Generate hospital discharge summaries from admission data, hospital course, medications, and follow-up plans. Trigger when user needs to create a discharge summary, compile inpatient medical records, or generate post-hospitalization documentation for patients.
Install with Tessl CLI
npx tessl i github:aipoch/medical-research-skills --skill discharge-summary-writer82
Does it follow best practices?
If you maintain this skill, you can automatically optimize it using the tessl CLI to improve its score:
npx tessl skill review --optimize ./path/to/skillValidation for skill structure
Script invocation and JSON input schema
Script invocation
0%
100%
--input flag used
0%
100%
--output flag used
0%
100%
--format flag used
0%
100%
Six required JSON sections
100%
100%
patient_info required fields
100%
100%
admission_data required fields
100%
100%
Medication objects structure
100%
100%
Output file produced
100%
100%
follow_up section structure
100%
100%
Without context: $0.2335 · 1m 4s · 12 turns · 19 in / 3,293 out tokens
With context: $0.5899 · 1m 47s · 23 turns · 1,613 in / 5,496 out tokens
Document structure and medication documentation
All 7 sections present
66%
100%
Bilingual section headers
0%
100%
Physician signature section
0%
62%
License number field
0%
100%
AI-generated disclaimer
0%
100%
Medication generic names
100%
100%
Medication complete fields
100%
100%
Medication purpose
50%
30%
Medication special instructions
100%
100%
Discharge medications note
28%
100%
Patient info table format
85%
100%
Without context: $0.2197 · 1m · 12 turns · 19 in / 3,218 out tokens
With context: $0.6619 · 1m 45s · 26 turns · 5,179 in / 4,959 out tokens
Clinical content standards and follow-up instructions
Chief complaint format
100%
100%
Chief complaint concise
100%
100%
OPQRST onset documented
100%
100%
OPQRST quality documented
100%
100%
OPQRST severity documented
100%
100%
Relevant negatives in HPI
100%
100%
Chronological hospital course
100%
100%
Discharge diagnosis ordering
100%
100%
Follow-up appointment specifics
100%
100%
Emergency contact number
100%
100%
Warning signs specificity
100%
100%
Measurements with units
100%
100%
Without context: $0.2451 · 1m 25s · 9 turns · 14 in / 4,644 out tokens
With context: $0.6466 · 1m 51s · 23 turns · 2,534 in / 5,622 out tokens
Table of Contents
If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.