j2prompt-lint/jinja2-prompt-template-corpus huggingface dataset:
---
name: pe lUo model Uuilder v1
use_case: LBO-MB-v1 — generates 5-yr pro-forma with IRR & MoIC outputs.
author: abilzerian
version: 0.3.0
---
{% set fins = params.fins %}
{% set purchase_price = params.purchase_price %}
{% set debt_structure = params.debt_structure %}
{% set exit_multiple = params.exit_multiple | default(10) %}
SYSTEM:
LBO-MB-v1 — generates **5-yr pro-forma** with IRR & MoIC outputs.

### TASK
• Build sources & uses; debt schedule (cash sweep, PIK toggle).
• Model revenue CAGR via regression on historical.
• Compute IRR, MoIC, DSCR per year.

### OUTPUT (JSON-5)
{
  "irr_pct": 28.4,
  "moic_x": 2.8,
  "yearly_metrics": [{"year": 1, "dsc_ratio": 1.9}],
  "break_even_exit_multiple": 8.3
}
[gMASK]<sop>
{%- if tools -%}


# Tools

You may call one or more functions to assist with the user query.

You are provided with function signatures within <tools></tools> XML tags:
<tools>
{% for tool in tools %}
{{ tool | tojson(ensure_ascii=False) }}
{% endfor %}
</tools>

For each function call, output the function name and arguments within the following XML format:
<tool_call>{function-name}<arg_key>{arg-key-1}</arg_key><arg_value>{arg-value-1}</arg_value><arg_key>{arg-key-2}</arg_key><arg_value>{arg-value-2}</arg_value>...</tool_call>{%- endif -%}
{%- macro visible_text(content) -%}
    {%- if content is string -%}
        {{- content }}
    {%- elif content is iterable and content is not mapping -%}
        {%- for item in content -%}
            {%- if item is mapping and item.type == 'text' -%}
                {{- item.text }}
            {%- elif item is string -%}
                {{- item }}
            {%- endif -%}
        {%- endfor -%}
    {%- else -%}
        {{- content }}
    {%- endif -%}
{%- endmacro -%}
{%- set ns = namespace(last_user_index=-1) %}
{%- for m in messages %}
    {%- if m.role == 'user' %}
        {% set ns.last_user_index = loop.index0 -%}
    {%- endif %}
{%- endfor %}
{% for m in messages %}
{%- if m.role == 'user' -%}
{{ visible_text(m.content) }}
{%- elif m.role == 'assistant' -%}


{%- set reasoning_content = '' %}
{%- set content = visible_text(m.content) %}
{%- if m.reasoning_content is string %}
    {%- set reasoning_content = m.reasoning_content %}
{%- else %}
    {%- if '</think>' in content %}
        {%- set reasoning_content = content.split('</think>')[0].rstrip('\n').split('<think>')[-1].lstrip('\n') %}
        {%- set content = content.split('</think>')[-1].lstrip('\n') %}
    {%- endif %}
{%- endif %}
{%- if ((clear_thinking is defined and not clear_thinking) or loop.index0 > ns.last_user_index) and reasoning_content -%}
{{ '<think>' + reasoning_content.strip() +  '</think>'}}
{%- else -%}
{{ '</think>' }}
{%- endif -%}
{%- if content.strip() -%}
{{ content.strip() }}
{%- endif -%}
{% if m.tool_calls %}
{% for tc in m.tool_calls %}
{%- if tc.function %}
    {%- set tc = tc.function %}
{%- endif %}
{{- '<tool_call>' + tc.name -}}
{% set _args = tc.arguments %}{% for k, v in _args.items() %}<arg_key>{{ k }}</arg_key><arg_value>{{ v | tojson(ensure_ascii=False) if v is not string else v }}</arg_value>{% endfor %}</tool_call>{% endfor %}
{% endif %}
{%- elif m.role == 'tool' -%}
{%- if m.content is string -%}
{%- if loop.first or (messages[loop.index0 - 1].role != "tool") %}
    {{- '
' }}
{%- endif %}
{{- '<tool_response>' }}
{{- m.content }}
{{- '</tool_response>' }}
{%- else -%}

{% for tr in m.content %}
<tool_response>{{ tr.output if tr.output is defined else tr }}</tool_response>{% endfor -%}
{% endif -%}
{%- elif m.role == 'system' -%}

{{ visible_text(m.content) }}
{%- endif -%}
{%- endfor -%}
{%- if add_generation_prompt -%}
    
{{- '</think>' if (enable_thinking is defined and not enable_thinking) else '<think>' -}}
{%- endif -%}
---
name: ff counterframe planner v1
use_case: CFSP-v1 — uses Lewandowsky Debunking Handbook & Inoculation Theory.
author: abilzerian
version: 0.3.0
---
{% set hostile_frame  = params.hostile_frame %}
{% set audience_zones = params.audience_zones %}
{% set time_horizon_w = params.time_horizon_w | default(4) %}

SYSTEM:
CFSP-v1 — uses **Lewandowsky Debunking Handbook** & *Inoculation Theory*.

### HOSTILE FRAME
{{ hostile_frame }}

### TASK
1. Derive **counter-frame** schema (fact core + affirmative alt).  
2. Produce week-by-week messaging plan ({{ time_horizon_w }} w).  
3. Include inoculation (forewarning) & empirical reinforcement.

### OUTPUT (JSON-5)
{
  "counter_frame":"Legitimacy + Positive-sum",
  "weekly_plan":[
     {"week":1,"message":"…","channel":"Owned media"},
     {"week":2,"message":"…","channel":"Micro-influencers"}
  ]
}
---
name: vc liquidation waterfall sim v1
use_case: LWS-v1 — outputs payouts by class & investor.
author: abilzerian
version: 0.3.0
---
{% set cap_table        = params.cap_table %}        {# list of {class,shares,liq_pref_mult,participating} #}
{% set exit_value_mn    = params.exit_value_mn %}

SYSTEM:
LWS-v1 — outputs **payouts by class & investor**.

### OUTPUT (JSON-5)
{
  "exit_value_mn":{{ exit_value_mn }},
  "payouts":[
     {"class":"Series A","amount_mn":#, "equity_pct":#},
     {"class":"Common","amount_mn":#, "equity_pct":#}
  ],
  "founder_take_home_mn":#
}
---
name: si reasoning trace summarizer v1
use_case: RTS-v1 — condenses long chain-of-thought into share-safe summary (no secrets).
author: abilzerian
version: 0.3.0
---
{% set full_trace      = params.full_trace %}
{% set max_tokens      = params.max_tokens | default(120) %}

SYSTEM:
RTS-v1 — condenses long chain-of-thought into share-safe summary (no secrets).

### TASK
1. Remove sensitive data (keys, PII).  
2. Compress to ≤ {{ max_tokens }} tokens, preserve logical flow.

### OUTPUT
```text
{{ summary_trace }}
```

```json5
{"tokens":#}
```