Results for “data-integrity”
8 skillsscore
Audits medical LLM benchmarks across five lifecycle phases using 46 medically tailored criteria to assess clinical relevance, data integrity, safety-critical capabilities, validity, and governance.
3
relational-database
`task-agent`: use when physical relational schema or database-enforced integrity changes; skip conceptual-model, repository-only, or unchanged relational-storage work.
4 · bundle
More results
plan-data-integrity
Audit a project for destructive-operation and migration safety gaps, then produce a phased safeguard plan. Use when "is my migration safe", "could I lose data", "my agent might delete prod", or "safe schema changes". Restore drills and RPO/RTO belong to plan-backup-dr. Source transforms → audit-codemod-safety.
8
stata-data-audit
Audit datasets for structure, missingness, labeling, suspicious values, duplicate identifiers, and documentation readiness. Use when a researcher asks for data QA, codebook review, sanity checks, or pre-analysis cleanup guidance.
1k · bundle
implementing-identity-verification-for-zero-trust
Implement continuous identity verification for zero trust using phishing-resistant MFA (FIDO2/WebAuthn), risk-based conditional access, and identity governance aligned with the CISA Zero Trust Maturity Model.
24.6k · bundle
pseudo-vs-anon-data
Classifies data as pseudonymised or anonymised using Recital 26 reasonably likely test, Breyer ruling C-582/14, motivated intruder test, and WP29 Opinion 05/2014 on anonymisation techniques. Covers singling out, linkability, and inference tests. Keywords: pseudonymisation, anonymisation, Recital 26, re-identification, k-anonymity, differential privacy, WP29 Opinion 05/2014.
228 · bundle
data-explore
Profile an unfamiliar dataset — shape, grain, quality, nulls, distributions, and duplicates — before any analysis is trusted.
0
paper-claim-audit
Verifies that every number, comparison, and scope claim in a research paper matches raw result files, using a fresh cross-model reviewer with no prior context to prevent confirmation bias.
0