---

name: presidio description: "Use Presidio for PII and PHI detection, anonymization, structured de-identification, image/DICOM redaction, and CLI scans." disable-model-invocation: true metadata: disco-role: operating license: MIT

presidio

Use this repo skill when a task needs Microsoft/Data Privacy Stack Presidio package guidance for detecting, anonymizing, pseudonymizing, redacting, or scanning personally identifiable information (PII) or protected health information (PHI).

Start with the task shape

User need	Read
Detect PII/PHI in text, configure recognizers, choose NLP engines, handle supported entities/languages, thresholds, context, or allow lists	sub-skills/analyze-text/SKILL.md
Replace, redact, hash, mask, encrypt/decrypt, custom-transform, batch anonymize, or reason about overlapping text spans	sub-skills/anonymize-text/SKILL.md
De-identify Pandas DataFrames, CSV-like columns, dictionaries, or JSON-like payloads	sub-skills/structured-data/SKILL.md
Redact standard images or DICOM burnt-in pixel text using OCR and bounding boxes	sub-skills/image-redaction/SKILL.md
Scan files, directories, or stdin from a terminal/CI job with the presidio CLI	sub-skills/cli-scans/SKILL.md
Install packages, pick extras, verify imports/model/OCR prerequisites	references/install-and-models.md and scripts/check_presidio_install.py
Run or call analyzer/anonymizer/image REST services	references/service-and-rest-api.md
Diagnose cross-cutting import/model/Tesseract/optional-extra/service issues	references/troubleshooting.md
Check whether this skill matches the current repository version	references/repo-provenance.md

Minimal Python package setup

# Text analysis plus anonymization
python -m pip install presidio-analyzer presidio-anonymizer
python -m spacy download en_core_web_lg

# Or install the convenience package for analyzer + anonymizer
python -m pip install presidio
python -m spacy download en_core_web_lg

Additional task-specific packages:

python -m pip install presidio-structured       # DataFrame / JSON workflows
python -m pip install presidio-image-redactor   # image and DICOM pixel redaction
python -m pip install presidio-cli              # terminal file scans

For image workflows, also install the Tesseract OCR system binary unless you inject another OCR engine. For optional integrations such as Transformers, Stanza, GLiNER, LangExtract, Azure AI Language, AHDS, or service mode, install only the extra needed for the selected workflow.

Minimal verification

After installing, run the bundled checker from this skill directory:

python scripts/check_presidio_install.py --help
python scripts/check_presidio_install.py
python scripts/check_presidio_install.py --smoke

If the task intentionally uses only no-download pattern recognizers, the default spaCy model can be skipped:

python scripts/check_presidio_install.py --skip-model-check --skip-tesseract-check

Sub-skills also provide focused smoke scripts for their workflows.

Common route combinations

• Analyze then anonymize text: use analyze-text to produce RecognizerResult spans, then anonymize-text to choose OperatorConfig mappings.
• Structured de-identification: use structured-data; route back to analyze-text only when builder entity detection or custom analyzer setup needs adjustment.
• Image redaction: use image-redaction; route to analyze-text for custom recognizers or analyzer kwargs and to root troubleshooting for Tesseract/model issues.
• CI PII scan: use cli-scans; route to analyze-text when the config needs a custom entity or model behavior beyond CLI YAML.
• REST services: use service-and-rest-api for endpoints, but use package sub-skills when custom Python objects or lambdas are required.

Hard boundaries and cautions

• Presidio is automated detection. It can miss sensitive data; use sampling, human review, custom recognizers, and domain-specific validation for high-risk workflows.
• DICOM image redaction only edits pixel data. It does not scrub metadata PHI.
• Keep analyzer span offsets aligned with the exact text passed to anonymizer.
• Do not install all extras by default; cloud/LLM/model/GPU integrations add credentials, downloads, services, or backend constraints.
• This generated skill is self-contained. Do not rely on the original repository checkout for runtime instructions.