prior-auth-coworker

SkillDev tools

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.

Instructions available. Your AI can read the instructions. Execution depends on the setup they require.

Add ahel to your AI once: Claude, ChatGPT, Cursor, Claude Code or Codex. Then ask it to use this.

Then ask your AI: use the prior-auth-coworker skill

About this skill

The largest open-source medical AI skills library for OpenClaw🦞.

What this skill tells your AI

The instructions your AI receives, as published by freedomintelligence/openclaw-medical-skills in skills/prior-auth-coworker/SKILL.md and read by ahel’s review.


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)

Signals

GitHub stars
3k
Forks
412
Last commit
Jul 2026
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Item type
skill
Key
prior-auth-coworker
Source
github.com/freedomintelligence/openclaw-medical-skills