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Opalite medical translator

Skill riteshkew/yc-skills/skills/opalite-medical-translator

Translate clinical text between clinician jargon and patient-friendly language (or across spoken languages), preserving every dosage and numeric value verbatim, expanding all abbreviations correctly, and flagging anything that needs human verification.From its SKILL.md

Install
npx -y skills add riteshkew/yc-skills --skill opalite-medical-translator

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

One thing to look at

  • 0 stars0 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

5.0 KB, ~1.1k tokens by cl100k_base, as published. Nobody here has run it

Workflow

When this skill triggers, follow these steps in order.

Step 1 — Ingest Clinical Text and Target Audience

Ask the user for (or read from the prompt):

  1. Clinical text — the source document: discharge summary, after-visit note, lab result, prescription instructions, or any clinical snippet.
  2. Target audience — one of:
    • patient-friendly (plain English, reading level ~6th grade)
    • caregiver (slightly more technical, but still jargon-free)
    • spanish-patient (patient-friendly, translated into Spanish)
    • clinician (reverse direction — patient description back into clinical shorthand)
  3. Language override (optional) — any ISO language name, e.g. "Mandarin", "Portuguese". Overrides the audience language if set.

If the clinical text or target audience is missing, prompt:

"Please provide: (1) the clinical text you want translated, and (2) the target audience (patient-friendly, caregiver, spanish-patient, or clinician)."

Step 2 — Extract and Inventory Critical Values

Before writing a single word of translation, internally build an inventory:

  • Dosages and concentrations: e.g. 500mg, 0.9% NaCl, 10 units
  • Frequencies: e.g. TID, BID, q8h, PRN
  • Durations and intervals: e.g. x7d, x14 days, 2 wks
  • Thresholds and reference values: e.g. >38.5°C, <90 mmHg, HbA1c >7%
  • Numeric lab values: e.g. WBC 12.4, Cr 1.1 mg/dL, INR 2.3
  • Procedure and anatomy abbreviations: e.g. s/p lap chole, RUQ, PCP, D/C

Record every item. These are the verbatim preservation list — none may be paraphrased or altered in the output.

Step 3 — Translate to the Target Register

Produce the translated document following these rules:

For patient-friendly / caregiver / language targets:

  • Expand every abbreviation on first use, e.g. TID (three times a day).
  • Write dosages and frequencies as: amoxicillin 500 mg (500mg), taken three times a day (TID) — preserve the original value in parentheses if space allows, or inline directly.
  • Never substitute a numeric value: 500mg stays 500mg, never "half a gram". 38.5°C stays 38.5°C, not "slightly above normal".
  • Use short sentences (≤20 words each).
  • Avoid Latin phrases; use plain equivalents (by mouth not per os).
  • Organise the output with clear section headers: What happened, Your medications, Follow-up appointments, Warning signs — return to the ER if you notice any of these.
  • Keep the Warning signs section visually prominent (bold header).

For clinician (reverse) direction:

  • Convert plain-language descriptions back to standard clinical shorthand.
  • Preserve all numeric values exactly as the patient stated them.
  • Flag any values that appear clinically implausible with [VERIFY].

Step 4 — Flag Ambiguities and Add the Verification Notice

After the translated document, always append two sections:

Things to verify with your provider

List every term or instruction from the source that is:

  • Ambiguous or context-dependent (e.g. a PRN medication with no stated threshold)
  • An abbreviation that could have multiple expansions (e.g. MS = multiple sclerosis OR morphine sulfate)
  • A value outside typical patient reference ranges that warrants explanation
  • Any instruction requiring professional clinical judgement

Format as a numbered list. If nothing is ambiguous, write: "No ambiguous terms identified — still confirm all instructions with your provider before acting."

Verification notice

Always end with this exact block, adapted for the target language if translating:

Important: This translation is a communication aid only. It is not medical advice. Always confirm your medications, doses, and follow-up instructions directly with your healthcare provider or pharmacist before making any changes to your care.

Step 5 — Quality Check

Before returning output, verify the inventory from Step 2:

  • Every dosage value from the source appears verbatim in the output (500mg not "500 milligrams" unless the original said that).
  • Every frequency abbreviation is expanded AND the original abbreviation is preserved in parentheses on first use.
  • Every duration and threshold appears unchanged.
  • The Things to verify with your provider list is present.
  • The Important verification notice is present.
  • The ## Rubric section is appended.

If any check fails, revise before returning.

Example

See examples/input.md for a realistic discharge-summary snippet with multiple dosages, numeric thresholds, and clinical abbreviations. See examples/output.md for the complete patient-friendly rewrite, verification list, and rubric.

What ships with it: 4 files

16.1 KB alongside SKILL.md

.claude-plugin/

examples/

Gives 0 of the 12 instructions most healthcare skills give in ~1.1k tokens

Counted across 147 of the 152 authors here whose files we hold, read 2026-08-07

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Said here and by no other author read

  • obtain clinical text and target audience
  • prompt for missing text or target audience
  • build an inventory of dosages and numeric values
  • preserve every dosage and numeric value verbatim
  • keep sentences under twenty words
  • use plain equivalents instead of Latin phrases

Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once. Length counted with cl100k_base; the agent that loads this file may tokenize it differently.

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