Run: 2026-09-03-01M1KS2SN6664QADEDQZKY8BWQ

Run Details

Duration:
1m
Cost:
$0.003827
Provider:
DeepInfra

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 sign over the door buzzed and threw a thin wash of light across the wet pavement. It was the kind of rain that didn't settle, just kept spitting, cold enough to find the seams in Aurora's jacket. She'd been on her bike since six, three orders for the Golden Empress, the last one to a flat in Fitzrovia where the woman tipped her with a folded ten and asked her not to ring the bell. Her legs ached from the pedals and her gloves were damp at the fingertips. She pushed into The Raven's Nest because it was warm and because the flat above was quiet in a way that made her think too much. The bell over the door gave a soft chime. Inside, the bar was low and amber. The walls were papered with old maps and black-and-white photographs, faces half-faded, a city of ghosts in frames. The smell of beer and polish and something faintly metallic from the kitchen behind the bar. Silas was behind it, polishing a pint glass with a cloth that had been white once. He didn't look up at first. Grey-streaked auburn hair pulled back, beard neatly trimmed, same as always. The silver signet ring caught the light on his right hand as he turned the glass. He had a slight limp when he moved, a hitch in his left leg from Prague, and even at the bar he stood with that quiet authority that had made her nervous the first night she’d been let up the back stairs. Aurora had lived above him for nearly three years. She knew the hours he opened, the way he took his whisky, the nights he didn’t come down at all. She had not spoken to him in eleven months. He saw her then. His hazel eyes found her and held for a beat longer than politeness required. “Rory,” he said, as if he’d been expecting her and hadn’t at the same time. She shrugged off her jacket, shook rain from her hair. It was straight, shoulder-length, black, plastered to her neck. “Si,” she said. The name felt small in her mouth. She used to call him Silas when she was scared, Si when she wasn’t. He set the glass down. “You’re late for rent.” She smiled, quick and cool. “It’s the third. I’m early.” He studied her. She was twenty-five now, five-six in the worn boots she wore for deliveries, bright blue eyes tired under the bar lights. A small crescent-shaped scar on her left wrist caught the light when she tucked her hands into her pockets. She’d told him once, after a night when Evan had followed her to the flat, that it was from a childhood accident. He’d never asked which childhood. “You’re wet,” he said. “I’m always wet.” She looked around. Two men at the far end, a woman reading at the corner table. The usual. “It’s quiet.” “Tuesday.” She stepped up to the bar, rested her forearms on it. The wood was worn smooth by hands. “Can I get a half-pint? I’ve got to be up.” He nodded, reached for a glass. His movements were unhurried. “You still doing the restaurant?” “Yu-Fei’s. Part-time. Delivery.” “Pre-law was a waste then.” “It was a waste before I left Cardiff.” She said it lightly, but the old bitterness was there. Brendan Carter would have been furious. Jennifer would have cried. She could still feel the kitchen in the flat above him, the way she’d sat at the table after leaving Evan and counted the bruises she didn’t have that week and felt guilty for counting them. Silas poured. He didn’t pour for himself. “You left Eva’s last Christmas and haven’t been back,” he said. She blinked. “You talk to Eva?” “I don’t need to. She tells me things.” He slid the glass toward her. “She’s worried you’re using the job as an excuse to disappear.” Aurora picked up the glass with her right hand. Her left stayed in her pocket, fingers tracing the scar. “I’m not disappearing. I’m working.” “You’re working the same circuit you were when you arrived. Golden Empress, the Nest, the flat. You’re a radius, Rory.” The words landed with a precision that was infuriating because it was true. She was cool-headed, intelligent, quick with out-of-the-box thinking, all the things she’d told herself made her good at navigating Soho on a bike in rain. But the radius was real. “I’m fine,” she said. He didn’t argue. He watched her drink. The limp was visible now as he shifted his weight to reach for a towel behind him. The bar was his front, and the front was always clean. She remembered the first time he’d let her in through the back, after she’d shown up at Eva’s with a suitcase and no plan. He’d been different then, less settled. He’d offered her the flat above without asking for a reference, just a look at her wrist and a question about Cardiff. She’d thought he was a landlord. She’d learned later he was a network. “You never asked why I stayed,” he said quietly. “I assumed you liked rent.” He gave a short, dry laugh. “I liked having someone up there who knew when to be quiet.” She felt the old flush rise in her cheeks. “I’m quiet.” “No. You’re still listening.” The bar door opened again, bringing in a gust of wet air and a man with a newspaper under his arm. Silas’s expression didn’t change. When the man was seated, Silas turned back to her. “You haven’t been down since the night he came in,” he said. She set the glass down harder than she meant to. “Evan’s not here.” “No. He’s not. You are.” They had a history that neither named. The night Evan had come to Soho, drunk and loud, asking where she lived. Silas had been at the bar, had closed early, had told her to go up the back stairs and stay there until morning. She’d watched from the window as Silas talked to him on the street, calm, his signet ring glinting. Evan had left. She’d never thanked him properly. She’d stopped coming down after that, as if proximity would invite another night. “I didn’t want to make it a thing,” she said now. “It was already a thing.” Silas picked up another glass, started polishing again. The cloth made a soft shushing sound. She could see the maps behind him, the Thames looping through London in ink. She thought about the bookshelf at the end of the bar, the one that didn’t quite line up with the others, the hidden back room she knew existed because she’d once heard a low voice through the floorboards at two in the morning. “You’re still running,” he said, not unkindly. “Just a smaller loop.” Aurora felt the weight of it, the years compressed into that sentence. She had fled Cardiff for London, left Pre-Law, left Evan, left the life her parents expected. She had thought London would be a new map. Instead she’d drawn a tight circle around a bar and a flat and a restaurant and a bike. “I’m thinking about going back,” she lied. Silas didn’t blink. “To Cardiff?” “To school.” He set the cloth down. “You were good at it. You still are. You solve problems in ways I don’t see coming.” She looked at him, this man with the quiet authority and the old knee injury and the bar that was a front for things she never asked about. He had been a mentor without ever saying the word. He had given her a roof when she had nothing else. And she had repaid him with absence. “I’m sorry,” she said, and the words surprised her with how easily they came. “For not saying thank you. For not… coming down.” He studied her for a long moment, then nodded once, a small movement that felt like absolution. “You’re welcome up any time, Rory.” She picked up her jacket, felt the rain still clinging to the sleeves. “I’ll pay rent on time.” “I know.” She turned to go, paused at the door where the green neon buzzed against the wet glass. “Do you ever miss Prague?” He smiled, just at the corner of his mouth. “Every day. I miss being able to walk.” She didn’t answer that. She pushed the door open and the bell chimed behind her. The rain was still falling, but she walked into it without pulling her collar up.
created_at"2026-09-03T13:59:37.397Z" 9/3/2026, 1:59:37 PM
model"meta/muse-glimmer-30b-20260810"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency238
moderation_latency(null)
generation_time60000
tokens_prompt846
tokens_completion3522
native_tokens_prompt832
native_tokens_completion3120
native_tokens_completion_images(null)
native_tokens_reasoning1449
native_tokens_cached640
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)
usage0.0038272
router(null)
user_agent"langchainjs-openai/1.0.0 ((node/v24.19.0; linux; x64))"
http_referer(null)
request_id"req-1788443977-Dp8OcDCgaKpYi8wFDlfk"
session_id(null)
preset_id(null)
api_type"completions"
id"gen-1788443977-DsNEb2C0aJP0AMy9Zrsd"
upstream_id"chatcmpl-RYljyAJp6ApHanUrNJzQUqPF"
provider_responses
0
endpoint_id"a9912acb-568e-4147-8ed3-5d20aea22135"
id"chatcmpl-RYljyAJp6ApHanUrNJzQUqPF"
is_byokfalse
latency72
model_permaslug"meta/muse-glimmer-30b-20260810"
provider_name"DeepInfra"
status200
total_cost0.0038272
cache_discount0.0001664
upstream_inference_cost0
provider_name"DeepInfra"
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
totalTags14
adverbTagCount2
adverbTags
0"She looked around [around]"
1"he said quietly [quietly]"
dialogueSentences43
tagDensity0.326
leniency0.651
rawRatio0.143
effectiveRatio0.093
96.48% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount1421
totalAiIsmAdverbs1
found
0
adverb"lightly"
count1
highlights
0"lightly"
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)
82.41% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount1421
totalAiIsms5
found
0
word"tracing"
count1
1
word"navigating"
count1
2
word"weight"
count2
3
word"glinting"
count1
highlights
0"tracing"
1"navigating"
2"weight"
3"glinting"
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
emotionTells2
narrationSentences104
matches
0"was scared"
1"felt guilty"
100.00% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount1
hedgeCount0
narrationSentences104
filterMatches
0"think"
hedgeMatches(empty)
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences133
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
repeatedSegmentCount0
maxSentenceWordsSeen43
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans0
markdownWords0
totalWords1421
ratio0
matches(empty)
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions22
unquotedAttributions0
matches(empty)
83.33% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions38
wordCount1182
uniqueNames19
maxNameDensity0.76
worstName"Silas"
maxWindowNameDensity2.5
worstWindowName"Silas"
discoveredNames
Aurora4
Golden1
Empress1
Fitzrovia1
Raven1
Nest1
Prague1
Silas9
Si1
Evan5
Two1
Brendan1
Carter1
Soho2
Eva1
Cardiff2
Thames1
London3
Pre-Law1
persons
0"Aurora"
1"Silas"
2"Evan"
3"Brendan"
4"Carter"
5"Eva"
places
0"Fitzrovia"
1"Raven"
2"Prague"
3"Two"
4"Soho"
5"Cardiff"
6"Thames"
7"London"
globalScore1
windowScore0.833
82.43% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences74
glossingSentenceCount2
matches
0"quite line up with the others, the hidden back room she knew existed because she’d once heard a low voice through the floorboards at two in the morning"
1"felt like absolution"
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches0
per1kWords0
wordCount1421
matches(empty)
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount1
totalSentences133
matches
0"have that week"
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs53
mean26.81
std26.6
cv0.992
sampleLengths
092
176
291
338
433
543
69
710
870
94
1023
111
1228
1315
143
155
1664
177
1811
196
2025
2124
2220
2343
244
25100
269
275
2818
2911
304
3135
3212
3313
345
3583
3611
375
3872
3911
4055
417
425
432
4422
4556
4623
4723
4818
492
98.52% Passive voice overuse
Target: ≤2% passive sentences
passiveCount2
totalSentences104
matches
0"were papered"
1"were unhurried"
100.00% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount1
totalVerbs210
matches
0"was still falling"
100.00% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount0
semicolonCount0
flaggedSentences0
totalSentences133
ratio0
matches(empty)
94.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount1192
adjectiveStacks1
stackExamples
0"small crescent-shaped scar"
adverbCount39
adverbRatio0.03271812080536913
lyAdverbCount9
lyAdverbRatio0.007550335570469799
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences133
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences133
mean10.68
std8
cv0.748
sampleLengths
019
121
238
314
426
59
67
718
816
916
106
1111
1216
1342
149
1520
169
174
1814
1915
2010
219
223
237
2414
255
264
275
285
293
3021
3119
3222
335
344
356
3613
372
382
391
4011
417
4210
436
444
455
463
475
4818
496
40.23% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats13
diversityRatio0.2556390977443609
totalSentences133
uniqueOpeners34
35.09% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount1
totalSentences95
matches
0"Instead she’d drawn a tight"
ratio0.011
0.00% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount62
totalSentences95
matches
0"It was the kind of"
1"She'd been on her bike"
2"Her legs ached from the"
3"She pushed into The Raven's"
4"He didn't look up at"
5"He had a slight limp"
6"She knew the hours he"
7"She had not spoken to"
8"He saw her then."
9"His hazel eyes found her"
10"he said, as if he’d"
11"She shrugged off her jacket,"
12"It was straight, shoulder-length, black,"
13"She used to call him"
14"He set the glass down."
15"She smiled, quick and cool."
16"He studied her."
17"She was twenty-five now, five-six"
18"She’d told him once, after"
19"He’d never asked which childhood."
ratio0.653
0.00% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount88
totalSentences95
matches
0"The green neon sign over"
1"It was the kind of"
2"She'd been on her bike"
3"Her legs ached from the"
4"She pushed into The Raven's"
5"The bell over the door"
6"The walls were papered with"
7"The smell of beer and"
8"Silas was behind it, polishing"
9"He didn't look up at"
10"The silver signet ring caught"
11"He had a slight limp"
12"Aurora had lived above him"
13"She knew the hours he"
14"She had not spoken to"
15"He saw her then."
16"His hazel eyes found her"
17"he said, as if he’d"
18"She shrugged off her jacket,"
19"It was straight, shoulder-length, black,"
ratio0.926
0.00% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount0
totalSentences95
matches(empty)
ratio0
99.13% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences49
technicalSentenceCount3
matches
0"Silas was behind it, polishing a pint glass with a cloth that had been white once."
1"He had a slight limp when he moved, a hitch in his left leg from Prague, and even at the bar he stood with that quiet authority that had made her nervous the fi…"
2"The words landed with a precision that was infuriating because it was true."
17.86% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags14
uselessAdditionCount3
matches
0"he said, as if he’d been expecting her and hadn’t at the same time"
1"he said, not unkindly"
2"she said, and the words surprised her with how easily they came"
100.00% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags12
fancyCount1
fancyTags
0"she lied (lie)"
dialogueSentences43
tagDensity0.279
leniency0.558
rawRatio0.083
effectiveRatio0.047
80.9822%