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Get Started Free →Guide a veterinary team through a compassionate end-of-life conversation with a pet owner — quality-of-life assessment, the recommendation, and the logistics. Use when asked to help discuss euthanasia, assess quality of life, prepare for a difficult end-of-life conversation, or support an owner facing the decision. Produces a quality-of-life framework, empathetic language for the conversation, how to answer the hard questions (is it time, will it hurt, should the kids be there), and the practica
.claude/skills/mohitagw15856-euthanasia-conversation/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-02 | ✗→✓ | ▲ Improved | 9% | 0% |
| case-04 | ✗→✓ | ▲ Improved | 158% | 0% |
| case-05 | ✓→✓ | ＝ Same ✓ | 89% | 0% |
| case-06 | ✓→✓ | ＝ Same ✓ | 32% | 0% |
| case-07 | ✓→✓ | ＝ Same ✓ | 39% | 0% |
This is the conversation that makes or breaks how an owner remembers their pet's death — and their trust in the practice. Done well, it relieves guilt and gives a peaceful goodbye; done clumsily, it haunts people for years. This skill helps the team assess quality of life honestly, guide the decision without pushing it, and handle the moment with clarity and warmth.
Given the patient's condition and the owner's situation, produce the guidance — offer a quality-of-life read, language for the conversation, and the logistics. Support the owner's decision without pressuring in either direction; be honest about prognosis without being blunt to the point of cruelty.
Ask for (if not provided, else infer and label):
A structured assessment (e.g. the HHHHHMM-style factors: hurt/pain, hunger, hydration, hygiene, happiness, mobility, more-good-days-than-bad) — an honest picture to ground the conversation, not a verdict imposed on the owner.
Empathetic, plain language for:
What the process actually involves (sedation, the steps, that it's peaceful), options for where (clinic, home, comfort room), being present or not (no judgment), aftercare (burial, cremation options, paw print/keepsake), and payment handled gently.
Acknowledging the loss, grief-support resources, and any follow-up (a condolence card) the practice offers.
| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-01 | fail→fail | 21,675 | 24,528 | +13% | 1 | 1 | 0% | 3,366 | 4,301 | +28% | 0 | 0 | — |
case-02 | fail→pass | 24,187 | 21,028 | -13% | 1 | 1 | 0% | 3,648 | 3,984 | +9% | 0 | 0 | — |
case-03 | fail→fail | 20,746 | 19,408 | -6% | 1 | 1 | 0% | 3,157 | 3,653 | +16% | 0 | 0 | — |
case-04 | fail→pass | 10,572 | 21,570 | +104% | 1 | 1 | 0% | 1,505 | 3,877 | +158% | 0 | 0 | — |
case-05 | pass→pass | 12,940 | 21,948 | +70% | 1 | 1 | 0% | 2,077 | 3,931 | +89% | 0 | 0 | — |
case-06 | pass→pass | 19,064 | 19,471 | +2% | 1 | 1 | 0% | 2,988 | 3,944 | +32% | 0 | 0 | — |
case-07 | pass→pass | 16,365 | 18,301 | +12% | 1 | 1 | 0% | 2,465 | 3,435 | +39% | 0 | 0 | — |
case-08 | pass→pass | 13,985 | 18,436 | +32% | 1 | 1 | 0% | 2,210 | 3,448 | +56% | 0 | 0 | — |
case-09 | pass→pass | 14,697 | 16,125 | +10% | 1 | 1 | 0% | 2,159 | 3,109 | +44% | 0 | 0 | — |
case-10 | pass→pass | 12,594 | 18,280 | +45% | 1 | 1 | 0% | 1,952 | 3,397 | +74% | 0 | 0 | — |
case-11 | pass→pass | 15,704 | 19,045 | +21% | 1 | 1 | 0% | 2,541 | 3,416 | +34% | 0 | 0 | — |
case-12 | pass→pass | 9,823 | 14,701 | +50% | 1 | 1 | 0% | 1,525 | 2,769 | +82% | 0 | 0 | — |
case-13 | pass→pass | 13,080 | 17,180 | +31% | 1 | 1 | 0% | 2,041 | 3,319 | +63% | 0 | 0 | — |
case-14 | pass→pass | 11,093 | 13,793 | +24% | 1 | 1 | 0% | 1,830 | 2,741 | +50% | 0 | 0 | — |
case-15 | pass→pass | 18,420 | 15,697 | -15% | 1 | 1 | 0% | 1,468 | 3,089 | +110% | 0 | 0 | — |
case-16 | pass→pass | 14,760 | 17,155 | +16% | 1 | 1 | 0% | 2,209 | 3,238 | +47% | 0 | 0 | — |
case-17 | pass→pass | 13,059 | 18,031 | +38% | 1 | 1 | 0% | 1,858 | 3,318 | +79% | 0 | 0 | — |
case-18 | pass→pass | 14,307 | 16,949 | +18% | 1 | 1 | 0% | 2,207 | 3,308 | +50% | 0 | 0 | — |
case-19 | pass→pass | 19,503 | 21,686 | +11% | 1 | 1 | 0% | 3,044 | 3,871 | +27% | 0 | 0 | — |
case-20 | pass→pass | 8,883 | 15,406 | +73% | 1 | 1 | 0% | 1,327 | 3,175 | +139% | 0 | 0 | — |
case-21 | pass→pass | 16,292 | 20,477 | +26% | 1 | 1 | 0% | 2,411 | 3,307 | +37% | 0 | 0 | — |
case-22 | pass→pass | 16,063 | 19,081 | +19% | 1 | 1 | 0% | 2,364 | 3,420 | +45% | 0 | 0 | — |
DecimalAI ran this skill against gemini-3.6-flash twice over the same eval suite — once with the skill loaded and once without — and compared the two runs case by case. 22 cases were attempted. The headline lift of +9 percentage points is the difference between those two pass rates over the 22 comparable cases.
Without the skill loaded, the model failed this case. With it loaded, the same prompt on the same model passed. This is one improved case from the latest verified run; every case, including any that regressed, is in the table above.
Other measured skills in the registry, with their headline benchmark lift.