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embu-data-audit

by murzogluData & AnalyticsSource

A specialized audit tool for the EMBU data pipeline, handling Likert standardization, CFA/ICC checks, and PII removal.

Data AnalysisCode ReviewResearchSQLPython

Install

mkdir -p .claude/skills/embu-data-audit && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/15032" && unzip -o skill.zip -d .claude/skills/embu-data-audit && rm skill.zip

Installs to .claude/skills/embu-data-audit

Activation

This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.

Audit active EMBU data pipeline decisions in the doktoratezi repository. Use when working on EMBU, EMBU-C, EMBU-P, Likert 4pt/6pt, Stage 1, Stage 2, Stage 3, family matching, outliers, ICC, CFA, mixed Likert families, find_embu_columns, PII removal, or EMBU v2.0 validation.
274 chars✓ has a “when” triggerlonger than Claude Code's old 250-char listing cap (fine on current versions)
Intermediate

Key capabilities

  • →Audit EMBU data processing stages
  • →Verify Stage 1 standardization and outlier conversion
  • →Confirm Stage 2 Likert conversion for 4pt/6pt scales
  • →Validate Stage 3 family structure and index/sibling roles
  • →Check data-boundary safety and PII removal
  • →Confirm active v2.0 decision context for CFA/ICC interpretation

How it works

This skill audits EMBU data pipeline decisions by reviewing specific R scripts and documentation files within the `doktoratezi` repository. It verifies data consistency, Likert handling, outlier conversion, and family structure against the active v2.0 architecture decisions.

Inputs & outputs

You give it
An EMBU audit focus (e.g., Stage 1 outliers, Likert conversion)
You get back
An audit report detailing findings, tests run, and any residual uncertainty

When to use embu-data-audit

  • →Verify Stage 1 outliers and Likert conversion
  • →Perform ICC and CFA validation checks
  • →Audit PII removal protocols
  • →Check EMBU v2.0 decision status

About this skill

EMBU Data Audit

Use this skill for EMBU pipeline review, verification, or narrow fixes. The current project status is important: EMBU data architecture v2.0 is active. Previous inactive-status language was an obsolete artifact; CSV headers are treated as mislabeled, PDF is canonical, and the separate field-validation phase is no longer required.

Load First

Read these files before making claims or edits:

Then inspect the relevant implementation:

Audit Procedure

  1. State the audit scope: Stage 1 standardization, Stage 2 Likert conversion, Stage 3 family structure, or Stage 4 psychometrics.
  2. Confirm the active v2.0 decision context before interpreting CFA, ICC, or EMBU scale results.
  3. Check data-boundary safety: do not expose names, raw rows, credentials, or raw data contents.
  4. Verify column discovery through find_embu_columns() instead of positional assumptions.
  5. Verify Likert handling through classify_embu_c_likert() and mark_mixed_likert_families().
  6. Verify out-of-range values are converted to NA and logged to outputs/tables/embu_stage1_outliers.csv.
  7. Verify family structure uses aile_no x cocuk_no and that index/sibling roles are handled in Stage 3.
  8. Run the narrowest relevant tests, then broaden only if the changed surface requires it.

Verification Commands

Rscript tests/test_embu_stage1.R
Rscript tests/test_embu_stage2_likert4.R
Rscript tests/test_embu_stage3_family.R
Rscript scripts/R/01_embu_stage1_standardize.R
Rscript scripts/R/02_embu_stage2_likert4.R
Rscript scripts/R/03_embu_stage3_family.R

Use runner scripts only when the user asks for regeneration or when verification genuinely requires regenerated artifacts.

Response Shape

Return:

  • Scope audited.
  • Files inspected.
  • Findings ordered by severity.
  • Whether any active v2.0 decision caveats affect interpretation.
  • Tests or commands run.
  • Any residual uncertainty requiring additional documentation, code, or field-record review.

When not to use it

  • →When working on obsolete EMBU data architecture versions
  • →When CSV headers are treated as reliable labels
  • →When a separate field-validation phase is required

Limitations

  • →Requires specific EMBU documentation and R scripts to be available
  • →Verification commands are R scripts, requiring an R environment

How it compares

This skill provides a targeted audit procedure for EMBU data pipelines, specifically verifying against the active v2.0 architecture and canonical PDF documentation, unlike a general data pipeline review.

Compared to similar skills

embu-data-audit side by side with the closest alternatives in the catalog.

SkillInstallsUpdatedSafetyDifficulty
embu-data-audit (this skill)03moReviewIntermediate
mimic03moReviewAdvanced
research05moNo flagsIntermediate
senior-data-engineer218moReviewAdvanced

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