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 deidentifying-clinical-text and configuring-privacy-policies.

Quality

85%

Does it follow best practices?

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Securityby

Passed

No findings from the security scan

Quality

Content

82%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

A well-crafted, actionable skill body with executable examples, a clear validated workflow, and strong sectioning. The main improvement room is making the final verification step inline rather than deferred to a sibling skill, and potentially offloading the standards/API reference detail into a bundled file.

Suggestions

Inline a concrete verification snippet in the Workflow's Verify step (e.g. a collision check command or auditing call) rather than only referencing the auditing-deidentification-runs skill, to close the validation checkpoint.

Consider moving the 'Standards & references' list and the full custom-provider API detail into a bundled references file, keeping SKILL.md a tighter overview with one-level-deep pointers.

Tighten the explanatory paragraph after the Quick start code block — the consistent=True/seed rationale is partly restated in the table and Workflow, so a single concise mention would reduce redundancy.

Dimension	Reasoning	Score
Conciseness	Lean, well-sectioned body that assumes Claude's competence — no padding about what PHI or Faker is — with only minor explanatory passages (e.g. the consistent=True paragraph) that could be trimmed slightly; sits above the 'mostly efficient' anchor but not perfectly lean.	4 / 5
Actionability	Fully executable, copy-paste-ready Quick start with expected output, plus a complete custom-providers block showing real signatures (register_label_generator, AnonymizerConfig.custom_providers) and a direct surrogate() call covering the common cases.	5 / 5
Workflow Clarity	A clear six-step Workflow sequence with an explicit Verify checkpoint (step 6) for a batch/de-identification operation, satisfying the destructive/batch validation requirement; the verify step points outward to auditing-deidentification-runs rather than giving an inline command, a minor gap keeping it below 5.	4 / 5
Progressive Disclosure	Well-organized into clear sections (When to use, Quick start, comparison table, Custom providers, Workflow, Hand-off, Edge cases, Standards) with clearly signaled sibling-skill references and external links; no bundle files exist, and a little of the inline standards/API detail could be split out, so it is just below the ideal one-level-deep structure.	4 / 5
	Total	17 / 20 Passed

Description

88%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

A strong, specific description that clearly states what the skill does and when to use it, with concrete API references and explicit trigger phrases. It is well-differentiated from sibling de-identification skills, with only minor room for broader natural-language trigger coverage.

Dimension	Reasoning	Score
Specificity	Lists multiple concrete actions — 'Replace detected PHI with realistic, type-matched fake values', 'register a custom surrogate generator or provider' — and enumerates specific API surfaces (deidentify, register_label_generator, register_clinical_provider, Anonymizer/AnonymizerConfig), giving comprehensive coverage.	5 / 5
Completeness	Explicitly answers both 'what' ('Replace detected PHI with realistic, type-matched fake values in OpenMed so clinical notes stay readable and parseable') and 'when' via a concrete 'Use when the user wants...' clause with multiple trigger phrases.	5 / 5
Trigger Term Quality	Strong natural keywords ('surrogate names, MRNs, addresses, or dates', 'consistent fake identities', 'downstream NLP', 'custom surrogate generator') with good synonym coverage; a few lay terms a non-expert might say are absent, so it sits just below the comprehensive anchor.	4 / 5
Distinctiveness Conflict Risk	Clear niche (OpenMed surrogate replacement) differentiated from masking ('rather than opaque masks') and explicitly paired with sibling skills deidentifying-clinical-text and configuring-privacy-policies; minor overlap risk with those closely related de-id skills keeps it just below 5.	4 / 5
	Total	18 / 20 Passed

Validation

100%

Warnings & errors only

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository: maziyarpanahi/openmed
Path: skills/generating-synthetic-surrogates/SKILL.md
Commit: 80da98c

Reviewed: about 23 hours ago

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