generating-synthetic-surrogates
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 deiden
Profile →npx skills add maziyarpanahi/openmed --skill generating-synthetic-surrogates --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Generating synthetic surrogates `method="replace"` swaps each detected identifier for a **realistic, type-matched fake** — `John Doe` becomes `Mark Lee`, a phone becomes a plausible phone, a date becomes a plausible date. Unlike opaque `[REDACTED]`/`[NAME]` masks, surrogate text reads naturally and stays parseable by downstream NLP, while still containing no real PHI. OpenMed generates surrogates on-device via Faker-backed providers keyed to each canonical label. ## When to use this skill Use surrogates when the de-identified text must remain **readable or machine- parseable**: training data for clinical NLP, demos, QA, or notes a human still needs to skim. If you only need the identifiers gone and don't care about readability, plain `method="mask"` is simpler and more obviously redacted. ## Quick start ```python import openmed note = ( "Patient John Doe (MRN 1234567) saw Dr. John Doe's colleague on 2024-03-02. " "Reach John Doe at 617-555-0142." ) result = openmed.deidentify( note, method="replace", consistent=True, # every "John Doe" -> the SAME surrogate within this call seed=42, # reproducible across runs locale="en_US", # shapes the fakes; defaults from lang via LANG_TO_LOCA
- When to use this skill
- Quick start
- Surrogates vs opaque redaction
- Custom providers and label generators
- Workflow
- Hand-off to / from OpenMed
- Edge cases & gotchas
- Standards & references
What does the generating-synthetic-surrogates skill do?
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 deiden
How do I install it?
Run `npx skills add maziyarpanahi/openmed --skill generating-synthetic-surrogates --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From maziyarpanahi/openmed, a repository with 4,851 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.