Build and run an adversarial de-identification ⟷ re-identification evaluation harness for clinical text: generate synthetic clinical notes with ground-truth identifier spans, run a de-id pipeline (defender) over them, and score leakage against an attacker. Use this whenever the task involves evaluating a PHI scrubber or de-id pipeline, measuring re-identification risk, testing HIPAA Safe Harbor coverage or Expert Determination risk, building a privacy-utility frontier for clinical NLP, or comparing de-identification approaches — even if the user only says "test my de-identifier," "how leaky is this scrubber," or "de-id eval." Prefer this over an ad-hoc script whenever synthetic clinical data, PHI, or de-identification evaluation is mentioned.
Install with
Claude CodeCodexCursorGitHub CopilotGemini CLI
Supported by the Atlas install prompt. Skill-specific requirements vary.
Skill stats
Skills1CategorySecurityStars0
About this skill
Build and run an adversarial de-identification ⟷ re-identification evaluation harness for clinical text: generate synthetic clinical notes with ground-truth identifier spans, run a de-id pipeline (defender) over them, and score leakage against an attacker. Use this whenever the task involves evaluating a PHI scrubber or de-id pipeline, measuring re-identification risk, testing HIPAA Safe Harbor coverage or Expert Determination risk, building a privacy-utility frontier for clinical NLP, or comparing de-identification approaches — even if the user only says "test my de-identifier," "how leaky is this scrubber," or "de-id eval." Prefer this over an ad-hoc script whenever synthetic clinical data, PHI, or de-identification evaluation is mentioned.
Quick start
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Build and run an adversarial de-identification ⟷ re-identification evaluation harness for clinical text: generate synthetic clinical notes with ground-truth identifier spans, run a de-id pipeline (defender) over them, and score leakage against an attacker. Use this whenever the task involves evaluating a PHI scrubber or de-id pipeline, measuring re-identification risk, testing HIPAA Safe Harbor coverage or Expert Determination risk, building a privacy-utility frontier for clinical NLP, or comparing de-identification approaches — even if the user only says "test my de-identifier," "how leaky is this scrubber," or "de-id eval." Prefer this over an ad-hoc script whenever synthetic clinical data, PHI, or de-identification evaluation is mentioned.
About this listing
Category
Security
Reported license
MIT
Listing language (estimated)
English
Review status
Not individually reviewed
Agent compatibility
Atlas installation supports Claude Code, Codex, and Cursor. Skill-specific dependencies and features are checked during setup.