Run: 2026-09-03-01M1K4WWJ181ZEBX4C3RS6GTDJ

Run Details

Duration:
2m 8s
Cost:
$0.047685
Provider:
Meta

Evaluation summary

Score Evaluator
Details Link
100.00% Matches word count (details)
100.00% Dialogue to Total Word Ratio (details)
100.0000% Overall

Model input

User/Human
You are a author of comedic heist books. Please write a 500 word scene that has 50% words of dialogue between two thieves named Molly and Bill who are planning to break into a children's party to steal all the presents. Only include the prose of the scene without any markdown or commentary.

Model response

AI
The van smelled like old fries and bad decisions as Molly spread the birthday party map across the dashboard. Bill chewed a red licorice rope and studied the suburban house with professional disappointment. Stealing presents from a six year old felt low even for them. Rain tapped the windshield while a dog barked at distant inflatable castles. Molly tapped a pink X marking the gift table. They needed a flawless plan before Saturday afternoon chaos began. "We hit the party at three when parents get distracted" said Molly. Bill groaned and wiped sugar from his stolen uniform. "Bill, kids parties have cake and screaming tiny witnesses everywhere" said Molly. He grinned, unfazed by moral complications or frosting. "Relax, Molly, I brought earplugs and extra large bags today" said Bill. Molly narrowed her eyes at the clown poster taped nearby. "Great, genius, how do we get past the clown huh?" said Molly. "Easy, I paid him twenty bucks to take lunch early" said Bill. Thunder rumbled as neighborhood kids practiced screaming with impressive lung capacity. "You bribed Bozo? What if he squeals to moms then?" said Molly. "He will not, he owes me from poker night yesterday" said Bill. Molly drummed fingers on steering wheel, calculating risk versus reward. "Fine, what about the birthday kid expecting presents tomorrow morning?" said Molly. "Kids forget fast, especially with sugar and bouncy castles around" said Bill. She snorted and checked the list of registered gifts online. "Heartless, I love it, but security camera by door though?" said Molly. "Covered, I will wear my dinosaur costume to hide everything" said Bill. Bill pulled the scaly green suit from backseat with pride. "Of course, nothing suspicious about a grown dinosaur sweating hard" said Molly. Sweat already stained the armpits from last Halloween casino job. "You dress as princess, kids trust tiaras and glitter always" said Bill. "I am not wearing pink tulle for cheap plastic toys" said Molly. Bill waved a printed eBay listing showing soaring resale prices. "These are premium LEGOs, worth serious cash on eBay now" said Bill. "Okay fine, but I get the big unicorn box first" said Molly. They shook on it, thieves honor among sticky fingered opportunists. "Deal, you distract parents while I grab gift table quickly" said Bill. "How? Juggle juice boxes? Sing Baby Shark loudly for hours?" said Molly. Bill tapped his temple, grinning widely. "Better, pretend you lost your own crying child somewhere outside" said Bill. "Dark, Bill, but parents will stampede to help instantly then" said Molly. Outside the van, balloons bobbed and a magician vanished awkwardly. "Exactly sixty seconds to load presents into van outside quietly" said Bill. "What if the kids chase us demanding their loot back?" said Molly. Bill opened a bulk bag of candy with tactical seriousness. "Throw gummy bears behind us like tiny delicious caltrops fast" said Bill. "You thought of everything, except getaway music playlist needed dude" said Molly. "Already made, Yakety Sax for maximum comedic sprinting effect baby" said Bill.
created_at"2026-09-03T08:06:52.231Z" 9/3/2026, 8:06:52 AM
model"meta/muse-spark-1.3-20260902"
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external_user(null)
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cancelledfalse
latency3296
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tokens_prompt75
tokens_completion789
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native_tokens_completion11200
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native_tokens_reasoning10494
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num_media_completion0
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is_byokfalse
finish_reason"stop"
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usage0.047685
router(null)
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provider_responses
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is_byokfalse
latency939
model_permaslug"meta/muse-spark-1.3-20260902"
provider_name"Meta"
status200
total_cost0.047685
cache_discount(null)
upstream_inference_cost0
provider_name"Meta"
response_cache_source_id(null)
data_region"global"
workspace_id"97e315e5-d303-487d-83c1-83180e8a13d4"

Evaluation details

Result Evaluator Details Meta Data
100.00% Matches word count n/a
neededCleanfalse
words500
100.00% Dialogue to Total Word Ratio
Ratio: 50.00%, Deviation: 0.00%
neededCleanfalse
wordsTotal500
wordsDialogue250
100.0000%