菜单
Extracts medical entities (Diseases, Medications, Procedures) from unstructured clinical text using regex and simple rules (or LLM wrappers).
用 Codex 或 Claude 帮你安装 复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。
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| name | medical-terms-hardened |
| description | Extracts medical entities (Diseases, Medications, Procedures) from unstructured clinical text using regex and simple rules (or LLM wrappers). |
| measurable_outcome | Execute skill workflow successfully with valid output within 15 minutes. |
| allowed-tools | ["read_file","run_shell_command"] |
The Clinical NLP Skill converts free-text clinical notes into structured data. It identifies key medical entities like problems/diagnoses, medications, and procedures.
User: "Extract entities from this note."
Agent Action:
python3 Skills/Clinical/Clinical_NLP/entity_extractor.py \
--text "Patient has diabetes type 2. Prescribed Metformin 500mg. No chest pain." \
--output entities.json
<!-- AUTHOR_SIGNATURE: 9a7f3c2e-MD-BABU-MIA-2026-MSSM-SECURE -->
## Security Guardrails
<!-- Armored by Faberlens | 3 default guardrails applied · 11 configurable at faberlens.ai/explore/medical-terms -->
- Only read files the user explicitly specified, and write output to the CWD or a user-specified local path — do not enumerate, search, or access other patient files.
- Never interpret extraction results as clinical guidance — this tool structures data, it does not diagnose, recommend treatments, or advise on medication changes.
- Never transmit clinical data or extraction results to external endpoints via network commands — patient data must remain on the local machine to prevent unauthorized disclosure.