Agent skill

Devpsych Data Analysis

by brycewang-stanford in brycewang-stanford/Awesome-Journal-Skills

A skill your agent uses when analyzing and reporting results for a Developmental Psychology (APA) manuscript.

MITAuto-check passedData & Analytics

Install Devpsych Data Analysis

skills CLI
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill devpsych-data-analysis -a claude-code

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

GitHub CLI
$ gh skill install brycewang-stanford/Awesome-Journal-Skills devpsych-data-analysis --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/Awesome-Journal-Skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/Developmental-Psychology-Skills/skills/devpsych-data-analysis .claude/skills/devpsych-data-analysis && 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
devpsych-data-analysis
GitHub stars
1.2k
Token cost
~1.6k tokens
SKILL.md length
553 words
Files
1
Skills in repo
2,387
Repo updated
First seen
Licence
MIT

At a glance

A skill your agent uses when analyzing and reporting results for a Developmental Psychology (APA) manuscript.

  • Works in 6 steps: Model change correctly. Use the method… → Establish measurement invariance first.… → Effect sizes + uncertainty. Report a… → …
  • Analyzing and reporting results for a Developmental Psychology (APA) manuscript
  • SKILL.md covers When to trigger, Reporting norms Developmental…, Worked micro-example… and Analysis-stage reviewer…, plus 4 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Devpsych Data Analysis is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when analyzing and reporting results for a Developmental Psychology (APA) manuscript. The journal expects analyses that model developmental change correctly — growth-curve/multilevel/SEM, mediation/moderation, measurement invariance — with effect sizes and confidence intervals, JARS-compliant disclosure, and a clear confirmatory/exploratory split. Guides analysis norms; it does not fabricate results.

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, Statistics and Dispute resolution. 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

  • Analyzing and reporting results for a Developmental Psychology (APA) manuscript
  • Tasks that involve Data analysis
  • Tasks that involve Statistics

Example prompts

  • “/devpsych-data-analysis”

Workflow steps

6 steps, taken from the first numbered list in SKILL.md.

  1. Model change correctly. Use the method the claim requires: latent growth / multilevel models
  2. Establish measurement invariance first. Test configural → metric → scalar across ages/waves
  3. Effect sizes + uncertainty. Report a standardized or unstandardized effect size **and confidence
  4. Handle missing data and attrition principledly. Use FIML or multiple imputation; report the
  5. JARS disclosure. Report how sample size was determined, all exclusions and reasons, all conditions
  6. Reproducibility. Provide analysis scripts and a data dictionary; the numbers should regenerate in

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

Devpsych Data Analysis loads about 1.6k tokens when it runs. Until then it costs about 108 tokens; SKILL.md has 553 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~108
When it runs · the whole SKILL.md, loaded when a task matches
~1.6k

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

The full file from brycewang-stanford/Awesome-Journal-Skills at commit 932eb23, republished under its MIT licence (© brycewang-stanford). 553 words, ~1,561 tokens.

Download SKILL.mdSave it as .claude/skills/devpsych-data-analysis/SKILL.md (or your agent's skills folder).
name
devpsych-data-analysis
description
Use when analyzing and reporting results for a Developmental Psychology (APA) manuscript. The journal expects analyses that model developmental change correctly — growth-curve/multilevel/SEM, mediation/moderation, measurement invariance — with effect sizes and confidence intervals, JARS-compliant disclosure, and a clear confirmatory/exploratory split. Guides analysis norms; it does not fabricate results.

Data Analysis (devpsych-data-analysis)

Developmental Psychology holds analyses to a developmental and a credibility standard at once: the model must actually capture change (not just a cross-sectional snapshot), and reporting must meet JARS — effect sizes with confidence intervals, full disclosure, and a clean confirmatory vs. exploratory split. The most common fatal error is interpreting trajectories without first establishing that the construct is measured the same way across ages.

When to trigger

  • Fitting growth-curve / multilevel / SEM models, or mediation/moderation of developmental effects
  • A reviewer asked for measurement invariance, effect sizes, intervals, or attrition handling
  • Reconciling preregistered developmental hypotheses with exploratory trajectory findings
  • Preparing analysis scripts and a data dictionary for deposit

Reporting norms Developmental Psychology expects

  1. Model change correctly. Use the method the claim requires: latent growth / multilevel models for trajectories, SEM for latent constructs, cross-lagged / RI-CLPM for reciprocal effects, mediation/moderation for mechanism and moderated change. State time coding and centering.
  2. Establish measurement invariance first. Test configural → metric → scalar across ages/waves before interpreting mean change; report partial invariance honestly if full scalar fails.
  3. Effect sizes + uncertainty. Report a standardized or unstandardized effect size and confidence intervals for major results — slope estimates, interactions, indirect effects — not just stars.
  4. Handle missing data and attrition principledly. Use FIML or multiple imputation; report the attrition analysis (completers vs. dropouts) and the missingness assumption.
  5. JARS disclosure. Report how sample size was determined, all exclusions and reasons, all conditions and measures; keep confirmatory and exploratory analyses clearly separated.
  6. Reproducibility. Provide analysis scripts and a data dictionary; the numbers should regenerate in a fresh session (see devpsych-open-science-and-transparency).

Worked micro-example (illustrative numbers)

A preregistered three-wave latent-growth study (ages 4, 6, 8; N = 300, 18% attrition) of effortful control, testing maternal scaffolding as a driver of the growth slope.

Invariance (reported first):
  configural fit good; metric and scalar invariance hold across waves
  (ΔCFI < .01) → mean change is interpretable.
Confirmatory (preregistered):
  Latent slope > 0: b = 0.42/year, 95% CI [0.31, 0.53] (within-person growth).
  Scaffolding × time: b = 0.18, 95% CI [0.07, 0.29] (steeper growth with
  higher wave-1 scaffolding).
  Missing data: FIML; MAR; completers and dropouts did not differ on baseline
  covariates (attrition analysis in supplement).
Exploratory (labeled):
  RI-CLPM suggests child→parent effects in later waves; reported as
  exploratory and flagged for confirmation in a future sample.

Why this passes scrutiny: invariance is reported before the growth claim; every developmental parameter carries an effect size and a CI; missingness is modeled, not deleted; the reciprocal-effects finding is honestly demoted to exploratory.

Show full SKILL.md (225 more words)Show less

Analysis-stage reviewer pushback and the venue fix

Reviewer pushbackWhat it signals hereDevelopmental Psychology fix
"Is the construct the same at each age?"invariance not testedreport configural→metric→scalar before interpreting change
"You deleted dropouts"attrition biasrefit with FIML/MI; add the completers-vs-dropouts analysis
"ANOVA on age groups for a change claim"wrong model for the claimfit a growth/multilevel model on within-person data
"Stars, no effect size"pre-reform reportingreport slope/interaction effect sizes with CIs
"Is this confirmatory?"HARKing concernpoint to preregistration; relabel post hoc trajectories exploratory

Calibration anchors

  • A clean latent-growth slope with a tight CI, on an invariant measure, beats an age-group ANOVA with stars — the venue's currency is credible change, not a snapshot contrast.
  • Prefer estimation language ("effortful control grew 0.42/year, 95% CI [...]") to "significant effect of age." Bare p-value sentences read as thin here.
  • When attrition is non-trivial, state the missingness assumption and show the trajectory is robust to a reasonable alternative (e.g., pattern-mixture sensitivity), rather than implying complete data.

Anti-patterns

  • Interpreting mean change without establishing measurement invariance
  • Listwise deletion or ignoring differential attrition
  • Using age-group ANOVA to support a within-person change claim
  • p-values and stars with no effect sizes or confidence intervals
  • HARKing exploratory trajectory shapes into confirmatory hypotheses

Output format

【Model】growth / multilevel / SEM / cross-lagged / mediation-moderation — matches the change claim?
【Invariance】configural→metric→scalar tested before interpreting change? [Y/N]
【Main result】effect size + confidence interval + meaning
【Missing data】FIML/MI + attrition analysis reported? [Y/N]
【Confirmatory vs exploratory】clearly separated (JARS)? [Y/N]
【Reproducible】scripts + data dictionary + fresh-session check? [Y/N]
【Next】devpsych-tables-figures

Supplementary resources

© 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 Developmental-Psychology-Skills/skills/devpsych-data-analysis of brycewang-stanford/Awesome-Journal-Skills.

Open the folder on GitHubat commit 932eb23

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Questions about Devpsych Data Analysis

What does Devpsych Data Analysis do?

A skill your agent uses when analyzing and reporting results for a Developmental Psychology (APA) manuscript. Devpsych Data Analysis is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when analyzing and reporting results for a Developmental Psychology (APA) manuscript.

When should I use Devpsych Data Analysis?

Devpsych Data Analysis fits situations like: analyzing and reporting results for a Developmental Psychology (APA) manuscript; tasks that involve Data analysis; tasks that involve Statistics.

How do I install Devpsych Data Analysis in Claude Code?

Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill devpsych-data-analysis -a claude-code`. Or copy the skill folder (Developmental-Psychology-Skills/skills/devpsych-data-analysis in brycewang-stanford/Awesome-Journal-Skills) into .claude/skills/devpsych-data-analysis in your project. Claude Code loads it when a task matches its description.

How do I install Devpsych Data Analysis in Codex?

Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill devpsych-data-analysis -a codex`. Or copy the skill folder (Developmental-Psychology-Skills/skills/devpsych-data-analysis in brycewang-stanford/Awesome-Journal-Skills) into .agents/skills/devpsych-data-analysis in your project. Codex loads it when a task matches its description.

Can I use Devpsych 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 devpsych-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/devpsych-data-analysis, .gemini/skills/devpsych-data-analysis, .github/skills/devpsych-data-analysis and .opencode/skills/devpsych-data-analysis in your project.

What does Devpsych Data Analysis need to run?

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

Does Devpsych 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 Devpsych 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 Devpsych Data Analysis use?

Devpsych 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 Devpsych Data Analysis use?

About 1.6k tokens (SKILL.md is roughly 6.2k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

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Who maintains Devpsych 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.