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 a Human Relations (HR) manuscript — qualitative coding and data-to-theory construction, critical interpretation, or quantitative…
Install Humrel Data Analysis
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill humrel-data-analysis -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills humrel-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/Human-Relations-Skills/skills/humrel-data-analysis .claude/skills/humrel-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 "humrel-data-analysis" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/Human-Relations-Skills/skills/humrel-data-analysis into .claude/skills/humrel-data-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "humrel-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/Human-Relations-Skills/skills/humrel-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 humrel-data-analysis -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills humrel-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/Human-Relations-Skills/skills/humrel-data-analysis .agents/skills/humrel-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 "humrel-data-analysis" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/Human-Relations-Skills/skills/humrel-data-analysis into .agents/skills/humrel-data-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "humrel-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 humrel-data-analysis -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills humrel-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/Human-Relations-Skills/skills/humrel-data-analysis .cursor/skills/humrel-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 "humrel-data-analysis" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/Human-Relations-Skills/skills/humrel-data-analysis into .cursor/skills/humrel-data-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "humrel-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 Human-Relations-Skills/skills/humrel-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 humrel-data-analysis -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills humrel-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/Human-Relations-Skills/skills/humrel-data-analysis .gemini/skills/humrel-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 "humrel-data-analysis" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/Human-Relations-Skills/skills/humrel-data-analysis into .gemini/skills/humrel-data-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "humrel-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 humrel-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 humrel-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/Human-Relations-Skills/skills/humrel-data-analysis .github/skills/humrel-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 "humrel-data-analysis" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/Human-Relations-Skills/skills/humrel-data-analysis into .github/skills/humrel-data-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "humrel-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 humrel-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 humrel-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/Human-Relations-Skills/skills/humrel-data-analysis .opencode/skills/humrel-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 "humrel-data-analysis" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/Human-Relations-Skills/skills/humrel-data-analysis into .opencode/skills/humrel-data-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "humrel-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
humrel-data-analysis- GitHub stars
- 1.2k
- Token cost
- ~1.6k tokens
- SKILL.md length
- 712 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 a Human Relations (HR) manuscript — qualitative coding and data-to-theory construction, critical interpretation, or quantitative…
- Executing and reporting the analysis for a Human Relations (HR) manuscript — qualitative coding and data-to-theory construction
- SKILL.md covers When to trigger, The HR bar: make the inference…, Branch A — Qualitative… and Branch B — Critical analysis, plus 6 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
- Critical interpretation
What it does
Humrel Data Analysis is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when executing and reporting the analysis for a Human Relations (HR) manuscript — qualitative coding and data-to-theory construction, critical interpretation, or quantitative estimation and robustness. Makes the evidence-to-theory link transparent; it does not design the study (see humrel-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 a Human Relations (HR) manuscript — qualitative coding and data-to-theory construction
- Critical interpretation
- Quantitative estimation and robustness
Example prompts
- “/humrel-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
Humrel Data Analysis loads about 1.6k tokens when it runs. Until then it costs about 81 tokens; SKILL.md has 712 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). 712 words, ~1,614 tokens.
Download SKILL.mdSave it as
.claude/skills/humrel-data-analysis/SKILL.md (or your agent's skills folder).- name
- humrel-data-analysis
- description
- Use when executing and reporting the analysis for a Human Relations (HR) manuscript — qualitative coding and data-to-theory construction, critical interpretation, or quantitative estimation and robustness. Makes the evidence-to-theory link transparent; it does not design the study (see humrel-methods).
Data Analysis & Evidence (humrel-data-analysis)
When to trigger
- You have data but the path from data to theory is opaque
- Qualitative: quotes are decorative, not evidentiary; coding is undocumented
- Critical: the interpretation reads as assertion rather than disciplined reading of the material
- Quantitative: main results exist but theorizing stops at the coefficient
- A reviewer asks "how did you get from your data to these constructs?"
The HR bar: make the inference auditable, then theorize beyond it
HR judges each tradition on its own terms, but every branch must satisfy the same demand: a reader should be able to see how the evidence became theory, and the analysis must yield the "unique and substantive theoretical contribution" the journal screens for. The relational, social nature of work should remain visible in the analysis — not abstracted away into variables or quotations stripped of context.
Branch A — Qualitative analysis (the data-to-theory ladder)
- Transparent coding. Document first-order codes (informant terms), second-order themes (your constructs), and aggregate dimensions — a Gioia-style data structure — or an equivalent (Eisenhardt cross-case, Langley process bracketing). State who coded, how disagreements were resolved, and how iteration proceeded.
- Data-to-theory table. Link representative raw evidence → codes → constructs so the inference is auditable (build with
humrel-tables-figures). - Power quotes vs. proof quotes. A few vivid quotes in the body; corroborating quotes in tables/appendix. Quotes must carry the claim, not illustrate it after the fact.
- Patterned evidence + negative cases. Back each construct with evidence across informants; report disconfirming instances and how they refined the theory.
- Process display. For process theory, show the temporal/event structure (timeline, phase model, visual map).
Branch B — Critical analysis
- Make the interpretive procedure explicit (how texts/talk/practices were read; which discursive or material features mattered) so the reading is disciplined, not just asserted.
- Keep reflexivity active: how your standpoint shaped the interpretation.
- Tie the critique to a constructive theoretical claim — the analysis should leave readers with a new way to understand, not only a debunking.
Branch C — Quantitative analysis
- Main models match the design (multilevel/mixed, panel FE, SEM, event-history) with standard errors clustered at the right level.
- Construct validity in the analysis: report reliabilities, factor structure, and discriminant validity; address common-method concerns with design or statistical remedies where same-source.
- Robustness that targets the theory's threats: alternative measures, samples, specifications, and endogeneity checks — not a table farm.
- Interpret magnitudes in substantive, relational terms, not significance stars alone; HR house style for exhibits avoids decorating tables with asterisks as the "result."
- Probe the mechanism (mediation/moderation or supplementary tests), don't stop at X→Y.
Show full SKILL.md (297 more words)Show less
Either branch — the "so what" of the evidence
- Tie every result back to the mechanism and the theoretical surprise.
- Distinguish what the data can and cannot establish — overclaiming is a fast route to rejection.
- Mind the data transparency matrix: if several papers draw on the same dataset, you must declare them and provide a matrix of which variables/quotations each uses; failure is grounds for rejection (检索于 2026-06；以官网为准).
Execution bridge (StatsPAI / Stata MCP)
Run the battery, don't just enumerate it. Full map:
execution-with-mcp. Human Relations blends critical/qualitative and quantitative work; apply the chain below to its survey / experimental quantitative papers.
- 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 table built; quotes carry (not decorate) claims; negative cases reported
- Critical: interpretive procedure explicit; reflexivity active; claim is constructive
- Quant: reliabilities/validity reported; SEs clustered correctly; magnitudes interpreted
- Mechanism probed, not just the headline relationship
- Claims matched to what the evidence can support; limits stated
- Same-dataset papers declared with a transparency matrix if applicable
Anti-patterns
- "Anecdotal" qualitative work: cherry-picked quotes, no coding transparency
- Quotes that illustrate a pre-set conclusion rather than supporting it
- Critical readings asserted with no statement of how the material was analyzed
- Robustness theater that never addresses the real threat
- Reporting significance with no substantive magnitude or relational meaning
- Concealing other papers built on the same dataset
Output format
【Journal】Human Relations
【Skill】humrel-data-analysis
【Branch】qualitative / critical / quantitative
【Data-to-theory link】data structure / interpretive procedure / mechanism tests
【Key evidence】power quotes or main estimates (with magnitude)
【Robustness/trustworthiness】checks done + gaps
【Transparency】same-dataset matrix needed? (yes/no/NA)
【Next skill】humrel-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 Human-Relations-Skills/skills/humrel-data-analysis of brycewang-stanford/Awesome-Journal-Skills.
Open the folder on GitHubat commit 932eb23
Compare with similar skills
Humrel 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 |
|---|---|---|---|---|---|---|
| Humrel Data Analysis this skillbrycewang-stanford/Awesome-Journal-Skills | 1.2k | — | ~1.6k | 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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Questions about Humrel Data Analysis
What does Humrel Data Analysis do?
A skill your agent uses when executing and reporting the analysis for a Human Relations (HR) manuscript — qualitative coding and data-to-theory construction, critical interpretation, or quantitative…. Humrel Data Analysis is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when executing and reporting the analysis for a Human Relations (HR) manuscript — qualitative coding and data-to-theory construction, critical interpretation, or quantitative estimation and robustness.
When should I use Humrel Data Analysis?
Humrel Data Analysis fits situations like: executing and reporting the analysis for a Human Relations (HR) manuscript — qualitative coding and data-to-theory construction; critical interpretation; quantitative estimation and robustness.
How do I install Humrel Data Analysis in Claude Code?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill humrel-data-analysis -a claude-code`. Or copy the skill folder (Human-Relations-Skills/skills/humrel-data-analysis in brycewang-stanford/Awesome-Journal-Skills) into .claude/skills/humrel-data-analysis in your project. Claude Code loads it when a task matches its description.
How do I install Humrel Data Analysis in Codex?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill humrel-data-analysis -a codex`. Or copy the skill folder (Human-Relations-Skills/skills/humrel-data-analysis in brycewang-stanford/Awesome-Journal-Skills) into .agents/skills/humrel-data-analysis in your project. Codex loads it when a task matches its description.
Can I use Humrel 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 humrel-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/humrel-data-analysis, .gemini/skills/humrel-data-analysis, .github/skills/humrel-data-analysis and .opencode/skills/humrel-data-analysis in your project.
What does Humrel Data Analysis need to run?
SKILL.md names no scripts, command-line tools or credentials: Humrel Data Analysis is instructions for the agent only.
Does Humrel 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 Humrel 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 Humrel Data Analysis use?
Humrel 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 Humrel 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 Humrel Data Analysis?
Skills that share tags, products or a category with Humrel 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 Humrel 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.