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aipoch-ai

Icd10 Cpt Coding Assistant

by AIpoch · GitHub ↗ · v0.1.0 · MIT-0
cross-platform ⚠ suspicious
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Install in OpenClaw
/install icd10-cpt-coding-assistant
Description
Automatically recommend ICD-10 diagnosis codes and CPT procedure codes from clinical notes. Trigger when: user provides clinical notes, patient encounter sum...
README (SKILL.md)

ICD-10 & CPT Coding Assistant

A medical coding assistant that parses clinical notes and recommends appropriate ICD-10 diagnosis codes and CPT procedure codes with confidence scoring.

Overview

This skill analyzes clinical documentation to extract relevant medical information and map it to standardized coding systems:

  • ICD-10-CM: International Classification of Diseases, 10th Revision, Clinical Modification (diagnosis codes)
  • CPT: Current Procedural Terminology (procedure/service codes)

Technical Difficulty: HIGH ⚠️

⚠️ HUMAN REVIEW REQUIRED: Medical coding directly impacts billing, reimbursement, and clinical documentation. All recommendations must be verified by a certified medical coder or healthcare provider.

Usage

python scripts/main.py --input "clinical_note.txt" [--format json|text]

Or use programmatically:

from scripts.main import CodingAssistant

assistant = CodingAssistant()
result = assistant.analyze("Patient presents with acute bronchitis...")
print(result.icd10_codes)
print(result.cpt_codes)

Parameters

Parameter Type Default Required Description
--input, -i string - Yes Path to clinical note file
--format, -f string json No Output format (json, text)
--output, -o string stdout No Output file path
--confidence-threshold float 0.7 No Minimum confidence score (0.0-1.0)
--include-alternatives flag false No Include alternative code suggestions

Input Format

Accepts clinical notes in various formats:

  • Free-text narrative
  • SOAP notes (Subjective, Objective, Assessment, Plan)
  • Discharge summaries
  • Progress notes
  • Procedure reports

Output Format

ICD-10 Recommendations

{
  "icd10_codes": [
    {
      "code": "J20.9",
      "description": "Acute bronchitis, unspecified",
      "confidence": 0.92,
      "evidence": ["cough for 5 days", "wheezing on exam"],
      "alternatives": ["J20.0", "J44.9"]
    }
  ]
}

CPT Recommendations

{
  "cpt_codes": [
    {
      "code": "99213",
      "description": "Office visit, established patient, moderate complexity",
      "confidence": 0.85,
      "evidence": ["detailed history", "low complexity decision making"],
      "time": "20 minutes"
    }
  ]
}

Confidence Scoring

  • 0.90-1.00: High confidence - Clear documentation, unambiguous mapping
  • 0.70-0.89: Medium confidence - Good documentation, some interpretation required
  • 0.50-0.69: Low confidence - Incomplete documentation, multiple possibilities
  • \x3C0.50: Very low confidence - Insufficient information, manual review essential

Limitations

  1. No Medical Advice: This tool does not provide clinical advice or diagnoses
  2. Coding Complexity: Cannot handle all coding nuances (comorbidities, sequencing, modifiers)
  3. Regional Variations: May not account for payer-specific coding requirements
  4. Updates: Code sets may not reflect the latest annual updates

References

See references/ folder for:

  • icd10_common_codes.json: Frequently used ICD-10 codes by specialty
  • cpt_common_codes.json: Frequently used CPT codes by specialty
  • coding_guidelines.md: General coding guidelines and conventions

Safety & Compliance

  • HIPAA Awareness: Ensure de-identification of PHI before processing
  • Audit Trail: Maintain records of automated recommendations for compliance
  • Human Oversight: All codes must be reviewed and approved by qualified personnel

Dependencies

  • Python 3.8+
  • See requirements.txt for package dependencies

Risk Assessment

Risk Indicator Assessment Level
Code Execution Python/R scripts executed locally Medium
Network Access No external API calls Low
File System Access Read input files, write output files Medium
Instruction Tampering Standard prompt guidelines Low
Data Exposure Output files saved to workspace Low

Security Checklist

  • No hardcoded credentials or API keys
  • No unauthorized file system access (../)
  • Output does not expose sensitive information
  • Prompt injection protections in place
  • Input file paths validated (no ../ traversal)
  • Output directory restricted to workspace
  • Script execution in sandboxed environment
  • Error messages sanitized (no stack traces exposed)
  • Dependencies audited

Prerequisites

# Python dependencies
pip install -r requirements.txt

Evaluation Criteria

Success Metrics

  • Successfully executes main functionality
  • Output meets quality standards
  • Handles edge cases gracefully
  • Performance is acceptable

Test Cases

  1. Basic Functionality: Standard input → Expected output
  2. Edge Case: Invalid input → Graceful error handling
  3. Performance: Large dataset → Acceptable processing time

Lifecycle Status

  • Current Stage: Draft
  • Next Review Date: 2026-03-06
  • Known Issues: None
  • Planned Improvements:
    • Performance optimization
    • Additional feature support
Usage Guidance
This package appears to be what it claims: a local ICD-10/CPT recommendation tool. Before installing/using it in a production or PHI-containing environment: 1) Open and review scripts/main.py to confirm it performs no network calls, telemetry, or unexpected subprocess execution; 2) Inspect requirements.txt to verify third‑party libraries are trustworthy and up-to-date; 3) Test with de-identified or synthetic clinical notes first; 4) Verify the script validates input paths (no ../ traversal) and enforces sandboxed output locations; 5) Prefer to run inside a restricted environment (container/sandbox) and have all outputs audited by a qualified coder — the SKILL.md itself reminds users that human review is required. If you want, provide the contents of scripts/main.py and requirements.txt and I will review them for network I/O, credential usage, or other red flags (that would raise my confidence level).
Capability Analysis
Type: OpenClaw Skill Name: icd10-cpt-coding-assistant Version: 0.1.0 The skill provides a medical coding assistant that parses clinical notes using regex and keyword matching. While the logic is aligned with its stated purpose and contains no intentional malware, `scripts/main.py` is vulnerable to path traversal because it opens user-provided file paths via the `--input` argument without any sanitization. This risk is explicitly noted as an unchecked item in the security checklist within `SKILL.md`, indicating a known but unaddressed vulnerability.
Capability Assessment
Purpose & Capability
Name/description match the packaged assets: SKILL.md documents ICD-10/CPT recommendations and the repository includes main.py plus multiple code/mapping/guideline reference files consistent with that purpose. No unrelated credentials, binaries, or odd install steps are requested.
Instruction Scope
Runtime instructions tell the agent/user to run scripts/main.py on an input clinical-note file and to write output; that behavior is appropriate for the stated purpose. However the instructions accept arbitrary input file paths (no enforced sandboxing is shown) and rely on the implementer/user to de-identify PHI. The SKILL.md contains a security checklist (mentions path validation/prompt injection protections) but does not show that those protections are implemented. I could not fully verify what scripts/main.py actually does from the SKILL.md alone.
Install Mechanism
No install spec or remote downloads are present (instruction-only skill plus packaged Python script and local reference files). Dependencies are declared in requirements.txt (small file present) — no high-risk external install URLs or extract steps in the registry metadata.
Credentials
The skill requests no environment variables, no credentials, and no config paths. That is proportionate for a local coding assistant. There are no hidden credential requirements declared in SKILL.md.
Persistence & Privilege
Flags show always:false and normal model invocation behavior. The skill does not request elevated or permanent presence and does not declare modifications to other skills or system-wide settings.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install icd10-cpt-coding-assistant
  3. After installation, invoke the skill by name or use /icd10-cpt-coding-assistant
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v0.1.0
Initial public release. - Automatically recommends ICD-10 and CPT codes from clinical notes with confidence scoring. - Supports various input formats including free-text, SOAP notes, and discharge summaries. - Offers command-line and programmatic interfaces for analysis. - Allows configurable confidence thresholds and inclusion of alternative code suggestions. - Emphasizes human review, compliance requirements, and provides technical risk assessment. - Includes sample references and coding guidelines.
Metadata
Slug icd10-cpt-coding-assistant
Version 0.1.0
License MIT-0
All-time Installs 0
Active Installs 0
Total Versions 1
Frequently Asked Questions

What is Icd10 Cpt Coding Assistant?

Automatically recommend ICD-10 diagnosis codes and CPT procedure codes from clinical notes. Trigger when: user provides clinical notes, patient encounter sum... It is an AI Agent Skill for Claude Code / OpenClaw, with 166 downloads so far.

How do I install Icd10 Cpt Coding Assistant?

Run "/install icd10-cpt-coding-assistant" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is Icd10 Cpt Coding Assistant free?

Yes, Icd10 Cpt Coding Assistant is completely free, licensed under MIT-0. You can download, install and use it at no cost.

Which platforms does Icd10 Cpt Coding Assistant support?

Icd10 Cpt Coding Assistant is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created Icd10 Cpt Coding Assistant?

It is built and maintained by AIpoch (@aipoch-ai); the current version is v0.1.0.

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