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Clinical note summarization

Skill FridrichMethod/awesome-skills/skills/clinical-note-summarization

Structure raw clinical notes into SOAP-format summaries with explicit contradictions, missing data, and ICD-linked assessments using the provided prompt + usage script.From its SKILL.md

Install
npx -y skills add FridrichMethod/awesome-skills --skill clinical-note-summarization

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

2 things to look at

  • no licenseNo license file was found in the repository. Code published without one is not open source by default, so using it at work is a question for whoever answers licensing questions where you are.
  • 13 stars13 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

SKILL.md

2.1 KB, 467 tokens by cl100k_base, as published. Nobody here has run it

<!-- # COPYRIGHT NOTICE # This file is part of the "Universal Biomedical Skills" project. # Copyright (c) 2026 MD BABU MIA, PhD <[email protected]> # 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 -->

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.
<!-- AUTHOR_SIGNATURE: 9a7f3c2e-MD-BABU-MIA-2026-MSSM-SECURE -->

What ships with it: 5 files

37.0 KB alongside SKILL.md, 2 of them executable

Keep looking

Skills are one crate of 325,949. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.