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 executing and reporting the analysis for an Organization Studies (OS) manuscript — qualitative coding and the data-to-theory ladder, process analysis, or quantitative…
Install Orgstud Data Analysis
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill orgstud-data-analysis -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills orgstud-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/Organization-Studies-Skills/skills/orgstud-data-analysis .claude/skills/orgstud-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 "orgstud-data-analysis" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/Organization-Studies-Skills/skills/orgstud-data-analysis into .claude/skills/orgstud-data-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "orgstud-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/Organization-Studies-Skills/skills/orgstud-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 orgstud-data-analysis -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills orgstud-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/Organization-Studies-Skills/skills/orgstud-data-analysis .agents/skills/orgstud-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 "orgstud-data-analysis" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/Organization-Studies-Skills/skills/orgstud-data-analysis into .agents/skills/orgstud-data-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "orgstud-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 orgstud-data-analysis -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills orgstud-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/Organization-Studies-Skills/skills/orgstud-data-analysis .cursor/skills/orgstud-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 "orgstud-data-analysis" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/Organization-Studies-Skills/skills/orgstud-data-analysis into .cursor/skills/orgstud-data-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "orgstud-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 Organization-Studies-Skills/skills/orgstud-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 orgstud-data-analysis -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills orgstud-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/Organization-Studies-Skills/skills/orgstud-data-analysis .gemini/skills/orgstud-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 "orgstud-data-analysis" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/Organization-Studies-Skills/skills/orgstud-data-analysis into .gemini/skills/orgstud-data-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "orgstud-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 orgstud-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 orgstud-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/Organization-Studies-Skills/skills/orgstud-data-analysis .github/skills/orgstud-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 "orgstud-data-analysis" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/Organization-Studies-Skills/skills/orgstud-data-analysis into .github/skills/orgstud-data-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "orgstud-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 orgstud-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 orgstud-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/Organization-Studies-Skills/skills/orgstud-data-analysis .opencode/skills/orgstud-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 "orgstud-data-analysis" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/Organization-Studies-Skills/skills/orgstud-data-analysis into .opencode/skills/orgstud-data-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "orgstud-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
orgstud-data-analysis- GitHub stars
- 1.2k
- Token cost
- ~1.6k tokens
- SKILL.md length
- 710 words
- Files
- 1
- Skills in repo
- 2,387
- Repo updated
- First seen
- Licence
- MIT
At a glance
A skill your agent uses when executing and reporting the analysis for an Organization Studies (OS) manuscript — qualitative coding and the data-to-theory ladder, process analysis, or quantitative…
- Executing and reporting the analysis for an Organization Studies (OS) manuscript — qualitative coding and the data-to-theory ladder
- SKILL.md covers When to trigger, OS expects readers to see how…, Branch A — Qualitative… and Branch B — Process analysis…, plus 6 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
- Process analysis
What it does
Orgstud Data Analysis is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when executing and reporting the analysis for an Organization Studies (OS) manuscript — qualitative coding and the data-to-theory ladder, process analysis, or quantitative estimation and robustness. Makes the evidence-to-theory link transparent; it does not design the study (see orgstud-methods).
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
- Executing and reporting the analysis for an Organization Studies (OS) manuscript — qualitative coding and the data-to-theory ladder
- Process analysis
- Quantitative estimation and robustness
Example prompts
- “/orgstud-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
Orgstud Data Analysis loads about 1.6k tokens when it runs. Until then it costs about 81 tokens; SKILL.md has 710 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). 710 words, ~1,622 tokens.
Download SKILL.mdSave it as
.claude/skills/orgstud-data-analysis/SKILL.md (or your agent's skills folder).- name
- orgstud-data-analysis
- description
- Use when executing and reporting the analysis for an Organization Studies (OS) manuscript — qualitative coding and the data-to-theory ladder, process analysis, or quantitative estimation and robustness. Makes the evidence-to-theory link transparent; it does not design the study (see orgstud-methods).
Data Analysis & Evidence (orgstud-data-analysis)
When to trigger
- You have data but the path from raw material to theory is opaque
- Qualitative: your quotes are decorative, not evidentiary; the coding is undocumented
- Process: you have events but no visible analytic structure turning them into a model
- Quantitative: main results exist but robustness and alternative explanations are thin
- A reviewer asks "how did you get from your data to these constructs?"
OS expects readers to see how data became theory
OS's interpretive, European tradition makes analytic transparency a first-class criterion — qualitative rigor is judged on its own terms, not against a quantitative yardstick. The reader must be able to audit the inference from raw data to theoretical claim. Make the analytic ladder visible.
Branch A — Qualitative analysis (the data-to-theory ladder)
- Transparent coding. Show first-order codes (informant terms), second-order themes (researcher constructs), and aggregate dimensions — the Gioia data structure — or an equivalent (Eisenhardt cross-case tables, Langley process bracketing). State who coded, how disagreements were resolved, and how iteration with theory proceeded.
- Data-to-theory table. A table linking representative raw evidence → codes → constructs, so the inference is auditable (build it with
orgstud-tables-figures). - Power quotes vs. proof quotes. A few vivid "power quotes" in the body carry the argument; corroborating "proof quotes" sit in tables/appendix. Quotes must carry the claim, not illustrate a conclusion reached elsewhere.
- Evidence for each construct. Every construct backed by patterned evidence across informants/cases, with prevalence where appropriate.
- Negative cases. Report disconfirming instances and how they refined the theory — central to trustworthiness at OS.
- Process display. For process theory, show the temporal/event structure (timeline, phase model, visual mapping); make the transitions between phases analytically explicit, not just narrated.
Branch B — Process analysis (when the contribution is a process model)
- Choose a process strategy explicitly: narrative, temporal bracketing, visual mapping, grounded theory, or alternate templates (Langley). Say why it fits.
- Identify events, sequences, and turning points; show what triggers each transition and what each phase accomplishes that the prior could not.
- Distinguish real-time from retrospective data and address the recall/hindsight risks of each.
- The output is a process model figure plus the analytic account that earns it.
Branch C — Quantitative analysis
- Main models match the design (FE/RE, event-history, multilevel, network); standard errors clustered at the right level.
- Robustness that targets the theory's threats — alternative measures, samples, specifications, endogeneity checks, modern staggered-DiD diagnostics if relevant — not a wall of tables that never address the real threat.
- Mechanism evidence. Don't stop at the reduced-form relationship; probe why (mediation/moderation or supplementary tests).
- Effect interpretation in organizational terms — magnitudes, not just significance.
Show full SKILL.md (285 more words)Show less
Either branch — the "so what" of the evidence
- Tie every analytic result back to the mechanism and the theoretical puzzle.
- Distinguish what the data can and cannot establish — overclaiming is a fast OS rejection.
- Prepare exhibits jointly with
orgstud-tables-figures.
Execution bridge (StatsPAI / Stata MCP)
Run the battery, don't just enumerate it. Full map:
execution-with-mcp. Organization Studies is largely qualitative/theoretical; use the chain below only for its quantitative-empirical papers, and say so when a study is interpretive.
- 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
- Qual: data structure (first-order → second-order → dimensions) documented
- Qual: a data-to-theory / evidence table built; quotes carry (not decorate) claims
- Qual: negative cases reported and used to refine the theory
- Process: process strategy named; turning points and transitions made explicit
- Quant: SEs clustered appropriately; robustness targets the theory's threats; magnitudes interpreted
- Mechanism is probed, not just the headline relationship
- Claims are matched to what the evidence can actually support
Anti-patterns
- "Anecdotal" qualitative work: cherry-picked quotes with no coding transparency
- Quotes that illustrate a pre-set conclusion rather than generating/supporting it
- A process "model" that is really a narrative with no analytic structure or transition logic
- Robustness theater: many tables that never address the real identification threat
- Reporting significance with no interpretation of organizational magnitude
- Overclaiming causality or generalizability beyond what the design supports
Output format
【Branch】qualitative / process / quantitative
【Data-to-theory link】data structure / process strategy / mechanism tests done
【Key evidence】power quotes, the process model, or main estimates
【Trustworthiness/robustness】checks completed + gaps (negative cases, clustering, alt explanations)
【What evidence cannot show】explicit limits
【Next skill】orgstud-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 Organization-Studies-Skills/skills/orgstud-data-analysis of brycewang-stanford/Awesome-Journal-Skills.
Open the folder on GitHubat commit 932eb23
Compare with similar skills
Orgstud 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 |
|---|---|---|---|---|---|---|
| Orgstud 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 | 205 | 2 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 Orgstud Data Analysis
What does Orgstud Data Analysis do?
A skill your agent uses when executing and reporting the analysis for an Organization Studies (OS) manuscript — qualitative coding and the data-to-theory ladder, process analysis, or quantitative…. Orgstud Data Analysis is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when executing and reporting the analysis for an Organization Studies (OS) manuscript — qualitative coding and the data-to-theory ladder, process analysis, or quantitative estimation and robustness.
When should I use Orgstud Data Analysis?
Orgstud Data Analysis fits situations like: executing and reporting the analysis for an Organization Studies (OS) manuscript — qualitative coding and the data-to-theory ladder; process analysis; quantitative estimation and robustness.
How do I install Orgstud Data Analysis in Claude Code?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill orgstud-data-analysis -a claude-code`. Or copy the skill folder (Organization-Studies-Skills/skills/orgstud-data-analysis in brycewang-stanford/Awesome-Journal-Skills) into .claude/skills/orgstud-data-analysis in your project. Claude Code loads it when a task matches its description.
How do I install Orgstud Data Analysis in Codex?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill orgstud-data-analysis -a codex`. Or copy the skill folder (Organization-Studies-Skills/skills/orgstud-data-analysis in brycewang-stanford/Awesome-Journal-Skills) into .agents/skills/orgstud-data-analysis in your project. Codex loads it when a task matches its description.
Can I use Orgstud 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 orgstud-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/orgstud-data-analysis, .gemini/skills/orgstud-data-analysis, .github/skills/orgstud-data-analysis and .opencode/skills/orgstud-data-analysis in your project.
What does Orgstud Data Analysis need to run?
SKILL.md names no scripts, command-line tools or credentials: Orgstud Data Analysis is instructions for the agent only.
Does Orgstud 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 Orgstud 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 Orgstud Data Analysis use?
Orgstud 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 Orgstud Data Analysis use?
About 1.6k tokens (SKILL.md is roughly 6.5k 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 Orgstud Data Analysis?
Skills that share tags, products or a category with Orgstud 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, 205 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 Orgstud Data Analysis?
brycewang-stanford (a GitHub user) maintains it in brycewang-stanford/Awesome-Journal-Skills, which has 1,216 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.