Run: 2026-09-03-01M1KREXA6E961EBCYCKSPJTNK

Run Details

Duration:
1m 2s
Cost:
$0.005250
Provider:
Fireworks

Model input

System
You are an expert novelist with a gift for vivid, immersive prose. You write in tight third-person limited point of view with a strong narrative voice. Your prose is clean, precise, and engaging — you favor strong verbs, concrete details, and natural-sounding dialogue. You will be given a story bible (codex) containing canonical details about characters, locations, items, and lore. Use these details to ground your writing in the established world. Stay consistent with the codex. Write only the prose of the scene. Do not include titles, chapter headings, markdown formatting, or any commentary before or after the scene.
User/Human
<codex> <character id="4412" name="Aurora Carter" aliases="Rory, Laila, Aurora, Carter, Malphora" pronouns="she/her" species="Human" storyRole="Protagonist"> <eyeColor>bright blue</eyeColor> <hair>straight shoulder-length black</hair> <height>5'6"</height> <age>25</age> <scar>small crescent-shaped scar on her left wrist from a childhood accident</scar> <description>Aurora, referred to by her friends as Rory, is cool-headed, intelligent, and known for quick out-of-the-box thinking.</description> <backstory>Born in Cardiff to an Irish barrister father (Brendan Carter) and Welsh teacher mother (Jennifer Carter née Ellis), Rory reluctantly pursued Pre-Law at Cardiff University. She fled to London at the behest of her childhood friend Eva after leaving an abusive ex named Evan. By day, Rory works part-time as a delivery person for Yu-Fei Cheung's Golden Empress restaurant. She lives in a flat above Silas' bar.</backstory> </character> <character id="4413" name="Silas Blackwood" aliases="Silas, Si, the Spymaster" pronouns="he/him" species="Human" storyRole="Mentor"> <eyeColor>hazel</eyeColor> <hair>grey-streaked auburn</hair> <height>6'1"</height> <age>58</age> <beard>neatly trimmed, matching his grey-streaked auburn hair</beard> <limp>slight limp in his left leg from an old knee injury</limp> <signetRing>silver signet ring, always worn on his right hand</signetRing> <description>Silas is a retired intelligence operative turned bar owner. He carries himself with quiet authority.</description> <backstory>Former MI6 field agent who retired after a botched operation in Prague left him with a permanent knee injury. He opened "The Raven's Nest" bar in Soho as a front for his network of contacts.</backstory> </character> <location id="854" name="The Raven's Nest" aliases="the Nest, Raven, Silas' bar" realm="Earth"> <signColor>distinctive green neon sign above the entrance</signColor> <secretRoom>hidden back room accessible through a bookshelf, used for clandestine meetings</secretRoom> <description>A dimly lit bar in Soho, London. The walls are covered with old maps and black-and-white photographs.</description> </location> </codex> Write a fully fleshed out scene of at least 1000 words in the literary fiction genre. Two old friends who haven't seen each other in years run into each other unexpectedly at a bar. One of them has changed significantly. Through their conversation and the tension between who they were and who they've become, reveal the weight of time and unspoken regret. Use the codex entries above as your world reference for characters and setting. Only include the prose of the scene without any markdown or commentary.

Model response

AI
The green neon over the door had buzzed since she was nineteen, a thin sickly light that cut the Soho wet to something almost soft. Aurora ducked under it with a rain-slicked satchel banging against her hip, the Golden Empress logo half peeled from the canvas. She smelled of fryer oil and the bus. The Raven’s Nest was the same as it had been when she first climbed the fire escape to her flat above it: low, warm, walls papered with maps whose creases had gone white and black-and-white photographs of men who never smiled quite right. Silas was behind the bar, wiping a glass with a cloth that had seen better decades. His auburn hair was more grey now at the temples, the neat beard still trimmed to the same line, the silver signet ring catching the amber light every time he set a glass down on the right. He limped a little more when he moved to the far end to pull a pint, the old knee twinging in the damp. “Rory,” he said, not looking up. “You’re late for your own life.” She smiled because it was the greeting they’d settled on, and because the bar was full of the low hum that let her forget she was on her feet since five. “Delivery ran long. Yu-Fei says the kitchen’s doing a new mapo tofu and the customers keep ordering it wrong.” He handed her a glass of water without asking. “You don’t have to sit here, you know.” “I like it here.” She meant it. The Nest was the only place in London that felt like it had kept some of her with it. She slid onto a stool at the far end, near the bookshelf that was always a little crooked, the one everyone knew led somewhere else if you knew the right pressure. Her hair was damp, black and straight to her shoulders, falling into her eyes. She pushed it back and caught her own reflection in the bar mirror — bright blue eyes tired at the edges, the small crescent scar on her left wrist pale against her skin where her sleeve had ridden up. A childhood accident, a kitchen drawer in Cardiff. She had told Silas once, when she was new and scared and he’d asked why she kept checking the lock three times. That was when the bell over the door chimed and the rain followed someone in. Aurora didn’t turn right away. She was used to the regulars. She was used to the way the bar smelled after rain. Then a voice said, “You still take it with two sugars?” It was too familiar and not familiar enough. Aurora turned. Eva was standing under the neon’s spill, shaking water from a coat that was too thin for October. She was shorter than Aurora remembered, or Aurora had grown into herself. Her hair was cut blunt at her jaw, dyed a dark auburn that didn’t suit her. There were lines at her mouth that weren’t there at twenty. The easy laugh was gone, replaced by something careful. Aurora’s fingers tightened around the glass. She was cool-headed by reputation, quick with an out-of-the-box answer when the delivery scooter broke down or Yu-Fei was short-staffed. Now her throat felt dry. “Eva.” Eva smiled, the same crooked smile, and then it faltered as she really looked at Aurora. “Rory. God. It’s you.” Silas watched them both from behind the bar, his hazel eyes steady. He set down the cloth. They moved as if to each other and then stopped, the space between the bar stools suddenly too wide. Ten years, maybe. Since Cardiff. Since the night Aurora had packed a duffel bag, left Pre-Law mid-term, left Brendan Carter’s house with the barrister father who never quite understood why she wouldn’t stay, left Jennifer Ellis Carter who had cried into the phone for weeks. She’d come to London because Eva had said, come, there’s a room, there’s work. Eva had been the one to book the train. “I didn’t know you were in London,” Aurora said. “I’m not really,” Eva said. “I’m here for a deposition. Work sent me.” She looked down at her hands. “I’m a solicitor now. In Cardiff. Family law.” Aurora laughed, a short sound. “You always said you’d never do law.” “I said a lot of things.” Eva slid onto the stool next to her, careful not to bump the satchel. “You look good. Tired, but good.” “You look… different.” It was the truth and it sounded cruel. Eva’s jaw tightened. “I’ve been different for a while.” Silas poured two whiskies without asking and set them down. He didn’t sit. He rested his right hand on the bar, the signet ring glinting. Aurora didn’t touch hers at first. She studied Eva the way she studied a delivery address she didn’t trust. The clothes were expensive, pressed. The hands were bare, no rings. The eyes were the same, but there was a hardness around them. “You remember the flat on Cathedral Road?” Eva asked softly. “The one with the busted radiator?” Aurora did. She remembered the nights they’d studied together, Eva quizzing her on torts while Aurora made tea with too much sugar. She remembered Eva bringing her home after Evan had... she remembered not telling anyone. She remembered Eva saying, stay with me in London, you don’t have to go back. “I remember,” Aurora said. “I meant it,” Eva said. “I thought it would be different here. For you. For us.” Aurora felt the old familiar click of her mind working, finding angles. “It is different.” Eva shook her head. “Not for me. I stayed. Mummy got sick. Da got worse. I took the pupillage they offered and it swallowed me whole. You got out.” The words landed like a slap, quiet and precise. Aurora had never told Eva about Evan’s name, about the abuse, about the crescent scar that wasn’t from a kitchen drawer at all, not really. She’d told Silas, in pieces, when she first moved in upstairs and he’d caught her crying over the sink at two a.m. “I didn’t get out,” Aurora said. “I just moved.” Eva reached out, then stopped. “I’m sorry. I should have—” “You should have what?” Aurora’s voice stayed even. “Called more? I didn’t give you a number for two years.” “I was scared you’d hate me.” Aurora looked at her wrist. The scar caught the light. “I didn’t. I just didn’t know how to say thank you without crying.” Silence settled between them, the bar noise folding around it. Silas polished a glass, the limp in his left leg betraying him when he shifted his weight. “You still work deliveries?” Eva asked. “Part-time. Yu-Fei’s restaurant. It pays rent.” Aurora shrugged. “I’m saving. Maybe I’ll go back to school. Or not.” Eva’s mouth twisted. “You were going to be a barrister, Rory. You were going to make your da proud.” Aurora had never wanted to make Brendan proud. She’d wanted to be safe. She’d wanted to stop being the girl who flinched at loud voices. “I’m proud of you,” she said, and it surprised her how true it felt. “Family law. That’s good work.” Eva’s eyes filled. She blinked it back. “You haven’t changed much. Still cool as ice.” “Still you,” Aurora said. “Still saying things you don’t mean and then meaning them later.” Eva laughed, wetly. She picked up the whisky and drank. “Do you ever think about Cardiff?” “Every time it rains.” They sat like that for a while, two women who had once shared a bed in a flat with a busted radiator and now sat on opposite sides of a bar in Soho, the city humming under them. The weight of time was in the small things: Eva’s cut hair, Aurora’s delivery satchel, the scar on Aurora’s wrist, the way Eva’s coat didn’t quite close. “I should go,” Eva said finally. “I have a train.” Aurora nodded. “Let me walk you out.” They stood. Eva hesitated at the door, the green neon painting her face. “If you ever want to talk, really talk. My number’s the same.” “I know,” Aurora said. “It’s been in my phone the whole time.” Eva nodded once, a small, regretful movement, and disappeared into the rain. Silas was still at the bar when Aurora returned. He slid her glass of water toward her. “You didn’t drink it,” he said. “I wasn’t thirsty.” He looked at her for a long moment, the retired operative in him cataloguing nothing, just seeing her. “You’re good at keeping the lid on.” Aurora smiled, tired. “I’m learning when to take it off.” He lifted his glass in a small salute. The maps on the wall creaked as the old building settled. Above them, her flat waited, quiet and warm. Outside, London kept moving, indifferent and kind in the way only a city could be.
created_at"2026-09-03T13:48:45.779Z" 9/3/2026, 1:48:45 PM
model"meta/muse-glimmer-30b-20260810"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency204
moderation_latency(null)
generation_time61915
tokens_prompt846
tokens_completion3699
native_tokens_prompt832
native_tokens_completion3306
native_tokens_completion_images(null)
native_tokens_reasoning1491
native_tokens_cached0
num_media_prompt(null)
num_input_audio_prompt(null)
num_media_completion0
num_search_results(null)
num_fetches(null)
web_search_engine(null)
origin"https://ncbench.com/"
is_byokfalse
finish_reason"stop"
native_finish_reason"stop"
service_tier(null)
usage0.0052502
router(null)
user_agent"langchainjs-openai/1.0.0 ((node/v24.19.0; linux; x64))"
http_referer(null)
request_id"req-1788443325-VoMf3SIgdnFmt830NGDb"
session_id(null)
preset_id(null)
api_type"completions"
id"gen-1788443325-xuQzZ8NtmPIjJKiH0AqN"
upstream_id"chatcmpl-chatcmpl-c4247557805b47c886cd008e8309cd0d"
provider_responses
0
endpoint_id"38b85376-97ef-4ae3-b2f4-b23ca1ee2495"
id"chatcmpl-chatcmpl-c4247557805b47c886cd008e8309cd0d"
is_byokfalse
latency56
model_permaslug"meta/muse-glimmer-30b-20260810"
provider_name"Fireworks"
status200
total_cost0.0052502
cache_discount(null)
upstream_inference_cost0
provider_name"Fireworks"
response_cache_source_id(null)
data_region"global"
workspace_id"97e315e5-d303-487d-83c1-83180e8a13d4"

Evaluation details

Result Evaluator Details Meta Data
100.00% Adverbs in dialogue tags
Target: ≤10% dialogue tags with adverbs
totalTags20
adverbTagCount2
adverbTags
0"Eva asked softly [softly]"
1"Eva said finally [finally]"
dialogueSentences52
tagDensity0.385
leniency0.769
rawRatio0.1
effectiveRatio0.077
79.78% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount1484
totalAiIsmAdverbs6
found
0
adverb"really"
count4
1
adverb"suddenly"
count1
2
adverb"softly"
count1
highlights
0"really"
1"suddenly"
2"softly"
100.00% AI-ism character names
Target: 0 AI-default names (16 tracked, −20% each)
codexExemptions
0"Blackwood"
found(empty)
100.00% AI-ism location names
Target: 0 AI-default location names (33 tracked, −20% each)
codexExemptions(empty)
found(empty)
76.42% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount1484
totalAiIsms7
found
0
word"familiar"
count3
1
word"glinting"
count1
2
word"silence"
count1
3
word"weight"
count2
highlights
0"familiar"
1"glinting"
2"silence"
3"weight"
100.00% Cliché density
Target: ≤1 cliche(s) per 800-word window
totalCliches0
maxInWindow0
found(empty)
highlights(empty)
100.00% Emotion telling (show vs. tell)
Target: ≤3% sentences with emotion telling
emotionTells0
narrationSentences105
matches(empty)
100.00% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount0
hedgeCount0
narrationSentences105
filterMatches(empty)
hedgeMatches(empty)
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences137
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
repeatedSegmentCount0
maxSentenceWordsSeen45
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans0
markdownWords0
totalWords1485
ratio0
matches(empty)
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions21
unquotedAttributions0
matches(empty)
0.00% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions84
wordCount1147
uniqueNames18
maxNameDensity2.44
worstName"Aurora"
maxWindowNameDensity6
worstWindowName"Eva"
discoveredNames
Soho2
Golden1
Empress1
Raven1
Nest2
London4
Cardiff2
Silas7
October1
Aurora28
Yu-Fei1
Pre-Law1
Brendan2
Carter2
Jennifer1
Ellis1
Eva25
Evan2
persons
0"Raven"
1"Silas"
2"Aurora"
3"Brendan"
4"Carter"
5"Jennifer"
6"Ellis"
7"Eva"
8"Evan"
places
0"Soho"
1"London"
2"Cardiff"
globalScore0.279
windowScore0
100.00% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences65
glossingSentenceCount1
matches
0"felt like it had kept some of her with"
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches0
per1kWords0
wordCount1485
matches(empty)
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount0
totalSentences137
matches(empty)
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs58
mean25.6
std24.58
cv0.96
sampleLengths
054
1119
212
350
417
526
6114
715
822
911
1010
1166
1231
131
1420
1517
1687
179
1827
1912
2026
2111
229
2325
2442
2516
2651
274
2816
2915
3029
3156
329
3310
3419
356
3623
3727
386
3918
4019
4144
4215
4315
4416
454
4665
4710
487
4925
95.24% Passive voice overuse
Target: ≤2% passive sentences
passiveCount3
totalSentences105
matches
0"was used"
1"was used"
2"was gone"
100.00% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount1
totalVerbs215
matches
0"was standing"
100.00% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount1
semicolonCount0
flaggedSentences1
totalSentences137
ratio0.007
matches
0"She pushed it back and caught her own reflection in the bar mirror — bright blue eyes tired at the edges, the small crescent scar on her left wrist pale against her skin where her sleeve had ridden up."
100.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount1154
adjectiveStacks0
stackExamples(empty)
adverbCount41
adverbRatio0.03552859618717504
lyAdverbCount9
lyAdverbRatio0.00779896013864818
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences137
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences137
mean10.84
std8.38
cv0.773
sampleLengths
025
121
28
343
416
537
623
76
86
931
1019
119
128
137
1419
1531
1614
1739
188
1922
2015
215
226
2311
2411
258
262
2718
2812
2916
3011
319
326
3320
345
351
3616
374
3812
395
4019
413
422
4340
4414
459
469
475
4814
498
36.13% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats19
diversityRatio0.24087591240875914
totalSentences137
uniqueOpeners33
37.04% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount1
totalSentences90
matches
0"Then a voice said,"
ratio0.011
46.67% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount39
totalSentences90
matches
0"She smelled of fryer oil"
1"His auburn hair was more"
2"He limped a little more"
3"he said, not looking up"
4"She smiled because it was"
5"He handed her a glass"
6"She meant it"
7"She slid onto a stool"
8"Her hair was damp, black"
9"She pushed it back and"
10"She had told Silas once,"
11"She was used to the"
12"She was used to the"
13"It was too familiar and"
14"She was shorter than Aurora"
15"Her hair was cut blunt"
16"She was cool-headed by reputation,"
17"He set down the cloth."
18"They moved as if to"
19"She’d come to London because"
ratio0.433
4.44% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount82
totalSentences90
matches
0"The green neon over the"
1"Aurora ducked under it with"
2"She smelled of fryer oil"
3"The Raven’s Nest was the"
4"Silas was behind the bar,"
5"His auburn hair was more"
6"He limped a little more"
7"he said, not looking up"
8"She smiled because it was"
9"He handed her a glass"
10"She meant it"
11"The Nest was the only"
12"She slid onto a stool"
13"Her hair was damp, black"
14"She pushed it back and"
15"A childhood accident, a kitchen"
16"She had told Silas once,"
17"That was when the bell"
18"Aurora didn’t turn right away."
19"She was used to the"
ratio0.911
55.56% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount1
totalSentences90
matches
0"Now her throat felt dry."
ratio0.011
59.80% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences43
technicalSentenceCount5
matches
0"The green neon over the door had buzzed since she was nineteen, a thin sickly light that cut the Soho wet to something almost soft."
1"She slid onto a stool at the far end, near the bookshelf that was always a little crooked, the one everyone knew led somewhere else if you knew the right pressu…"
2"Eva was standing under the neon’s spill, shaking water from a coat that was too thin for October."
3"Her hair was cut blunt at her jaw, dyed a dark auburn that didn’t suit her."
4"Since the night Aurora had packed a duffel bag, left Pre-Law mid-term, left Brendan Carter’s house with the barrister father who never quite understood why she …"
100.00% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags20
uselessAdditionCount1
matches
0"he said, not looking up"
100.00% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags14
fancyCount0
fancyTags(empty)
dialogueSentences52
tagDensity0.269
leniency0.538
rawRatio0
effectiveRatio0
83.0358%