medical-invoice-fix-review

Apply auditor comments from comments.json to output.json and manage claim-denial workflow.

Updated Aug 27, 2026
One-click install
npx skills add https://github.com/arkangelai/skills --skill medical-invoice-fix-review
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: medical-invoice-fix-review
Source: https://github.com/arkangelai/skills/tree/main/medical-insurance-audit/medical-invoice-fix-review
Command: npx skills add https://github.com/arkangelai/skills --skill medical-invoice-fix-review

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Bridges human auditor feedback and automated workflows by applying edits to the consolidated output (output.json), updating labels, and preparing for final approval, while delegating PDF regeneration to a separate step.

Core Features & Use Cases

  • Watches comments.json for new entries from auditors and applies them to output.json in chronological order.
  • Classifies intents (modify_finding, add_finding, approve, escalate, etc.), updates hallazgos and resumen, and logs changes for traceability.
  • Signals pdf_regeneration_needed when changes occurred and appends a detailed audit-log entry for each processed comment.
  • Ensures safety invariants (no negative valor_glosado, total_glosado ≤ total_facturado) and supports final approval or escalation flows.

Quick Start

Run this skill in your working directory when new auditor comments appear in comments.json to auto-apply edits to output.json.

Frequently Asked Questions about medical-invoice-fix-review

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I apply auditor comments to a medical invoice JSON file automatically?

To apply auditor comments to a medical invoice JSON file, this skill reads comments.json chronologically, classifies intents like modify_finding or approve, and patches the output.json accordingly. It updates hallazgos and resumen fields while appending detailed audit-log entries for traceability.

What is the best way to manage a claim-denial workflow until final approval?

Managing a claim-denial workflow requires processing auditor feedback chronologically until final approval is achieved. This skill classifies comment intents, applies JSON patches to output.json, enforces safety invariants like total_glosado limits, and supports escalation flows when edits cannot be resolved immediately.

How do I classify structured intents from auditor feedback in an audit workflow?

Classifying structured intents from auditor feedback involves parsing comments.json to identify actions such as modify_finding, add_finding, approve, or escalate. This skill automatically categorizes each comment, applies the corresponding JSON patch to output.json, and logs the change to maintain a strict audit trail.

Can I signal PDF regeneration automatically after applying JSON patches to invoice findings?

Yes, you can signal PDF regeneration automatically after applying JSON patches to invoice findings. This skill sets the pdf_regeneration_needed flag whenever changes affect hallazgos or resumen, ensuring the PDF output reflects the latest auditor corrections while leaving the actual regeneration to a separate step.

What safety invariants are enforced when applying auditor edits to medical invoice claims?

Safety invariants enforced when applying auditor edits to medical invoice claims include preventing negative valor_glosado values and ensuring total_glosado never exceeds total_facturado. These guards protect the output.json integrity during the JSON patch application process across all processed auditor comments.

Do I need a separate comments.json file to process auditor feedback for medical invoice fixes?

Yes, you need a separate comments.json file containing new auditor entries to process medical invoice fixes. The skill watches this file for new comments, applies them chronologically to output.json, updates resumen and hallazgos, and logs every change to maintain full audit traceability before final approval.