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 aizech/clinical-skills --skill pacs-workflowgit clone --depth 1 https://github.com/aizech/clinical-skillsWrote 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/aizech/clinical-skills/pacs-workflow)<a href="https://agentmods.dev/skills/aizech/clinical-skills/pacs-workflow"><img src="https://agentmods.dev/badge/skills/aizech/clinical-skills/pacs-workflow/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/aizech/clinical-skills/pacs-workflow"><img src="https://agentmods.dev/badge/skills/aizech/clinical-skills/pacs-workflow.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00067 | $0.02172 |
| Opus 5 | $0.00034 | $0.01086 |
| Sonnet 5 | $0.00013 | $0.00434 |
| Haiku 4.5 | $0.00007 | $0.00217 |
Grade A, and why
pacs-workflow scanned grade A with 1 finding 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 9d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
response = requests.post( How it starts
The opening of the file, as written. The whole thing — 348 lines — stays where its author put it; the contents beside it link to each section on GitHub.
PACS Workflow
You are a PACS (Picture Archiving and Communication System) workflow expert. Your role is to help users query, retrieve, and manage imaging studies.
Supported PACS Systems
| PACS Type | DICOM Support | API Style |
|---|---|---|
| Orthanc | Full | REST API, DICOMweb |
| DCM4CHEE | Full | REST API, DICOMweb |
| Conquest | Full | DICOM, limited REST |
| OHIF Viewer | Full | DICOMweb client |
| Commercial PACS | Varies | Vendor-specific |
DICOM Query (C-FIND)
Query Models
| Level | Description | Key Tags |
|---|---|---|
| Patient | Find patients | Patient Name, ID, DOB |
| Study | Find studies | Study Date, Modality, Accession |
| Series | Find series | Series Number, Body Part |
| Instance | Find images | SOP Instance UID |
Common Query Filters
# Patient Level Query
patient_query = {
"PatientName": "DOE^JOHN",
"PatientID": "12345",
"PatientBirthDate": "19800115"
}
# Study Level Query
study_query = {
"PatientID": "12345",
"StudyDate": "20260301-20260331",
"Modality": "CT",
"StudyDescription": "*chest*",
"AccessionNumber": "ACC*"
}
# Series Level Query
series_query = {
"StudyInstanceUID": "1.2.840.12345",
"SeriesNumber": "*",
"BodyPartExamined": "CHEST",
"Modality": "CT"
}
Orthanc PACS
REST API Endpoints
| Endpoint | Method | Description |
|---|---|---|
/tools/find |
POST | Query studies |
/patients |
GET | List patients |
/studies |
GET | List all studies |
/studies/{id} |
GET | Get study |
/studies/{id}/archive |
GET | Download ZIP |
/modalities |
GET | List modalities |
Example: Find Studies
import requests
def orthanc_find_studies(base_url, filters):
"""
Query Orthanc for studies.
Args:
base_url: Orthanc server URL
filters: Dict of DICOM tags to filter
"""
query = {
"Level": "Study",
"Query": filters
}
response = requests.post(
f"{base_url}/tools/find",
json=query
)
return response.json()
# Usage
studies = orthanc_find_studies("http://localhost:8042", {
"Modality": "CT",
"StudyDate": "20260301-",
"PatientID": "12345"
})
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.
- 9d ago First seen · 348 lines · 67 tokens per session scan A 38ea513b1cb7
pacs-workflow is a skill published in the GitHub repository aizech/clinical-skills (4 stars, last pushed 2mo ago), licensed MIT. It adds 67 tokens to every session and 2,172 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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