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 estimating and reporting results for a Journal of International Marketing (JIM) manuscript — measurement-invariance testing (MGCFA/alignment), multilevel models with…
Install Jim Data Analysis
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill jim-data-analysis -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills jim-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-International-Marketing-Skills/skills/jim-data-analysis .claude/skills/jim-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 "jim-data-analysis" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/Journal-of-International-Marketing-Skills/skills/jim-data-analysis into .claude/skills/jim-data-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "jim-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-International-Marketing-Skills/skills/jim-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 jim-data-analysis -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills jim-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-International-Marketing-Skills/skills/jim-data-analysis .agents/skills/jim-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 "jim-data-analysis" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/Journal-of-International-Marketing-Skills/skills/jim-data-analysis into .agents/skills/jim-data-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "jim-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 jim-data-analysis -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills jim-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-International-Marketing-Skills/skills/jim-data-analysis .cursor/skills/jim-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 "jim-data-analysis" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/Journal-of-International-Marketing-Skills/skills/jim-data-analysis into .cursor/skills/jim-data-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "jim-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-International-Marketing-Skills/skills/jim-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 jim-data-analysis -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills jim-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-International-Marketing-Skills/skills/jim-data-analysis .gemini/skills/jim-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 "jim-data-analysis" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/Journal-of-International-Marketing-Skills/skills/jim-data-analysis into .gemini/skills/jim-data-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "jim-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 jim-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 jim-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-International-Marketing-Skills/skills/jim-data-analysis .github/skills/jim-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 "jim-data-analysis" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/Journal-of-International-Marketing-Skills/skills/jim-data-analysis into .github/skills/jim-data-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "jim-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 jim-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 jim-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-International-Marketing-Skills/skills/jim-data-analysis .opencode/skills/jim-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 "jim-data-analysis" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/Journal-of-International-Marketing-Skills/skills/jim-data-analysis into .opencode/skills/jim-data-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "jim-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
jim-data-analysis- GitHub stars
- 1.2k
- Token cost
- ~1.6k tokens
- SKILL.md length
- 687 words
- Files
- 1
- Skills in repo
- 2,387
- Repo updated
- First seen
- Licence
- MIT
At a glance
A skill your agent uses when estimating and reporting results for a Journal of International Marketing (JIM) manuscript — measurement-invariance testing (MGCFA/alignment), multilevel models with…
- Multilevel models with country-level predictors
- SKILL.md covers When to trigger, Invariance first — nothing…, Match the estimator to the… and Report so the cross-national…, plus 4 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
- Multi-group SEM
What it does
Jim Data Analysis is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when estimating and reporting results for a Journal of International Marketing (JIM) manuscript — measurement-invariance testing (MGCFA/alignment), multilevel models with country-level predictors, multi-group SEM, and multi-country panels. It executes and reports; jim-methods designed the study.
Its SKILL.md is about 1.6k 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
- Multilevel models with country-level predictors
- Multi-group SEM
- Multi-country panels
Example prompts
- “/jim-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
Jim Data Analysis loads about 1.6k tokens when it runs. Until then it costs about 80 tokens; SKILL.md has 687 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). 687 words, ~1,643 tokens.
Download SKILL.mdSave it as
.claude/skills/jim-data-analysis/SKILL.md (or your agent's skills folder).- name
- jim-data-analysis
- description
- Use when estimating and reporting results for a Journal of International Marketing (JIM) manuscript — measurement-invariance testing (MGCFA/alignment), multilevel models with country-level predictors, multi-group SEM, and multi-country panels. It executes and reports; jim-methods designed the study.
Cross-National Data Analysis (jim-data-analysis)
When to trigger
- Multi-country data are in and the invariance battery must be run before anything else
- Country-level moderators need estimating (HLM, multi-group SEM, cross-level interactions)
- Latent means or path coefficients are about to be compared across countries
- A reviewer writes "the cross-national comparisons are not interpretable as reported"
Invariance first — nothing compares until it passes
Run the MGCFA ladder per construct, in order, and report every rung:
| Step | Constraint added | Licenses you to… |
|---|---|---|
| Configural | same factor structure | claim the construct exists everywhere |
| Metric | equal loadings | compare structural paths / correlations across countries |
| Scalar | equal intercepts | compare latent means across countries |
Decision rules: χ² difference plus practical criteria (ΔCFI ≤ .01; monitor ΔRMSEA). When full invariance fails: release the minimum number of parameters for partial invariance (at least two invariant items per construct, per the Steenkamp–Baumgartner protocol) and restate exactly which comparisons remain licensed. With many countries (8+), pairwise MGCFA explodes — use the alignment method and report the proportion of non-invariant parameters (≤25% rule of thumb). If scalar invariance dies and cannot be partially rescued, mean-comparison hypotheses are off the table; say so in the paper rather than burying it.
Also run: response-style controls (model ARS/ERS factors or covariates as planned in design) and per-country reliability/validity (CR, AVE, discriminant checks reported for each country, not pooled).
Match the estimator to the cross-national structure
| Data structure | Estimator | Reporting keys |
|---|---|---|
| Consumers nested in countries (10+ countries) | Multilevel / HLM with country-level predictors | ICC first; random slopes for moderated effects; group-mean vs. grand-mean centering stated |
| Few countries (2–4) | Multi-group SEM with invariance constraints | path-difference tests across groups, not eyeballed coefficients |
| Cross-level moderation | random-slope HLM or MSEM | the slope variance must be nonzero before a country variable can explain it |
| Firm export panels | FE / DiD (staggered-adoption estimators) / selection models | cluster at firm or country per the variation; pre-trends where causal |
| Country dyads (home–host) | dyadic models with distance variables | control both origin and destination effects |
| Meta-analytic | random-effects + meta-regression on country dimensions | between-study heterogeneity decomposed |
Small-N-countries warning: with fewer than ~10 countries, country-level regression coefficients are unstable — prefer multi-group contrasts, fixed effects, or Bayesian multilevel with informative priors, and never narrate 5 countries as a "test" of a continuous cultural dimension.
Show full SKILL.md (321 more words)Show less
Report so the cross-national claim is auditable
- Invariance table is mandatory — steps, fit per step, Δ-statistics, decision. It is the first table JIM methods reviewers look for.
- Per-country descriptives and correlations (or a Web Appendix panel), not pooled-only.
- Standardized effects with CIs; for mediation, bootstrapped indirect effects per group or conditional on the country moderator.
- For every country difference claimed: the formal test of the difference (constrained vs. free model; interaction coefficient), never two separate significance verdicts.
- Translate the headline effect into a cross-border managerial magnitude: adaptation lift in market A vs. B, export-revenue elasticity, the country profile where the strategy flips sign.
Execution bridge (StatsPAI / Stata MCP)
Run the battery end-to-end instead of enumerating it. Full map: execution-with-mcp. For JIM's structures: multi-country panels via detect_design → recommend → fit with as_handle=true → audit_result; staggered policy variation via callaway_santanna / sun_abraham with honest_did_from_result; few-cluster (few-country) inference via wild_cluster_bootstrap; many-outcome hypothesis families via romano_wolf; OVB sensitivity via oster_delta / sensemakr; exhibits exported from the result handle (etable) so no number is retyped. HLM and measurement-invariance runs (MGCFA ladders, alignment) execute in lavaan/Mplus-lane scripts under resources/code/ — keep the per-step fit log as the audit trail; SEM path models follow the same handle-then-audit discipline.
Checklist
- Invariance ladder run and tabled per construct; licensed comparisons restated
- Partial invariance (≥2 invariant items) or alignment used where full invariance failed
- Response styles controlled; per-country reliability and validity reported
- Estimator matches nesting; ICC and centering choices stated for multilevel models
- Every claimed country difference backed by a formal difference test
- Small-N-countries limits acknowledged; no continuous-dimension claims from 4 countries
- Headline results carry cross-border managerial magnitudes
Anti-patterns
- Comparing raw scale means across countries with no scalar-invariance evidence
- "Significant in Germany, not in Brazil" offered as evidence of moderation
- Country dummies interpreted as cultural effects
- HLM with 6 countries and three country-level predictors
- Pooled reliability statistics hiding a collapsed construct in one country
- An invariance failure silently absorbed by dropping the offending country
Output format
【Invariance】per construct: configural/metric/scalar (full/partial/alignment) + decision rule
【Licensed comparisons】means / paths / neither — per construct
【Estimator】structure-matched model + clustering/centering choices
【Country-difference tests】formal Δ-tests for each claimed difference: done?
【Managerial magnitude】headline effect in cross-border decision units
【Robustness】response styles / small-N limits / identification threat addressed
【Next skill】jim-contribution-framing© 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-International-Marketing-Skills/skills/jim-data-analysis of brycewang-stanford/Awesome-Journal-Skills.
Open the folder on GitHubat commit 932eb23
Compare with similar skills
Jim 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 |
|---|---|---|---|---|---|---|
| Jim Data Analysis this skillbrycewang-stanford/Awesome-Journal-Skills | 1.2k | — | ~1.6k | Automated safety check: Pass | MIT | |
| Exploratory Data Analysisspacering-net/codeg | 3.8k | 15 repos | ~3.6k | Automated safety check: Pass | MIT | |
| Excel and CSV Data Analysisbytedance/deer-flow | 83k | 4 repos | ~2.2k | Automated safety check: Pass | MIT | |
| Exploratory Data AnalysisOleafly/Oleafly | 206 | 3 repos | ~3.4k | Automated safety check: Notes | MIT | |
| Python Executorcortega26/chile-hub | 113 | 2 repos | ~1.5k | Automated safety check: Pass | MIT | |
| Agentic Kaggle WorkflowFrankS-IntelLab/agentic-kaggle-skill | 188 | — | ~4k | Automated safety check: Pass | MIT |
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Questions about Jim Data Analysis
What does Jim Data Analysis do?
A skill your agent uses when estimating and reporting results for a Journal of International Marketing (JIM) manuscript — measurement-invariance testing (MGCFA/alignment), multilevel models with…. Jim Data Analysis is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when estimating and reporting results for a Journal of International Marketing (JIM) manuscript — measurement-invariance testing (MGCFA/alignment), multilevel models with country-level predictors, multi-group SEM, and multi-country panels.
When should I use Jim Data Analysis?
Jim Data Analysis fits situations like: multilevel models with country-level predictors; multi-group SEM; multi-country panels.
How do I install Jim Data Analysis in Claude Code?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill jim-data-analysis -a claude-code`. Or copy the skill folder (Journal-of-International-Marketing-Skills/skills/jim-data-analysis in brycewang-stanford/Awesome-Journal-Skills) into .claude/skills/jim-data-analysis in your project. Claude Code loads it when a task matches its description.
How do I install Jim Data Analysis in Codex?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill jim-data-analysis -a codex`. Or copy the skill folder (Journal-of-International-Marketing-Skills/skills/jim-data-analysis in brycewang-stanford/Awesome-Journal-Skills) into .agents/skills/jim-data-analysis in your project. Codex loads it when a task matches its description.
Can I use Jim 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 jim-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/jim-data-analysis, .gemini/skills/jim-data-analysis, .github/skills/jim-data-analysis and .opencode/skills/jim-data-analysis in your project.
What does Jim Data Analysis need to run?
SKILL.md names no scripts, command-line tools or credentials: Jim Data Analysis is instructions for the agent only.
Does Jim 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 Jim 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 Jim Data Analysis use?
Jim 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 Jim Data Analysis use?
About 1.6k tokens (SKILL.md is roughly 6.6k 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 Jim Data Analysis?
Skills that share tags, products or a category with Jim Data Analysis: Exploratory Data Analysis (spacering-net/codeg, 3.8k stars), Excel and CSV Data Analysis (bytedance/deer-flow, 83k stars), Exploratory Data Analysis (Oleafly/Oleafly, 206 stars) and Python Executor (cortega26/chile-hub, 113 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Jim Data Analysis?
brycewang-stanford (a GitHub user) maintains it in brycewang-stanford/Awesome-Journal-Skills, which has 1,219 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.