Scar photo standardization
Skill KangjieShen/openscar-starter/skills/imaging/scar-photo-standardization
AI-native scar and keloid phenotyping framework with registry schema, synthetic mock data, validation scripts, and clinician-reviewable workflow skills
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Define repeatable scar and keloid photography workflows with quality flags aligned to the OpenScar image schema.
The file declares its own license as MIT. That is the author’s claim about this one file, and it is not the same thing as the license GitHub reports for the repository, which is listed with the other numbers below.
SKILL.md
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Scar Photo Standardization
Description
Use this skill to create a standardized scar or keloid photo capture protocol for clinical documentation, research registry preparation, and longitudinal before/after comparison. The skill focuses on repeatability, consent, privacy, and image quality. It does not diagnose scars, determine recurrence, or judge treatment success.
When to Use
- A clinic needs a scar or keloid photo SOP.
- A researcher is preparing cases for the OpenScar schema.
- A team wants consistent baseline and follow-up images before outcome review.
- A user needs image quality flags for
image.csv.
Do Not Use
- Do not diagnose scar type from photos.
- Do not determine recurrence or treatment response from photos alone.
- Do not alter photos to exaggerate outcomes.
- Do not store or share identifiable images without appropriate consent and access control.
- Do not use public image paths for real patient media.
Required Inputs
- Anatomic site and lesion identifier, if available.
- Visit type:
baseline,treatment,follow_up,complication,recurrence_check, orother. - Intended use: clinical record, research-deidentified dataset, teaching, or public media.
- Available camera setup, room setup, and privacy constraints.
- Whether scale marker and color reference are available.
Workflow
- Confirm consent and intended use before capture.
- Assign or confirm
patient_id,lesion_id, and plannedvisit_idif the case is entering a registry. - Define the image set:
overview: anatomic orientation and surrounding landmarks.close_up: lesion detail with scale marker when feasible.oblique: contour, height, and edge visibility.profile: raised lesions or contracture-relevant views.with_scale: measurement-oriented image when not already covered.
- Standardize capture conditions:
- same room or lighting setup when possible
- plain background
- camera perpendicular for close-up views
- consistent distance, ideally recorded in
distance_cm - no cosmetic editing, smoothing, filters, or exposure manipulation
- Prepare the patient and field:
- expose the full lesion and surrounding normal skin
- remove jewelry, clothing edges, adhesive residue, or makeup when clinically appropriate
- avoid unnecessary identifiable anatomy
- cover or crop unrelated identifiable features when possible
- Capture image quality metadata aligned to OpenScar:
view_labelcapture_devicedistance_cmscale_marker_presentcolor_reference_presentlighting_qualityangle_qualityfocus_qualityprivacy_redaction_status
- Flag limitations and repeat any photo only if doing so is clinically practical and respectful.
- Produce a registry-ready image record draft and a human-readable capture checklist.
Quality Flag Rules
Use these labels so outputs can map directly into open-scar-starter/docs/data-schema.md.
lighting_quality
good: lesion color and border are visible without glare or heavy shadow.acceptable: minor shadow, glare, or exposure variation, but lesion remains interpretable.poor: color, border, or surface detail is substantially obscured.unknown: image is unavailable or cannot be reviewed.
angle_quality
standardized: view matches the planned protocol and is comparable to prior/future visits.acceptable: view is usable but has mild rotation, tilt, or distance variation.nonstandard: view limits comparison because angle, distance, or framing differs substantially.unknown: angle cannot be assessed.
focus_quality
good: lesion edge and surface detail are sharp.acceptable: slight blur but main features remain visible.poor: blur prevents meaningful comparison.unknown: focus cannot be assessed.
privacy_redaction_status
not_needed: no unnecessary identifying features are visible.redacted: identifying features were covered, cropped, masked, or otherwise protected.needs_review: image may contain identifiable features or consent/media-use uncertainty.
Output Format
Return:
- Purpose and consent check
- Required view list
- Room and camera setup
- Patient and field preparation checklist
- OpenScar
image.csvfield draft - Quality flags and limitations
- Repeat-capture recommendations
- Privacy and storage notes
Example Output Skeleton
Purpose and consent:
- Intended use: research_deidentified registry
- Consent status to confirm before export: research_deidentified
View list:
- overview
- close_up with scale marker
- oblique
Image field draft:
- image_id: img_pending_001
- visit_id: v_pending_001
- lesion_id: l_pending_001
- image_uri: secure_storage_pointer_required
- view_label: close_up
- capture_device: clinic_camera_or_phone_model
- distance_cm: 30
- scale_marker_present: true
- color_reference_present: false
- lighting_quality: acceptable
- angle_quality: standardized
- focus_quality: good
- privacy_redaction_status: needs_review
Limitations:
- No color reference available.
- Confirm image storage and consent before research export.
Safety and Compliance
This skill supports documentation, research preparation, and clinician review. It does not diagnose, prescribe, determine recurrence, or replace licensed clinical judgment. Escalate urgent symptoms, suspected infection, wound breakdown, severe pain, rapid progression, bleeding, ulceration, or functional compromise to a qualified clinician.
Protect all patient media under applicable privacy rules. Use secure storage pointers for real images. Do not place real patient photos in public repositories.
Examples
Create a standardized photo checklist for an anterior chest keloid baseline visit, with fields ready for OpenScar image.csv.
Review this proposed scar photography SOP and map its quality-control items to OpenScar image schema fields.
Integration
Works well with:
keloid-follow-up-intakescar-treatment-response-reviewscar-registry-entry-builderbefore-after-analysisconsent-form-review
Gives 0 of the 12 instructions most images graphics skills give
Counted across 371 of the 372 authors here whose files we hold, read 2026-08-06
- create a complete brand world in one imagein 19 of 371, across 5 files
- infer the brand strategy before generatingin 19 of 371, across 5 files
- use a clean presentation gridin 19 of 371, across 5 files
- confirm connection status is activein 19 of 371, across 4 files
- base the visual system on meaningin 17 of 371, across 3 files
- use very little textin 17 of 371, across 3 files
- make every panel feel connectedin 17 of 371, across 3 files
- call RUBE_SEARCH_TOOLS firstin 17 of 371, across 3 files
- convert dash-format node IDs to colon formatin 17 of 371, across 5 files
- match reference quality and rhythm if providedin 16 of 371, across 2 files
- narrow scope or reduce depth to avoid oversized payloadsin 16 of 371, across 4 files
- generate a simple and memorable logoin 15 of 371, across 1 file
Said here and by no other author read
- confirm consent and intended use before capture
- assign patient and lesion identifiers for registry cases
- define required image view labels
- standardize room lighting and background setup
- remove clothing and jewelry from the field
- avoid unnecessary identifiable anatomy
Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once.