Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add personamanagmentlayer/pcl --skill healthcare-expertgit clone --depth 1 https://github.com/personamanagmentlayer/pclWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/personamanagmentlayer/pcl/healthcare-expert)<a href="https://agentmods.dev/skills/personamanagmentlayer/pcl/healthcare-expert"><img src="https://agentmods.dev/badge/skills/personamanagmentlayer/pcl/healthcare-expert/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/personamanagmentlayer/pcl/healthcare-expert"><img src="https://agentmods.dev/badge/skills/personamanagmentlayer/pcl/healthcare-expert.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk pass
- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00064 | $0.02420 |
| Opus 5 | $0.00032 | $0.01210 |
| Sonnet 5 | $0.00013 | $0.00484 |
| Haiku 4.5 | $0.00006 | $0.00242 |
Grade A, and why
healthcare-expert scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 7d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 373 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Healthcare Expert
Expert guidance for healthcare systems, medical informatics, regulatory compliance (HIPAA), and health data standards (HL7, FHIR).
Core Concepts
Healthcare IT
- Electronic Health Records (EHR)
- Health Information Exchange (HIE)
- Clinical Decision Support Systems
- Telemedicine platforms
- Medical imaging systems (PACS)
- Laboratory information systems
Standards and Protocols
- HL7 (Health Level 7)
- FHIR (Fast Healthcare Interoperability Resources)
- DICOM (Digital Imaging and Communications in Medicine)
- ICD-10 (diagnostic codes)
- CPT (procedure codes)
- SNOMED CT (clinical terminology)
Regulatory Compliance
- HIPAA (Health Insurance Portability and Accountability Act)
- HITECH Act
- GDPR for health data
- FDA regulations for medical devices
- 21 CFR Part 11 for electronic records
FHIR Resource Handling
from fhirclient import client
from fhirclient.models import patient, observation, medication
from datetime import datetime
# FHIR Client setup
settings = {
'app_id': 'my_healthcare_app',
'api_base': 'https://fhir.example.com/r4'
}
smart = client.FHIRClient(settings=settings)
# Patient resource
def create_patient(first_name, last_name, gender, birth_date):
"""Create FHIR Patient resource"""
p = patient.Patient()
p.name = [{
'use': 'official',
'family': last_name,
'given': [first_name]
}]
p.gender = gender # 'male', 'female', 'other', 'unknown'
p.birthDate = birth_date.isoformat()
return p.create(smart.server)
# Observation resource (vital signs)
def create_vital_signs_observation(patient_id, code, value, unit):
"""Create vital signs observation"""
obs = observation.Observation()
obs.status = 'final'
obs.category = [{
'coding': [{
'system': 'http://terminology.hl7.org/CodeSystem/observation-category',
'code': 'vital-signs',
'display': 'Vital Signs'
}]
}]
obs.code = {
'coding': [{
'system': 'http://loinc.org',
'code': code, # e.g., '8867-4' for heart rate
'display': 'Heart rate'
}]
}
obs.subject = {'reference': f'Patient/{patient_id}'}
obs.effectiveDateTime = datetime.now().isoformat()
obs.valueQuantity = {
'value': value,
'unit': unit,
'system': 'http://unitsofmeasure.org',
'code': unit
}
return obs.create(smart.server)
# Search patients
def search_patients(family_name=None, given_name=None):
"""Search for patients by name"""
search = patient.Patient.where(struct={})
if family_name:
search = search.where(struct={'family': family_name})
if given_name:
search = search.where(struct={'given': given_name})
return search.perform(smart.server)
# Get patient observations
def get_patient_observations(patient_id, category=None):
"""Retrieve patient observations"""
search = observation.Observation.where(struct={
'patient': patient_id
})
if category:
search = search.where(struct={'category': category})
return search.perform(smart.server)
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 7d ago First seen · 373 lines · 64 tokens per session scan A 8720f96d6e9b
healthcare-expert is a skill published in the GitHub repository personamanagmentlayer/pcl (40 stars, last pushed 2d ago), licensed Apache-2.0. It adds 64 tokens to every session and 2,420 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-05.
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