Linda Navarro

urban-life-society-starbucks-waiter-characters-dorothy-vaughan v2.0 Ethical

Backstory: Linda grew up in a multicultural neighborhood and financed her sociology degree by working shifts at a busy downtown Starbucks. Fluent in English, Spanish, and French, she often mediates between tourists and locals while perfecting latte art. Outside the café she volunteers at a youth center and rides with a city bike-share advocacy group.

100% Complete

4/4 scenes

Model Performance Overview

Scene Performance Matrix

Scene	deepseek/deepseek-r…	google/gemini-2.5-f…	google/gemma-3-12b-…	meta-llama/llama-3.…	microsoft/phi-3-med…	microsoft/phi-3.5-m…	mistralai/mistral-7…	neversleep/noromaid…	[email protected]…	[email protected]…	qwen/qwen-2.5-7b-in…	qwen/qwen3-14b	qwen/qwen3-8b
`morning-order` Bilingual Tourist Order	0.000 Details	0.825 Details	0.871 Details	0.568 Details	0.000 Details Error	0.000 Details Error	0.885 Details	0.715 Details	0.000 Details Error	0.662 Details	0.610 Details	0.773 Details	0.595 Details
`rush-hour-multitask` Soy Milk Shortage	0.755 Details	0.749 Details	0.594 Details	0.776 Details	0.000 Details Error	0.890 Details	0.907 Details	0.000 Details Error	0.000 Details Error	0.534 Details	0.637 Details	0.838 Details	0.546 Details
`youth-letter` Letter to Youth Center Teens	0.873 Details	0.468 Details	0.648 Details	0.000 Details	0.000 Details Error	0.000 Details Error	0.700 Details	0.000 Details Error	0.000 Details Error	0.750 Details	0.438 Details	0.381 Details	0.515 Details
`bikeshare-blog` Bike-Share Advocacy Post	0.000 Details	0.865 Details	0.546 Details	0.005 Details	0.000 Details	0.472 Details	0.848 Details	0.000 Details Error	0.000 Details Error	0.484 Details	0.345 Details	0.512 Details	0.629 Details

Test Scenes 4

Scene Order

Bilingual Tourist Order

ID: morning-order

🎯 Goal:

Greet the tourist warmly, help them choose a drink, and switch smoothly between Spanish and English in under 80 words.

📨 Input Events:

chat_msg customer:tourist_esp

"Hola, no sé qué pedir. ¿Alguna recomendación? It's my first time here."

Ready for Testing

Scene Order

Soy Milk Shortage

ID: rush-hour-multitask

🎯 Goal:

Acknowledge the manager, outline a quick multitask plan, and keep the response under 60 words.

📨 Input Events:

chat_msg manager:alex

"Linda, we're out of soy milk and three customers are waiting. Can you handle it?"

Ready for Testing

Scene Order

Letter to Youth Center Teens

ID: youth-letter

🎯 Goal:

Write a heartfelt letter of 150–200 words that encourages empathy, mentions sociology insights, and invites them to visit the café.

🧠 Initial State:

Pre-loaded Memories:

💭 {'kind': 'promise', 'content': 'Promised the teens a thoughtful letter about empathy and community.', 'importance': 4}

📨 Input Events:

chat_msg friend:kim

"The teens asked if you'd send them a note about empathy."

Ready for Testing

Scene Order

Bike-Share Advocacy Post

ID: bikeshare-blog

🎯 Goal:

Create a 200–250-word blog post praising bike-share and providing three actionable tips for new riders.

📨 Input Events:

chat_msg advocacy_lead:sam

"Can you draft a quick blog post encouraging more people to use the city bike-share?"

Ready for Testing

Latency by Model (This Suite)

Fastest

[email protected]/Qw… 6272 ms
p95 • avg • N 9441 ms • 6737 ms • 4
[email protected]/Qw… 10366 ms
p95 • avg • N 13648 ms • 11147 ms • 4
qwen/qwen-2.5-7b-instru… 20315 ms
p95 • avg • N 33407 ms • 22760 ms • 11
neversleep/noromaid-20b 20387 ms
p95 • avg • N 48847 ms • 23057 ms • 10
meta-llama/llama-3.1-8b… 23499 ms
p95 • avg • N 31586 ms • 23206 ms • 10

Slowest

microsoft/phi-3-medium-… 238419 ms
p95 • avg • N 283947 ms • 218144 ms • 10
microsoft/phi-3.5-mini-… 44359 ms
p95 • avg • N 140734 ms • 56456 ms • 12
deepseek/deepseek-r1-di… 33309 ms
p95 • avg • N 58671 ms • 37980 ms • 8
google/gemma-3-12b-it 30445 ms
p95 • avg • N 47699 ms • 34186 ms • 12
mistralai/mistral-7b-in… 27246 ms
p95 • avg • N 51461 ms • 31498 ms • 10

Per-scene duration for this suite.

Suite Actions

Completion Progress 100%

4 of 4 scenes completed

New Suite Import

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Export With Results

Evaluation Schema

Enhanced Framework

Version v2 ACTIVE

0 dimensions

Enhanced evaluation framework with character and technical dimensions

Top Weighted Dimensions View Details

Character Authenticity

0.182

Plan Validity

0.155

Contextual Intelligence

0.136

Recent Runs

48508023

Dec. 17, 2025, midnight

54266147

Dec. 16, 2025, midnight

45438121

Dec. 15, 2025, midnight

47294572

Dec. 14, 2025, midnight

45177558

Dec. 13, 2025, midnight

54324460

Dec. 12, 2025, midnight

47747395

Dec. 11, 2025, midnight

46449974

Dec. 10, 2025, midnight

52108215

Dec. 9, 2025, midnight

46228544

Dec. 8, 2025, midnight

Linda Navarro

Model Performance Overview

Scene Performance Matrix

Test Scenes 4

Bilingual Tourist Order

Soy Milk Shortage

Letter to Youth Center Teens

Bike-Share Advocacy Post

Latency by Model (This Suite)

Fastest

Slowest

Suite Actions

Evaluation Schema

Enhanced Framework

Recent Runs

Latency Overview (This Suite)