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Install with the open skills CLI (global, non-interactive — available in every Claude Code session):
npx skills add FreedomIntelligence/OpenClaw-Medical-Skills --skill "clinical-note-summarization" -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/clinical-note-summarization ~/.claude/skills/clinical-note-summarizationThis skill is a directory: SKILL.md is the entry point; the files below ship with it.
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# 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.
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# Provenance: Authenticated by MD BABU MIA
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---
name: clinical-note-summarization
description: Structure raw clinical notes into SOAP-format summaries with explicit contradictions, missing data, and ICD-linked assessments using the provided prompt + usage script.
allowed-tools:
- read_file
- run_shell_command
---
## At-a-Glance
- **description (10-20 chars):** SOAP builder
- **keywords:** clinical-notes, SOAP, guardrails, ICD10, gaps
- **measurable_outcome:** Produce SOAP markdown + JSON (when requested) covering all four sections with ≥95% note coverage and explicit missing info in ≤2 minutes per note.
## Inputs
- `note_text` (dictation, OCR, or EHR export) and optional `patient_context` metadata.
- `output_format` (`markdown` default, `json` when downstream validators need schema).
## Outputs
1. Structured SOAP summary with Subjective/Objective/Assessment/Plan bulleting.
2. Alerts plus missing-information checklist.
3. Optional JSON payload using schema from README.
## Workflow
1. **Load system prompt:** `prompt.md` enforces no hallucinations + data gap surfacing.
2. **Normalize input:** Pre-clean vitals, labs, and timeline context when available.
3. **Generate summary:** Call preferred LLM (OpenAI, Anthropic, Gemini, OSS) using `usage.py` as a template.
4. **Validate:** Cross-check extracted values vs. source text and ensure contradictions/missing data are spelled out.
5. **Deliver output:** Provide markdown + JSON as required and log PHI handling steps.
## Guardrails
- Never invent findings; state "not provided" explicitly.
- Mark outputs as documentation support only—not clinical decisions.
- Strip/re-mask PHI before storing prompts/responses.
## References
- For detailed schema, guardrails, and integration snippets see `README.md`, `prompt.md`, and `usage.py`.
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