Agent D4 - Measurement Instrument Developer - Scale construction and psychometric validation.

Custom licenceAuto-check passed

Install D4

skills CLI
$ npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill d4 -a claude-code

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

GitHub CLI
$ gh skill install brycewang-stanford/Auto-Empirical-Research-Skills d4 --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/25-HosungYou-Diverga/skills/d4 .claude/skills/d4 && 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/

Facts

Skill name
d4
GitHub stars
4.5k
Token cost
~7.6k tokens
SKILL.md length
330 words
Files
1
Skills in repo
364
Repo updated
First seen
Licence
Custom licence

At a glance

Agent D4 - Measurement Instrument Developer - Scale construction and psychometric validation.

  • Works in 4 steps: Survey Item Development → Scale Construction Process → Validity Evidence Framework → …
  • SKILL.md covers ⛔ Prerequisites (v8.2 — MCP…, Core Mission, Capabilities and Response Templates, plus 4 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

D4 is an agent skill from brycewang-stanford/Auto-Empirical-Research-Skills. Agent D4 - Measurement Instrument Developer - Scale construction and psychometric validation. Covers item development, validity evidence, and reliability testing for social science research.

Its SKILL.md is about 7.6k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

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…

Example prompts

  • “/d4”

Workflow steps

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

  1. Survey Item Development
  2. Scale Construction Process
  3. Validity Evidence Framework
  4. Reliability Testing

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 (its code samples are yaml and markdown).

    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

D4 loads about 7.6k tokens when it runs. Until then it costs about 48 tokens; SKILL.md has 330 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~48
When it runs · the whole SKILL.md, loaded when a task matches
~7.6k

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 330 words (~7,567 tokens).

“diverga_check_prerequisites("d4") → must return approved: true If not approved → AskUserQuestion for each missing checkpoint (see .claude/references/checkpoint-templates.md)”

— opening of SKILL.md by brycewang-stanford, Custom licence
name
d4
version
12.0.1

Read the full SKILL.md on GitHub

Files

Just SKILL.md in skills/25-HosungYou-Diverga/skills/d4 of brycewang-stanford/Auto-Empirical-Research-Skills.

Open the folder on GitHubat commit 9fa87d8

Compare with similar skills

D4 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.

D4 compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
D4 this skillbrycewang-stanford/Auto-Empirical-Research-Skills4.5k—~7.6kAutomated safety check: PassCustom licence
MCP Developmentcoollabsio/coolify63k1 repos~949Automated safety check: PassMIT
Game Developmentsickn33/agentic-awesome-skills47k1 repos~1.3kAutomated safety check: PassMIT
Twenty App Entity Developmenttwentyhq/twenty58k—~1.8kAutomated safety check: PassCustom licence
Developmentccusage/ccusage19k—~433Automated safety check: PassCustom licence
Frontend DevelopmentOpenHands/OpenHands90k—~324Automated safety check: PassMIT

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Questions about D4

What does D4 do?

Agent D4 - Measurement Instrument Developer - Scale construction and psychometric validation. D4 is an agent skill from brycewang-stanford/Auto-Empirical-Research-Skills. Agent D4 - Measurement Instrument Developer - Scale construction and psychometric validation.

How do I install D4 in Claude Code?

Run `npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill d4 -a claude-code`. Or copy the skill folder (skills/25-HosungYou-Diverga/skills/d4 in brycewang-stanford/Auto-Empirical-Research-Skills) into .claude/skills/d4 in your project. Claude Code loads it when a task matches its description.

How do I install D4 in Codex?

Run `npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill d4 -a codex`. Or copy the skill folder (skills/25-HosungYou-Diverga/skills/d4 in brycewang-stanford/Auto-Empirical-Research-Skills) into .agents/skills/d4 in your project. Codex loads it when a task matches its description.

Can I use D4 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 d4 -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/d4, .gemini/skills/d4, .github/skills/d4 and .opencode/skills/d4 in your project.

What does D4 need to run?

SKILL.md names no scripts, command-line tools or credentials: D4 is instructions for the agent only.

Does D4 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 D4 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 D4 use?

D4 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 D4 use?

About 7.6k tokens (SKILL.md is roughly 30k 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 D4?

Skills that share tags, products or a category with D4: MCP Development (coollabsio/coolify, 63k stars), Game Development (sickn33/agentic-awesome-skills, 47k stars), Twenty App Entity Development (twentyhq/twenty, 58k stars) and Development (ccusage/ccusage, 19k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains D4?

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.