<!-- COPYRIGHT NOTICE This file is part of the "Universal Biomedical Skills" project. Copyright c 2026 MD BABU MIA, PhD <md.babu.mia@mssm.edu All Rights Reserved. This code is proprietary and confidential. Unauthorized copying of this file, via any medium is strictly prohibited. Provenance:
Install with the open skills CLI (global, non-interactive — available in every Claude Code session):
npx skills add FreedomIntelligence/OpenClaw-Medical-Skills --skill "prior-auth-coworker" -g -a claude-code -yOr manually — clone and copy the skill directory (SKILL.md + companion files):
git clone --depth 1 https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills /tmp/OpenClaw-Medical-Skills && cp -r /tmp/OpenClaw-Medical-Skills/skills/prior-auth-coworker ~/.claude/skills/prior-auth-coworkerThis skill is a directory: SKILL.md is the entry point; the files below ship with it.
<!--
# COPYRIGHT NOTICE
# This file is part of the "Universal Biomedical Skills" project.
# Copyright (c) 2026 MD BABU MIA, PhD <md.babu.mia@mssm.edu>
# All Rights Reserved.
#
# This code is proprietary and confidential.
# Unauthorized copying of this file, via any medium is strictly prohibited.
#
# Provenance: Authenticated by MD BABU MIA
-->
---
name: 'prior-auth-coworker'
description: 'Prior Auth Review'
measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes.
allowed-tools:
- read_file
- run_shell_command
---
# Prior Authorization Coworker
This skill acts as an automated utilization management reviewer. It takes unstructured clinical notes and a procedure code, compares them against internal policy criteria (e.g., conservative therapy failure), and renders a decision.
## When to Use This Skill
* When a user asks to "review a prior auth request".
* When checking if a patient qualifies for a specific procedure (e.g., MRI).
* When you need to generate a structured approval/denial letter justification.
## Core Capabilities
1. **Policy Matching**: Checks against specific criteria (e.g., "Pain > 6 weeks").
2. **Trace Generation**: Produces an "Anthropic-style" `<thinking>` trace for auditability.
3. **Structured Output**: Returns a JSON object with decision, reasoning, and timestamps.
## Workflow
1. **Extract Data**: Parse the clinical note and procedure code from the user's input.
2. **Execute Review**: Run the coworker script.
3. **Present Decision**: Output the JSON decision and the reasoning trace.
## Example Usage
**User**: "Check if this patient qualifies for an MRI of the Lumbar Spine: Patient has had back pain for 2 months, tried PT but it didn't work."
**Agent Action**:
```bash
python3 Skills/Clinical/Prior_Authorization/anthropic_coworker.py --code "MRI-L-SPINE" --note "Patient has back pain > 2 months. Failed PT."
```
## Supported Policies
* `MRI-L-SPINE` (Lumbar Spine MRI)
<!-- AUTHOR_SIGNATURE: 9a7f3c2e-MD-BABU-MIA-2026-MSSM-SECURE -->Give the agent its own dedicated email inbox via AgentMail. Send, receive, and manage email autonomously using agent-owned email addresses (e.g. hermes-agent@agentmail.to).
AudioCraft: MusicGen text-to-music, AudioGen text-to-sound.
Axolotl: YAML LLM fine-tuning (LoRA, DPO, GRPO).