ai-detection-pipeline

ai-detection-pipeline is a skill for Claude Code, Codex from aizech/clinical-skills. It costs 53 tokens per session (2,553 once invoked), scanned A, original, MIT.

A workflow for connecting medical-image AI detection systems to a PACS, the system hospitals use to store and view medical images. It covers detection engines, result storage, worklists, and alerts.

In plain words
What is it for?
Use it to integrate or configure systems such as Aidoc, Nvidia Clara, Zebra Medical, MaxQ AI, Qure AI, Lunit, and Riverain for modalities including CT, MRI, and X-ray.
Why use it?
It organizes the path from receiving DICOM images to running AI analysis and delivering findings to clinical users.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: installed under .agents/ (shared by several agents).

Good fit Use it to integrate or configure systems such as Aidoc, Nvidia Clara, Zebra Medical, MaxQ AI, Qure AI, Lunit, and Riverain for modalities including CT, MRI, and X-ray.

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Install with agentmods
npx agentmods add skills/aizech/clinical-skills/ai-detection-pipeline
Install

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.

Any agent
npx skills add aizech/clinical-skills --skill ai-detection-pipeline
Clone the repo
git clone --depth 1 https://github.com/aizech/clinical-skills

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for ai-detection-pipeline

README.md
[![agentmods](https://agentmods.dev/badge/skills/aizech/clinical-skills/ai-detection-pipeline/github.svg)](https://agentmods.dev/skills/aizech/clinical-skills/ai-detection-pipeline)
Your own site
<a href="https://agentmods.dev/skills/aizech/clinical-skills/ai-detection-pipeline"><img src="https://agentmods.dev/badge/skills/aizech/clinical-skills/ai-detection-pipeline/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.

agentmods 80×15 button for ai-detection-pipeline

Your own site · 80×15
<a href="https://agentmods.dev/skills/aizech/clinical-skills/ai-detection-pipeline"><img src="https://agentmods.dev/badge/skills/aizech/clinical-skills/ai-detection-pipeline.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 53 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,553 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 1 finding. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00053 $0.02553
Opus 5 $0.00026 $0.01277
Sonnet 5 $0.00011 $0.00511
Haiku 4.5 $0.00005 $0.00255

Measured 11d ago against content hash 8a0a036a0e68, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

ai-detection-pipeline 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 11d 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(
.agents/skills/ai-detection-pipeline/SKILL.md · 384 lines

How it starts

The opening of the file, as written. The whole thing — 384 lines — stays where its author put it; the contents beside it link to each section on GitHub.

AI Detection Pipeline

You are an expert in AI medical imaging detection pipelines. Your role is to help users integrate, configure, and optimize AI detection systems.

Supported AI Platforms

Platform Focus Areas Modality
Aidoc Triage, hemorrhage, PE, C-spine CT
Nvidia Clara Multi-modal, general detection CT, MRI, X-ray
Zebra Medical Multi-finding, chest X-ray, CT
MaxQ AI Neuro, PE, chest CT
Qure AI Chest, head X-ray, CT
Lunit Chest, mammography X-ray, MG
Riverain Chest, lung nodules X-ray

Pipeline Architecture

+-------------+     +-------------+     +-------------+     +-------------+
|    PACS     |---->|  AI Engine  |---->|   Results   |---->|  Worklist   |
|  (Source)   |     |  (Detect)   |     |   (Store)   |     |  (Alert)    |
+-------------+     +-------------+     +-------------+     +-------------+
      |                   |                   |                   |
      v                   v                   v                   v
  DICOM Send         Inference          Database             Notification
  C-STORE           GPU Compute         Results Store        Pager/Email

Aidoc Integration

API Configuration

import requests

AIDOC_API = "https://api.aidoc.com/v1"

def configure_aidoc(api_key):
    """Configure Aidoc API."""
    return {
        "base_url": AIDOC_API,
        "headers": {
            "Authorization": f"Bearer {api_key}",
            "Content-Type": "application/json"
        }
    }

def submit_study_aidoc(config, study_uid, study_url):
    """Submit study for Aidoc analysis."""
    response = requests.post(
        f"{config['base_url']}/studies",
        headers=config["headers"],
        json={
            "study_uid": study_uid,
            "study_dicom_url": study_url,
            "priority": "normal"
        }
    )
    return response.json()

Detection Types

AIDOC_DETECTIONS = {
    "ct_head": [
        "intracranial_hemorrhage",
        "mass_effect",
        "midline_shift",
        "fracture"
    ],
    "ct_chest": [
        "pulmonary_embolism",
        "pneumothorax",
        "cervical_spine_fracture"
    ],
    "ct_angiography": [
        "aortic_dissection",
        "pulmonary_embolism"
    ]
}

Read the full file on GitHub · 384 lines

Files

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.

Changes

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.

  1. 11d ago First seen · 384 lines · 53 tokens per session scan A 8a0a036a0e68

Subscribe to this mod's changes

ai-detection-pipeline is a skill published in the GitHub repository aizech/clinical-skills (4 stars, last pushed 2mo ago), licensed MIT. It adds 53 tokens to every session and 2,553 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.