Agent skill

Data Profile

by brycewang-stanford in brycewang-stanford/Auto-Empirical-Research-Skills

Generate a complete, manuscript-ready data profile: demographics summary table, scale identification with reliability (alpha, omega, CFA), comprehensive codebook, sample characteristics, and…

Custom licenceAuto-check passed

Install Data Profile

skills CLI

$ npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill data-profile -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI

$ gh skill install brycewang-stanford/Auto-Empirical-Research-Skills data-profile --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy

$ git clone --depth 1 https://github.com/brycewang-stanford/Auto-Empirical-Research-Skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/61-phdemotions-research-methods/skills/data-profile .claude/skills/data-profile && rm -rf skills-src

Use ~/.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/

Paste into Claude Code

Install the "data-profile" agent skill from https://github.com/brycewang-stanford/Auto-Empirical-Research-Skills/tree/main/skills/61-phdemotions-research-methods/skills/data-profile into .claude/skills/data-profile/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "data-profile", 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

$skill-installer install https://github.com/brycewang-stanford/Auto-Empirical-Research-Skills/tree/main/skills/61-phdemotions-research-methods/skills/data-profile

Type 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.

skills CLI

$ npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill data-profile -a codex

Project install goes to .agents/skills/; add -g for ~/.codex/skills/.

GitHub CLI

$ gh skill install brycewang-stanford/Auto-Empirical-Research-Skills data-profile --agent codex

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/brycewang-stanford/Auto-Empirical-Research-Skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/61-phdemotions-research-methods/skills/data-profile .agents/skills/data-profile && rm -rf skills-src

Use ~/.agents/skills/ instead of .agents/skills for a personal install.

Codex skills documentation · loads skills from .agents/skills/

Paste into Codex

Install the "data-profile" agent skill from https://github.com/brycewang-stanford/Auto-Empirical-Research-Skills/tree/main/skills/61-phdemotions-research-methods/skills/data-profile into .agents/skills/data-profile/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "data-profile", 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.

skills CLI

$ npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill data-profile -a cursor

Project install goes to .agents/skills/; add -g for ~/.cursor/skills/.

GitHub CLI

$ gh skill install brycewang-stanford/Auto-Empirical-Research-Skills data-profile --agent cursor

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/brycewang-stanford/Auto-Empirical-Research-Skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/61-phdemotions-research-methods/skills/data-profile .cursor/skills/data-profile && rm -rf skills-src

Use ~/.cursor/skills/ instead of .cursor/skills for a personal install.

Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/

Paste into Cursor

Install the "data-profile" agent skill from https://github.com/brycewang-stanford/Auto-Empirical-Research-Skills/tree/main/skills/61-phdemotions-research-methods/skills/data-profile into .cursor/skills/data-profile/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "data-profile", 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

$ gemini skills install https://github.com/brycewang-stanford/Auto-Empirical-Research-Skills.git --path skills/61-phdemotions-research-methods/skills/data-profile

--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.

skills CLI

$ npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill data-profile -a gemini-cli

Project install goes to .agents/skills/; add -g for ~/.gemini/skills/.

GitHub CLI

$ gh skill install brycewang-stanford/Auto-Empirical-Research-Skills data-profile --agent gemini-cli

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/brycewang-stanford/Auto-Empirical-Research-Skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/61-phdemotions-research-methods/skills/data-profile .gemini/skills/data-profile && rm -rf skills-src

Use ~/.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/

Paste into Gemini CLI

Install the "data-profile" agent skill from https://github.com/brycewang-stanford/Auto-Empirical-Research-Skills/tree/main/skills/61-phdemotions-research-methods/skills/data-profile into .gemini/skills/data-profile/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "data-profile", 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.

GitHub CLI

$ gh skill install brycewang-stanford/Auto-Empirical-Research-Skills data-profile

Installs 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).

skills CLI

$ npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill data-profile -a github-copilot

Project install goes to .agents/skills/; add -g for ~/.copilot/skills/.

Manual copy

$ git clone --depth 1 https://github.com/brycewang-stanford/Auto-Empirical-Research-Skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/61-phdemotions-research-methods/skills/data-profile .github/skills/data-profile && rm -rf skills-src

Use ~/.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/

Paste into GitHub Copilot

Install the "data-profile" agent skill from https://github.com/brycewang-stanford/Auto-Empirical-Research-Skills/tree/main/skills/61-phdemotions-research-methods/skills/data-profile into .github/skills/data-profile/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "data-profile", 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.

skills CLI

$ npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill data-profile -a opencode

OpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.

GitHub CLI

$ gh skill install brycewang-stanford/Auto-Empirical-Research-Skills data-profile --agent opencode

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/brycewang-stanford/Auto-Empirical-Research-Skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/61-phdemotions-research-methods/skills/data-profile .opencode/skills/data-profile && rm -rf skills-src

Use ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.

OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/

Paste into OpenCode

Install the "data-profile" agent skill from https://github.com/brycewang-stanford/Auto-Empirical-Research-Skills/tree/main/skills/61-phdemotions-research-methods/skills/data-profile into .opencode/skills/data-profile/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "data-profile", 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: data-profile
GitHub stars: 4.5k
Token cost: ~2.2k tokens
SKILL.md length: 967 words
Files: 3 (incl. references)
Skills in repo: 364
Repo updated: Oct 5, 2026
First seen: Oct 7, 2026
Licence: Custom licence

At a glance

Generate a complete, manuscript-ready data profile: demographics summary table, scale identification with reliability (alpha, omega, CFA), comprehensive codebook, sample characteristics, and…

Works in 11 steps: Check current best practices → Locate and read the data → Load principles and rubric → …
The user says describe my data for the manuscript
SKILL.md covers How to run a data profile, Voice and Argument handling
Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Data Profile is an agent skill from brycewang-stanford/Auto-Empirical-Research-Skills. Generate a complete, manuscript-ready data profile: demographics summary table, scale identification with reliability (alpha, omega, CFA), comprehensive codebook, sample characteristics, and measurement documentation — all following current best practices at the time of execution. Searches for the latest reporting standards (JARS, TOP, APA) before generating output. Produces everything a Methods section needs to describe the data. Use when the user says "describe my data for the manuscript," "demographics table,"…

Its SKILL.md is about 2.2k tokens, which your agent loads only when the skill is triggered. The skill folder holds 3 other files, including reference files (for example `references/criteria.md` and `references/principles.md`).

The repository describes itself as: 🔬 A curated collection of 23,000+ agent skills for empirical research across 8 social science disciplines. | 精选 23,000+ AI Agent 技能库，覆盖8大社会科学学科的实证研究。CoPaper.AI…

When your agent uses it

The user says describe my data for the manuscript
Demographics table
What scales are in here
Methods section data

Example prompts

“describe my data for the manuscript,”
“demographics table,”
“what scales are in here,”
“/data-profile”

Workflow steps

11 steps, taken from the step headings in SKILL.md.

Check current best practices
Locate and read the data
Load principles and rubric
Identify all constructs and scales
Compute reliability for every multi-item scale
Generate demographics summary table
Generate comprehensive codebook
Generate scale documentation table
Generate sample flow (if applicable)
Compile the data profile report
Summary and next steps

What it can do on your machine

Read from SKILL.md and the folder at commit 9fa87d8. 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

Data Profile loads about 2.2k tokens when it runs, and up to ~4.2k if it reads all its reference files. Until then it costs about 194 tokens; SKILL.md has 967 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it: ~194
When it runs · the whole SKILL.md, loaded when a task matches: ~2.2k
With references · SKILL.md plus every file in references/, read only if the agent opens them: ~4.2k

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

Its licence (Custom licence) doesn't allow us to republish the file, so here is its outline and opening line. It has 967 words (~2,191 tokens).

“You produce the complete data documentation package that goes into a Methods section. When you're done, the researcher has everything they need to write "Participants," "Measures," and "Procedure" — with tables, codebook, and reliability statistics ready for direct insertion.”

— opening of SKILL.md by brycewang-stanford, Custom licence

name: data-profile
argument-hint: <path to data file or data/processed/ — defaults to data/processed/>

Outline of SKILL.md

/data-profile — Manuscript-Ready Data Profile
How to run a data profile
Step 1 — Check current best practices
Step 2 — Locate and read the data
Step 3 — Load principles and rubric
Step 4 — Identify all constructs and scales
Step 5 — Compute reliability for every multi-item scale
Step 6 — Generate demographics summary table
Step 7 — Generate comprehensive codebook
Step 8 — Generate scale documentation table
Step 9 — Generate sample flow (if applicable)
Step 10 — Compile the data profile report
Step 11 — Summary and next steps
Voice
Argument handling

Read the full SKILL.md on GitHub

Files

SKILL.md and 2 other files (references) in skills/61-phdemotions-research-methods/skills/data-profile of brycewang-stanford/Auto-Empirical-Research-Skills.

SKILL.md
references/criteria.md
references/principles.md

Open the folder on GitHubat commit 9fa87d8

Compare with similar skills

Data Profile 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.

Data Profile compared with similar skills
Skill	Stars	Used in	Tokens	Auto-check	Licence	Repo updated
Data Profile this skillbrycewang-stanford/Auto-Empirical-Research-Skills	4.5k	—	~2.2k	Automated safety check: Pass	Custom licence	3 days ago
Profileccusage/ccusage	19k	—	~430	Automated safety check: Pass	Custom licence	today
Cpu ProfileClickHouse/ClickHouse	50k	—	~1.9k	Automated safety check: Notes	Apache-2.0	today
Codex Profilessickn33/agentic-awesome-skills	47k	1 repos	~1.7k	Automated safety check: Pass	MIT	today
Collectors Snmp Profilesnetdata/netdata	81k	—	~3.1k	Automated safety check: Pass	GPL-3.0	today
Alloc ProfileClickHouse/ClickHouse	50k	—	~4.3k	Automated safety check: Pass	Apache-2.0	today

Similar skills

Profile
ccusage/ccusage
Profiles ccusage performance. An agent skill from ccusage/ccusage.
19k GitHub stars~430 tokensUpdated today
Auto-check passed
Cpu Profile
ClickHouse/ClickHouse
Profile a ClickHouse query using the sampling query profiler and system.tracelog.
50k GitHub stars~1.9k tokensUpdated today
DatabasesAuto-check: notes
Codex Profiles
sickn33/agentic-awesome-skills
Use codex-profiles to run Codex CLI or Codex Desktop with isolated CODEXHOME profiles for separate accounts, projects, and local state.
47k GitHub starsUsed in 1 repo~1.7k tokens
Auto-check passed
Collectors Snmp Profiles
netdata/netdata
Author or review Netdata SNMP polling profiles, ddsnmp parsing, topology/licensing/BGP rows and profile-format documentation.
81k GitHub stars~3.1k tokensUpdated today
Frontend & DesignAuto-check passed
Alloc Profile
ClickHouse/ClickHouse
Analyze a jemalloc (or other) allocation profile in collapsed stack format.
50k GitHub stars~4.3k tokensUpdated today
DatabasesAuto-check passed
Competitor Profiling
sickn33/agentic-awesome-skills
When the user wants to research, profile, or analyze competitors from their URLs.
47k GitHub starsUsed in 1 repo~3.6k tokens
Marketing & SEOAuto-check passed

More from brycewang-stanford/Auto-Empirical-Research-Skills

All 364 skills in this repo

Latex Paper En
brycewang-stanford/Auto-Empirical-Research-Skills
English LaTeX academic paper assistant for existing .tex projects.
4.5k GitHub starsUsed in 1 repo~2.2k tokens
Auto-check passed
Bayesian Workflow
brycewang-stanford/Auto-Empirical-Research-Skills
Opinionated Bayesian modeling workflow with PyMC and ArviZ. An agent skill from brycewang-stanford/Auto-Empirical-Research-Skills.
4.5k GitHub stars~3.5k tokensUpdated 3 days ago
Auto-check passed
Five Questions
brycewang-stanford/Auto-Empirical-Research-Skills
Deeply analyze any empirical economics PDF using the five-question framework (五问框架): research question, identification strategy, core estimand, robustness logic, and scholarly contribution.
4.5k GitHub stars~1.7k tokensUpdated 3 days ago
Auto-check: notes
Kaggle Research
brycewang-stanford/Auto-Empirical-Research-Skills
A skill your agent uses when a research task needs reproducible Kaggle discovery, metadata inspection, bounded public-data downloads, competition or kernel discovery, model discovery, or an…
4.5k GitHub stars~868 tokensUpdated 3 days ago
Auto-check passed
Latex Thesis Zh
brycewang-stanford/Auto-Empirical-Research-Skills
Chinese LaTeX thesis assistant for existing .tex degree thesis projects (XeLaTeX/LuaLaTeX/latexmk).
4.5k GitHub stars~1.5k tokensUpdated 3 days ago
Auto-check passed
Obsidian Project Memory
brycewang-stanford/Auto-Empirical-Research-Skills
This skill should be used when the user asks to maintain an Obsidian knowledge base for a research project, import an existing research repository into Obsidian, keep project memory or daily notes…
4.5k GitHub stars~2.4k tokensUpdated 3 days ago
Auto-check passed

Questions about Data Profile

What does Data Profile do?

Generate a complete, manuscript-ready data profile: demographics summary table, scale identification with reliability (alpha, omega, CFA), comprehensive codebook, sample characteristics, and…. Data Profile is an agent skill from brycewang-stanford/Auto-Empirical-Research-Skills. Generate a complete, manuscript-ready data profile: demographics summary table, scale identification with reliability (alpha, omega, CFA), comprehensive codebook, sample characteristics, and measurement documentation — all following current best practices at the time of execution.

When should I use Data Profile?

Data Profile fits situations like: the user says describe my data for the manuscript; demographics table; what scales are in here; methods section data.

How do I install Data Profile in Claude Code?

Run `npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill data-profile -a claude-code`. Or copy the skill folder (skills/61-phdemotions-research-methods/skills/data-profile in brycewang-stanford/Auto-Empirical-Research-Skills) into .claude/skills/data-profile in your project. Claude Code loads it when a task matches its description.

How do I install Data Profile in Codex?

Run `npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill data-profile -a codex`. Or copy the skill folder (skills/61-phdemotions-research-methods/skills/data-profile in brycewang-stanford/Auto-Empirical-Research-Skills) into .agents/skills/data-profile in your project. Codex loads it when a task matches its description.

Can I use Data Profile 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/Auto-Empirical-Research-Skills --skill data-profile -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/data-profile, .gemini/skills/data-profile, .github/skills/data-profile and .opencode/skills/data-profile in your project.

What does Data Profile need to run?

SKILL.md names no scripts, command-line tools or credentials: Data Profile is instructions for the agent only.

Does Data Profile 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 Data Profile 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 Data Profile use?

Data Profile has a licence file (the repository's licence) that doesn't match a standard licence. Read it on GitHub before reusing the skill.

How many tokens does Data Profile use?

About 2.2k tokens (SKILL.md is roughly 8.8k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 2k tokens, read only when the agent opens those files.

What are the alternatives to Data Profile?

Skills that share tags, products or a category with Data Profile: Profile (ccusage/ccusage, 19k stars), Cpu Profile (ClickHouse/ClickHouse, 50k stars), Codex Profiles (sickn33/agentic-awesome-skills, 47k stars) and Collectors Snmp Profiles (netdata/netdata, 81k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Data Profile?

brycewang-stanford (a GitHub user) maintains it in brycewang-stanford/Auto-Empirical-Research-Skills, which has 4,529 GitHub stars. The repository holds 364 skills in this directory. The repository was last updated on October 5, 2026.

Source: brycewang-stanford/Auto-Empirical-Research-Skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.

Install Data Profile

Facts

At a glance

What it does

When your agent uses it

Example prompts

Workflow steps

What it can do on your machine

Tool permissions

Runs code

Network

Credentials

Context cost

Safety

SKILL.md

Files

Compare with similar skills

Similar skills

More from brycewang-stanford/Auto-Empirical-Research-Skills

Questions about Data Profile