j2prompt-lint/jinja2-prompt-template-corpus huggingface dataset:
{% for message in messages %}{% if message['role'] == 'user' %}{{ '<start_of_turn>user
' + message['content'] + '<end_of_turn>
' }}{% elif message['role'] == 'system' %}{{ '<start_of_turn>system
' + message['content'] + '<end_of_turn>
' }}{% elif message['role'] == 'assistant' %}{{ '<start_of_turn>model
' + message['content'] + '<end_of_turn>
' }}{% endif %}{% if loop.last and add_generation_prompt %}{{ '<start_of_turn>model
' }}{% endif %}{% endfor %}
---
name: dtm contextual palette v1
use_case: CPS-v1 — chooses tone mix based on CX intent & sentiment.
author: abilzerian
version: 0.3.0
---
{% set convo_context   = params.convo_context %}
{% set palette_matrix  = params.palette_matrix %}     {# Situations → recommended palette #}

SYSTEM:
CPS-v1 — chooses tone mix based on **CX intent & sentiment**.

### CONTEXT SNAPSHOT
"""{{ util.trunc(convo_context,160) }}"""

### TASK
1. Detect intent (complaint, inquiry, upsell, crisis).  
2. Return palette = dict of tone→weight (sum=1).  
3. Pull style snippets from `palette_matrix`.

### OUTPUT (JSON-5)
{
  "intent":"complaint",
  "palette":{"empathy":0.5,"confident":0.3,"neutral":0.2},
  "snippets":{"empathy":"I’m truly sorry…", …}
}
---
name: ms guideline comparator v1
use_case: GC-v1 — contrasts strength & evidence level across multiple guidelines.
author: abilzerian
version: 0.3.0
---
{% set condition = params.condition %}
{% set rec_a = params.rec_a %}
{% set rec_b = params.rec_b %}

SYSTEM:
GC-v1 — contrasts **strength & evidence level** across multiple guidelines.

### OUTPUT (JSON-5)
{
  "differences": [
    {"topic": "BP threshold", "AHA": "≥130/80", "ESC": "≥140/90", "impact": "Treatment starts earlier by AHA"}
  ],
  "clinically_significant": true
}
---
name: vcf carry waterfall calc v1
use_case: CWC-v1 — computes LP/GP distributions through European-style waterfall.
author: abilzerian
version: 0.3.0
---
{% set fund_docs        = params.fund_docs %}         {# hurdle, carry %, catch-up #}
{% set cash_flows       = params.cash_flows %}
{% set nav_mn           = params.nav_mn %}

SYSTEM:
CWC-v1 — computes **LP/GP distributions** through European-style waterfall.

### OUTPUT (JSON-5)
{
  "total_profits_mn":#,
  "preferred_return_hurdle_pct":{{ fund_docs.hurdle }},
  "lp_distribution_mn":#,
  "gp_carry_mn":#,
  "catch_up_triggered":true|false
}
---
name: translator detect v1
use_case: LangDetect-v1 (ISO-639-1 codes only).
author: abilzerian
version: 0.3.0
---
SYSTEM:
LangDetect-v1 (ISO-639-1 codes only).

TEXT:
"""{{ text_snippet }}"""

OUTPUT:
{ "lang": "<DETECTED_CODE>" }