generating-synthetic-surrogates
generating-synthetic-surrogates is a Health informatics & FHIR skill for AI agents, published by maziyarpanahi in the openmed repository on GitHub. Skillspace rates generating-synthetic-surrogates C (74/100) and it passed the safety scan; the rating is based on static analysis only.
Replace detected PHI with realistic, type-matched fake values in OpenMed so clinical notes stay readable and parseable instead of full of [REDACTED] markers. Use when the user wants surrogate names, MRNs, addresses, or dates rather than opaque masks, needs consistent fake identities across a document, must keep notes natural for downstream NLP, or wants to register a custom surrogate generator or provider. Covers deidentify(method="replace", consistent=True, seed=..., locale=...), register_label_generator, register_clinical_provider, and Anonymizer/AnonymizerConfig. Pairs with OpenMed deidentifying-clinical-text and configuring-privacy-policies.
- Grade
- C
- Quality
- 74 / 100
- Safety
- Passed
- GitHub stars
- 4,654
Unproven: rated by static analysis only, not yet compared head-to-head.
Our two independent classifiers differ on this skill's category, so treat the placement as provisional.
This rating describes the version of the repository we crawled; it may have changed since, so go by its current files.
Our review
- Architecture
- 100 / 100
- Maturity
- Basic: a single SKILL.md
- Security scan
- No issues found
- License
- Apache-2.0
- Adoption
- Adopted by 0 other repositories, in 0 collections
- Scope
- Vendor-specific: built around one product. Generates PHI surrogates within the OpenMed toolkit.
Not checked yet
- Not judged on the rubric yet (not a contender in its category)
- No blind task eval yet
- Sibling files (scripts, references) not fetched; security scan covers SKILL.md only
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