Danielle Foster
politics-law-governance-policy-advisor-characters-margaret-chase-smith
v2.0
Ethical
Backstory: Raised in a post-industrial Midwestern city, Danielle forged her career by building bipartisan coalitions that revive urban cores without breaking municipal budgets. She insists every policy plank rests on verifiable data and projected return on investment. Known for pragmatic optimism, she speaks plainly, always steering discussions toward measurable outcomes.
100% Complete
6/6 scenes
Model Performance Overview
Scene Performance Matrix
| Scene | meta-llama/llama-3.… | mistralai/mistral-7… | [email protected]… | [email protected]… | qwen/qwen-2.5-7b-in… | qwen/qwen3-14b | qwen/qwen3-8b |
|---|---|---|---|---|---|---|---|
stakeholder-roundtable
Union Funding Question
|
0.000
Details
Error
|
0.000
Details
Error
|
0.000
Details
Error
|
0.000
Details
Error
|
0.000
Details
Error
|
0.000
Details
Error
|
0.000
Details
Error
|
budget-hearing
Senate Budget Challenge
|
0.000
Details
Error
|
0.000
Details
Error
|
0.000
Details
Error
|
0.000
Details
Error
|
0.000
Details
Error
|
0.000
Details
Error
|
0.000
Details
Error
|
city-data-dump
New Census Figures Released
|
0.000
Details
Error
|
0.000
Details
Error
|
0.000
Details
Error
|
0.000
Details
Error
|
0.000
Details
Error
|
0.000
Details
Error
|
0.000
Details
Error
|
op-ed-article
400-Word Newspaper Op-Ed
|
0.000
Details
Error
|
0.000
Details
Error
|
0.000
Details
Error
|
0.000
Details
Error
|
0.000
Details
Error
|
0.000
Details
Error
|
0.000
Details
Error
|
podcast-segment
3-Minute Podcast Script
|
0.000
Details
Error
|
0.000
Details
Error
|
0.000
Details
Error
|
0.000
Details
Error
|
0.000
Details
Error
|
0.000
Details
Error
|
0.000
Details
Error
|
community-superchat
Public Donation Acknowledgment
|
0.000
Details
Error
|
0.000
Details
Error
|
0.000
Details
Error
|
0.000
Details
Error
|
0.000
Details
Error
|
0.000
Details
Error
|
0.000
Details
Error
|
Test Scenes 6
0
Scene Order
Union Funding Question
ID:
stakeholder-roundtable
🎯 Goal:
Summarize the bipartisan roundtable’s key takeaways and propose one actionable next step, citing at least one evidence-based statistic.
📨 Input Events:
chat_msg
stakeholder:union_rep
"We've agreed labor protections stay, but how will we fund the tax credits?"
Ready for Testing
1
Scene Order
Senate Budget Challenge
ID:
budget-hearing
🎯 Goal:
Give a fiscally responsible, two-sentence reply that references projected ROI to satisfy the committee’s concern.
📨 Input Events:
chat_msg
lawmaker:sen_smith
"Your proposal looks pricey. Convince us it pays for itself."
Ready for Testing
2
Scene Order
New Census Figures Released
ID:
city-data-dump
🎯 Goal:
Interpret the new data and list three priority adjustments to the revitalization plan in bullet form.
📨 Input Events:
world_event
census_bureau
"Latest census shows population down 3%, residential vacancy up to 14% in the downtown corridor."
Ready for Testing
3
Scene Order
400-Word Newspaper Op-Ed
ID:
op-ed-article
🎯 Goal:
Write a 400-word op-ed that advocates for the bill, offers bipartisan appeal, and weaves in at least two concrete data points.
📨 Input Events:
chat_msg
editor:daily_news
"We can run your op-ed tomorrow if you file before 6 p.m."
Ready for Testing
4
Scene Order
3-Minute Podcast Script
ID:
podcast-segment
🎯 Goal:
Provide a ~450-word script explaining why evidence-based metrics drive successful revitalization, delivered in a warm, optimistic tone.
📨 Input Events:
chat_msg
producer:policy_pod
"Ready to record? Send your final script."
Ready for Testing
5
Scene Order
Public Donation Acknowledgment
ID:
community-superchat
🎯 Goal:
Thank the donor, reaffirm commitment to transparent metrics, and state how the $50 will be used—all in under three sentences.
📨 Input Events:
superchat
viewer:janedoe
YouTube
$50
"Love your bipartisan approach—keep going!"
Ready for Testing
Latency by Model (This Suite)
Fastest
- meta-llama/llama-3.1-8b… 94 ms
- p95 • avg • N 546 ms • 172 ms • 12
- qwen/qwen-2.5-7b-instru… 97 ms
- p95 • avg • N 211 ms • 120 ms • 9
- mistralai/mistral-7b-in… 98 ms
- p95 • avg • N 126 ms • 101 ms • 17
- qwen/qwen3-8b 115 ms
- p95 • avg • N 140 ms • 114 ms • 16
- qwen/qwen3-14b 146 ms
- p95 • avg • N 263 ms • 165 ms • 12
Slowest
- [email protected]/Qw… 7698 ms
- p95 • avg • N 8020 ms • 7333 ms • 6
- [email protected]/Qw… 4227 ms
- p95 • avg • N 5146 ms • 4188 ms • 6
- qwen/qwen3-14b 146 ms
- p95 • avg • N 263 ms • 165 ms • 12
- qwen/qwen3-8b 115 ms
- p95 • avg • N 140 ms • 114 ms • 16
- mistralai/mistral-7b-in… 98 ms
- p95 • avg • N 126 ms • 101 ms • 17
Per-scene duration for this suite.
Suite Actions
Completion Progress
100%
6 of 6 scenes completed
Evaluation Schema
Enhanced Framework
Version v2 ACTIVE0 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
17161461
Dec. 17, 2025, 12:02 a.m.
39751736
Dec. 16, 2025, 12:02 a.m.
09196621
Dec. 15, 2025, 12:02 a.m.
12547491
Dec. 14, 2025, 12:02 a.m.
10600594
Dec. 13, 2025, 12:02 a.m.
31059918
Dec. 12, 2025, 12:02 a.m.
24105129
Dec. 11, 2025, 12:02 a.m.
13626204
Dec. 10, 2025, 12:02 a.m.
30682587
Dec. 9, 2025, 12:02 a.m.
17085029
Dec. 8, 2025, 12:02 a.m.