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prior-auth-coworker

prior-auth-coworker,来自 FreedomIntelligence/OpenClaw-Medical-Skills 的 agent 技能。

读文件无严重或高危命中FreedomIntelligence/OpenClaw-Medical-Skills

它会碰到什么

扫了多少6 个文本文件,18 KB
它会碰到什么读文件
命中总数1 处
命中统计严重 0 · 高 0 · 中 1 · 低 0

这一栏是扫描器报的事实,不是结论。命中多不等于有毒(安全工具、规则库、示例脚本本来就会包含危险写法),命中少也不等于干净。它和你手上的凭据、文件、网络有什么关系,需要你自己看。

技能内容

<!--

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:

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 -->

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