-Studies-Skills/skills/jms-data-analysis into .claude/skills/jms-data-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "jms-data-analysis", 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.
$skill-installer install https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/Journal-of-Management-Studies-Skills/skills/jms-data-analysisType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill jms-data-analysis -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills jms-data-analysis --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/brycewang-stanford/Awesome-Journal-Skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/Journal-of-Management-Studies-Skills/skills/jms-data-analysis .agents/skills/jms-data-analysis && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "jms-data-analysis" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/Journal-of-Management-Studies-Skills/skills/jms-data-analysis into .agents/skills/jms-data-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "jms-data-analysis", 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/Awesome-Journal-Skills --skill jms-data-analysis -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills jms-data-analysis --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/brycewang-stanford/Awesome-Journal-Skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/Journal-of-Management-Studies-Skills/skills/jms-data-analysis .cursor/skills/jms-data-analysis && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "jms-data-analysis" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/Journal-of-Management-Studies-Skills/skills/jms-data-analysis into .cursor/skills/jms-data-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "jms-data-analysis", 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.
$ gemini skills install https://github.com/brycewang-stanford/Awesome-Journal-Skills.git --path Journal-of-Management-Studies-Skills/skills/jms-data-analysis--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill jms-data-analysis -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills jms-data-analysis --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/brycewang-stanford/Awesome-Journal-Skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/Journal-of-Management-Studies-Skills/skills/jms-data-analysis .gemini/skills/jms-data-analysis && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "jms-data-analysis" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/Journal-of-Management-Studies-Skills/skills/jms-data-analysis into .gemini/skills/jms-data-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "jms-data-analysis", 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/Awesome-Journal-Skills jms-data-analysisInstalls 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/Awesome-Journal-Skills --skill jms-data-analysis -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/brycewang-stanford/Awesome-Journal-Skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/Journal-of-Management-Studies-Skills/skills/jms-data-analysis .github/skills/jms-data-analysis && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "jms-data-analysis" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/Journal-of-Management-Studies-Skills/skills/jms-data-analysis into .github/skills/jms-data-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "jms-data-analysis", 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/Awesome-Journal-Skills --skill jms-data-analysis -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/Awesome-Journal-Skills jms-data-analysis --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/brycewang-stanford/Awesome-Journal-Skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/Journal-of-Management-Studies-Skills/skills/jms-data-analysis .opencode/skills/jms-data-analysis && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "jms-data-analysis" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/Journal-of-Management-Studies-Skills/skills/jms-data-analysis into .opencode/skills/jms-data-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "jms-data-analysis", 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
jms-data-analysis- GitHub stars
- 1.2k
- Token cost
- ~1.5k tokens
- SKILL.md length
- 646 words
- Files
- 1
- Skills in repo
- 2,387
- Repo updated
- First seen
- Licence
- MIT
At a glance
A skill your agent uses when the execution and credibility of the analysis is the bottleneck for a Journal of Management Studies (JMS) manuscript — regression/SEM and robustness for quantitative…
- Trustworthiness for qualitative work
- SKILL.md covers When to trigger, The JMS analysis bar — two…, Quantitative path and Qualitative path, plus 4 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
- Tasks that involve Data analysis
What it does
Jms Data Analysis is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when the execution and credibility of the analysis is the bottleneck for a Journal of Management Studies (JMS) manuscript — regression/SEM and robustness for quantitative work, OR coding, abduction, and trustworthiness for qualitative work. Runs and defends the analysis; it does not design the study (jms-methods) or build exhibits (jms-tables-figures).
Its SKILL.md is about 1.5k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in Data & Analytics, covering Data analysis. The repository describes itself as: Journal-specific Claude Code/Codex skill packs covering mainstream journals — AER, QJE, Nature, Cell, 管理世界, 经济研究 & 200+ more — your fast track to getting published. ｜ 覆盖主流期刊的… The licence is MIT.
When your agent uses it
- Trustworthiness for qualitative work
- Tasks that involve Data analysis
Example prompts
- “/jms-data-analysis”
What it can do on your machine
Read from SKILL.md and the folder at commit 932eb23. 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
No scripts in the folder and no shell commands in SKILL.md.
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
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
Jms Data Analysis loads about 1.5k tokens when it runs. Until then it costs about 94 tokens; SKILL.md has 646 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); files beside SKILL.md are not scanned.
SKILL.md
The full file from brycewang-stanford/Awesome-Journal-Skills at commit 932eb23, republished under its MIT licence (© brycewang-stanford). 646 words, ~1,479 tokens.
Download SKILL.mdSave it as
.claude/skills/jms-data-analysis/SKILL.md (or your agent's skills folder).- name
- jms-data-analysis
- description
- Use when the execution and credibility of the analysis is the bottleneck for a Journal of Management Studies (JMS) manuscript — regression/SEM and robustness for quantitative work, OR coding, abduction, and trustworthiness for qualitative work. Runs and defends the analysis; it does not design the study (jms-methods) or build exhibits (jms-tables-figures).
Data Analysis (jms-data-analysis)
When to trigger
- Estimates are in but reviewers question endogeneity, robustness, or the indirect-effect claim
- A qualitative analysis reaches findings but the path from data to constructs is not auditable
- Effects hinge on a single specification with no robustness
- A mediation/moderation result is reported without the analysis JMS expects
- A reviewer says "the analysis does not support the claim" or "I can't see how you got here"
The JMS analysis bar — two idioms, one standard
JMS judges analysis by whether it credibly supports the theoretical claim, in whichever idiom the study uses. Quantitative work is held to identification and robustness standards; qualitative work is held to trustworthiness and transparency standards. Use the path that matches your design; do not import quant criteria (p-values, effect sizes) to judge a qualitative paper, or qualitative looseness into a quantitative one.
Quantitative path
- Specification & estimator: match the estimator to the data structure (OLS/GLM, fixed effects for panels, SEM for latent constructs and full mediation models, multilevel models for nested data). State why.
- Mediation done right: test indirect effects with bootstrapped confidence intervals (not Baron–Kenny steps alone); but remember an indirect effect is evidence for a theorised mechanism, not a substitute for theorising it.
- Moderation: plot the interaction; report simple slopes and the region of significance; do not over-read a marginal interaction.
- Endogeneity & robustness: run the identification strategy planned in
jms-methods(FE, IV/2SLS, DiD, matching) and a robustness battery — alternative measures, alternative samples, controls in/out — each tied to a named threat, not a fishing expedition. - Measurement evidence: report reliability (alpha/CR), convergent/discriminant validity (AVE), and CFA fit; address CMB with a designed test, not only Harman.
Qualitative path
- Coding transparency: show the move from first-order codes → second-order themes → aggregate dimensions; a reader should be able to trace a quote to a construct.
- Abductive logic: make the iteration between data and theory explicit — surprising observations, the candidate explanations considered, why the retained one fits best. JMS rewards visible abduction, not a tidy after-the-fact story.
- Evidentiary support: a representative-quotes table tying each theme to data; report disconfirming/negative cases and how they refined the model.
- Trustworthiness: state the procedures used (audit trail, member checking, inter-coder reliability where appropriate, prolonged engagement) so credibility is demonstrable.
- From narrative to mechanism: for process work, show what drives the transitions across phases, not just the sequence.
Show full SKILL.md (260 more words)Show less
Execution bridge (StatsPAI / Stata MCP)
Run the battery, don't just enumerate it. Full map:
execution-with-mcp. JMS mixes qualitative and quantitative management research; the chain below is for the quantitative-empirical lane.
- Many outcomes / specifications:
romano_wolf(step-down FWER) orbenjamini_hochberg— report the adjusted threshold. - OVB sensitivity:
oster_delta/sensemakr. - Inference:
wild_cluster_bootstrap(few clusters),twoway_cluster/conley; multilevel data → cluster at the right level. - Re-fit off one handle:
audit_result(result_id)lists the missing checks and the exactsuggest_functionfor each. - Exhibits:
etable/did_summary_to_latexfrom the handle — no retyped numbers.
Keep the decisive checks in the body and the exhaustive battery in the appendix. See the executed chain in the JF execution walkthrough.
Checklist
- Path chosen (quantitative / qualitative) and matched to the design
- Quant: estimator fits the data; mediation via bootstrapped CIs; interactions plotted with simple slopes
- Quant: each robustness check tied to a named threat; CMB addressed by design; CFA/validity reported
- Qual: first-order → second-order → aggregate-dimension chain is auditable
- Qual: abductive reasoning visible; representative quotes table; negative cases reported
- Qual: trustworthiness procedures stated
- The claim never exceeds what the analysis supports
Anti-patterns
- Mechanism by mediation: claiming a process exists only because the indirect effect is significant
- Robustness theatre: a wall of checks that never names the threat each one rules out
- p-hacking / specification mining: the one significant model among many, presented as the model
- Quote-mining: cherry-picked quotes with no systematic coding behind them
- Tidy abduction: a too-clean narrative that hides the messy data-theory iteration reviewers want to see
- Idiom confusion: judging a qualitative paper by sample size and significance, or a quant paper by "richness"
Output format
【Path】quantitative / qualitative
【Quant】estimator + why; mediation (bootstrap CI); moderation (simple slopes); robustness→threats; CMB/CFA
【Qual】coding chain (1st→2nd→dimensions); abduction made visible; quotes table; negative cases; trustworthiness
【Claim support】does the analysis carry the theoretical claim? gaps …
【Next step】jms-tables-figures© brycewang-stanford, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
Just SKILL.md in Journal-of-Management-Studies-Skills/skills/jms-data-analysis of brycewang-stanford/Awesome-Journal-Skills.
Open the folder on GitHubat commit 932eb23
Compare with similar skills
Jms Data Analysis 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 |
|---|---|---|---|---|---|---|
| Jms Data Analysis this skillbrycewang-stanford/Awesome-Journal-Skills | 1.2k | — | ~1.5k | Automated safety check: Pass | MIT | |
| Exploratory Data Analysisspacering-net/codeg | 3.9k | 14 repos | ~3.6k | Automated safety check: Pass | MIT | |
| Excel and CSV Data Analysisbytedance/deer-flow | 84k | 4 repos | ~2.2k | Automated safety check: Pass | MIT | |
| Exploratory Data AnalysisOleafly/Oleafly | 209 | 2 repos | ~3.4k | Automated safety check: Notes | MIT | |
| Pandas ProJeffallan/claude-skills | 12k | 1 repos | ~1.5k | Automated safety check: Pass | MIT | |
| Python Executorcortega26/chile-hub | 113 | 2 repos | ~1.5k | Automated safety check: Pass | MIT |
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Categories
Questions about Jms Data Analysis
What does Jms Data Analysis do?
A skill your agent uses when the execution and credibility of the analysis is the bottleneck for a Journal of Management Studies (JMS) manuscript — regression/SEM and robustness for quantitative…. Jms Data Analysis is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when the execution and credibility of the analysis is the bottleneck for a Journal of Management Studies (JMS) manuscript — regression/SEM and robustness for quantitative work, OR coding, abduction, and trustworthiness for qualitative work.
When should I use Jms Data Analysis?
Jms Data Analysis fits situations like: trustworthiness for qualitative work; tasks that involve Data analysis.
How do I install Jms Data Analysis in Claude Code?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill jms-data-analysis -a claude-code`. Or copy the skill folder (Journal-of-Management-Studies-Skills/skills/jms-data-analysis in brycewang-stanford/Awesome-Journal-Skills) into .claude/skills/jms-data-analysis in your project. Claude Code loads it when a task matches its description.
How do I install Jms Data Analysis in Codex?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill jms-data-analysis -a codex`. Or copy the skill folder (Journal-of-Management-Studies-Skills/skills/jms-data-analysis in brycewang-stanford/Awesome-Journal-Skills) into .agents/skills/jms-data-analysis in your project. Codex loads it when a task matches its description.
Can I use Jms Data Analysis 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/Awesome-Journal-Skills --skill jms-data-analysis -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/jms-data-analysis, .gemini/skills/jms-data-analysis, .github/skills/jms-data-analysis and .opencode/skills/jms-data-analysis in your project.
What does Jms Data Analysis need to run?
SKILL.md names no scripts, command-line tools or credentials: Jms Data Analysis is instructions for the agent only.
Does Jms Data Analysis access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is Jms Data Analysis 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. Review the folder before installing.
What licence does Jms Data Analysis use?
Jms Data Analysis is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Jms Data Analysis use?
About 1.5k tokens (SKILL.md is roughly 5.9k 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 Jms Data Analysis?
Skills that share tags, products or a category with Jms Data Analysis: Exploratory Data Analysis (spacering-net/codeg, 3.9k stars), Excel and CSV Data Analysis (bytedance/deer-flow, 84k stars), Exploratory Data Analysis (Oleafly/Oleafly, 209 stars) and Pandas Pro (Jeffallan/claude-skills, 12k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Jms Data Analysis?
brycewang-stanford (a GitHub user) maintains it in brycewang-stanford/Awesome-Journal-Skills, which has 1,228 GitHub stars. The repository holds 2,387 skills in this directory. The repository was last updated on September 27, 2026.
Source: brycewang-stanford/Awesome-Journal-Skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.