Run: 2026-09-03-01M1KS2H2KYAGPD0A35A0FZ832

Run Details

Duration:
37.3s
Cost:
$0.002785
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="4416" name="Detective Harlow Quinn" aliases="Quinn, Detective Quinn, Harlow" pronouns="she/her" species="Human" storyRole="Antagonist"> <eyeColor>brown</eyeColor> <hair>closely cropped salt-and-pepper</hair> <height>5'9"</height> <age>41</age> <jawline>sharp jaw</jawline> <watch>worn leather watch on her left wrist</watch> <bearing>military precision</bearing> <description>A Metropolitan Police detective with 18 years of decorated service who suspects the clique is involved in criminal activity.</description> <backstory>She lost her partner, DS Morris, during a case three years ago under unexplained circumstances that had supernatural origins she doesn't yet understand.</backstory> </character> <character id="4417" name="Tomás Herrera" aliases="Tommy, Tomás, Herrera" pronouns="he/him" species="Human" storyRole="Support"> <eyeColor>warm brown</eyeColor> <hair>short curly dark brown</hair> <height>5'10"</height> <age>29</age> <skinTone>olive skin</skinTone> <scar>scar running along his left forearm from a knife attack</scar> <medallion>Saint Christopher medallion around his neck</medallion> <birthplace>Seville, Spain</birthplace> <description>A former paramedic who provides off-the-books medical care for the clique.</description> <backstory>Born in Seville, Spain. He moved to London to work for the NHS but lost his license after administering unauthorized treatments to supernatural patients.</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> <location id="856" name="The Veil Market" aliases="Veil Market, the Market, underground market" realm="Earth"> <currentLocation>abandoned Tube station beneath Camden</currentLocation> <entryRequirement>bone token</entryRequirement> <schedule>moves locations every full moon</schedule> <description>A hidden supernatural black market that sells enchanted goods, banned alchemical substances, and information.</description> </location> </codex> Write a fully fleshed out scene of at least 1000 words in the thriller genre. A detective is pursuing a suspect through rain-soaked city streets at night. The chase takes them from the street level down into an underground market. The detective must decide whether to follow the suspect into unfamiliar and potentially dangerous territory. 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
Rain came down hard off Shaftesbury Avenue, hammering the awnings and turning the pavement into a black mirror. Detective Harlow Quinn kept her coat collar up and her stride even, military precision in the way she moved through the crowd, head down, eyes up. The Raven's Nest had been empty when she left it twenty minutes ago. Not empty the way a closed bar is empty. Empty the way a room is emptied fast. Green neon still buzzed above the door, bleeding its color onto the wet street, and the old maps on the walls inside were still tacked up, still creased from years of handling. No one at the bar. Just a single glass left on the table where the suspect had been sitting, and the bookshelf by the back room had been nudged an inch out of line. She had him. Tomás Herrera. Short curly dark brown hair damp now, olive skin slick with rain, the Saint Christopher medallion catching the streetlight as he ran. The scar on his left forearm showed white through his sleeve when he broke into a sprint past the shuttered bookshop. Quinn didn't call it in. She didn't want a uniform in the Nest, didn't want the name logged. She followed. He knew the streets. Soho at night was a maze of alleys and service roads, and he used them. He cut down a narrow passage between two buildings, ducked under a fire escape, and came out onto a side street that stank of diesel and drain. Quinn's leather watch on her left wrist was soaked through, the strap dark with water, but the second hand kept its steady tick. Eighteen years of service taught her to count that. Three years since Morris had gone down in a flat in Whitechapel with a wound that shouldn't have killed him that fast and a story that wouldn't hold. She still didn't know what had taken him. She just knew she wasn't going to lose another one because she hesitated. Tomás looked back once. Warm brown eyes, startled, not afraid. That was worse. He wasn't panicking. He was checking the gap. She closed it. He hit Camden Lock Road at a dead run, weaving through tourists with umbrellas and delivery bikes. Rain plastered her hair to her scalp, the salt-and-pepper cropped close to her skull. Her sharp jaw was set. The medallion swung against his chest with each step. He didn't go for a cab. He went down. Camden Underground. The station had been shut for a decade, the tiled entrance choked with weeds and a rusted iron gate. A sign, half-peeled, warned of no entry. Tomás slipped through a gap in the fencing, dropped to a concrete stairwell slick with algae, and vanished down. Quinn stopped at the top of the stairs. Cold rose from below, different from the rain. It carried a faint metallic tang and the low thrum of something alive, like a generator running too far underground. She could hear water dripping, a steady metronome in the dark. Her radio was silent in her pocket. No signal down here. The detective's hand went to her belt, then stopped. She had a warrant for the Nest, for questioning Herrera about off-the-books medical care, for the clique he was rumored to run with, for missing persons who'd been traced to a back room behind a bookshelf. She had nothing for this. She should call it in. She should wait for forensics, for backup, for a proper entry team. Military precision demanded procedure. Tomás was down there. The steps were narrow and the rain made them treacherous. She took them one at a time, testing each with her boot. The walls were damp brick, covered in old graffiti that had been painted over and painted over again until the surface looked bruised. The air got thicker, heavier. Somewhere far below, a bell chimed once, low and resonant. The tunnel opened into the shell of a disused Tube platform. It was not abandoned. Stalls lined the curved wall, low tables lit by lanterns that burned without smoke. Figures moved between them, cloaked and uncloaked, trading in things that shouldn't be sold. She could see the glint of glass vials filled with liquid that moved on its own, a stack of bound ledgers with wax seals, a woman holding out a bone token the size of a thumbnail to a man who examined it with a loupe. The Veil Market. She'd heard the name in a file that never made it past her desk, a whisper from a source who'd been killed in custody. It moved every full moon. It required a bone token for entry. It sold enchanted goods, banned alchemical substances, information. It was a myth, until now. Tomás was at a stall near the far end, talking to a vendor with a scarred face. He wasn't running anymore. He was negotiating. His left forearm was visible, the knife scar pale against his skin, and he was holding something out in his palm, something small and white. Quinn stepped out of the shadows onto the platform. The lantern light caught the rain still dripping from her coat. Several heads turned. No one drew a weapon. That was worse. They watched her with the calm curiosity of people who had seen police before and knew how to deal with them. Tomás saw her and froze. His eyes widened just a fraction. The medallion swung. "Detective," he said, quietly, as if they were still in the Nest. "You shouldn't be here." She kept her hands visible. "Tomás Herrera. You left the Raven's Nest in a hurry. I'd like to know why." A man at the next stall laughed, soft and without humor. "She doesn't have a token," he said. Quinn's gaze swept the market. The old maps in the Nest had been of places that didn't exist. The black-and-white photographs had been of people who had never been in the papers. She thought of Morris, of the bruising around his neck that the pathologist had called inconsistent, of the file that had been redacted line by line. She could leave. Go back up the stairs, call this in, let the Met throw resources at something it couldn't understand. She could follow procedure and spend the rest of her career wondering what happened to Morris. Or she could step further in. Tomás took a half-step between her and the vendor, not threatening, shielding. "There's nothing here for you," he said. "You have a good night." The bell chimed again, deeper this time. The lanterns flickered. The market breathed. Quinn felt the weight of her watch against her wrist, the familiar leather worn smooth by years of use. She thought about loss, about unexplained circumstances, about the line between criminal activity and something else she didn't have a name for yet. She didn't draw her gun. She didn't run. She took one more step down onto the platform, rainwater pooling at her boots, and the market seemed to settle around her, waiting to see what she would ask for. "Then tell me," she said, voice low and even, "what you're buying, and who you're buying it for."
created_at"2026-09-03T13:59:28.602Z" 9/3/2026, 1:59:28 PM
model"meta/muse-glimmer-30b-20260810"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency415
moderation_latency(null)
generation_time37222
tokens_prompt888
tokens_completion2657
native_tokens_prompt830
native_tokens_completion2252
native_tokens_completion_images(null)
native_tokens_reasoning958
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)
usage0.002785
router(null)
user_agent"langchainjs-openai/1.0.0 ((node/v24.19.0; linux; x64))"
http_referer(null)
request_id"req-1788443968-FH8NgNWEeG2vRBjyMxsY"
session_id(null)
preset_id(null)
api_type"completions"
id"gen-1788443968-qOSjSjv6OnjKtvodimLX"
upstream_id"chatcmpl-RxYccGCqzgVlNcNPFowYkreU"
provider_responses
0
endpoint_id"a9912acb-568e-4147-8ed3-5d20aea22135"
id"chatcmpl-RxYccGCqzgVlNcNPFowYkreU"
is_byokfalse
latency60
model_permaslug"meta/muse-glimmer-30b-20260810"
provider_name"DeepInfra"
status200
total_cost0.002785
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
totalTags4
adverbTagCount0
adverbTags(empty)
dialogueSentences7
tagDensity0.571
leniency1
rawRatio0
effectiveRatio0
100.00% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount1199
totalAiIsmAdverbs0
found(empty)
highlights(empty)
100.00% AI-ism character names
Target: 0 AI-default names (17 tracked, −20% each)
codexExemptions(empty)
found(empty)
100.00% AI-ism location names
Target: 0 AI-default location names (33 tracked, −20% each)
codexExemptions(empty)
found(empty)
70.81% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount1199
totalAiIsms7
found
0
word"traced"
count1
1
word"treacherous"
count1
2
word"glint"
count1
3
word"whisper"
count1
4
word"flickered"
count1
5
word"weight"
count1
6
word"familiar"
count1
highlights
0"traced"
1"treacherous"
2"glint"
3"whisper"
4"flickered"
5"weight"
6"familiar"
100.00% Cliché density
Target: ≤1 cliche(s) per 800-word window
totalCliches1
maxInWindow1
found
0
label"eyes widened/narrowed"
count1
highlights
0"eyes widened"
100.00% Emotion telling (show vs. tell)
Target: ≤3% sentences with emotion telling
emotionTells0
narrationSentences104
matches(empty)
87.91% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount2
hedgeCount2
narrationSentences104
filterMatches
0"watch"
hedgeMatches
0"happened to"
1"seemed to"
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences107
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
totalWords1199
ratio0
matches(empty)
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions6
unquotedAttributions0
matches(empty)
100.00% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions40
wordCount1152
uniqueNames20
maxNameDensity0.61
worstName"Quinn"
maxWindowNameDensity1
worstWindowName"Quinn"
discoveredNames
Shaftesbury1
Avenue1
Harlow1
Quinn7
Raven1
Nest5
Herrera2
Saint1
Christopher1
Morris3
Whitechapel1
Camden2
Lock1
Road1
Underground1
Tube1
Veil1
Market1
Met1
Tomás7
persons
0"Harlow"
1"Quinn"
2"Raven"
3"Herrera"
4"Saint"
5"Christopher"
6"Morris"
7"Market"
8"Tomás"
places
0"Shaftesbury"
1"Avenue"
2"Whitechapel"
3"Camden"
4"Lock"
5"Road"
globalScore1
windowScore1
100.00% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences65
glossingSentenceCount0
matches(empty)
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches0
per1kWords0
wordCount1199
matches(empty)
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount0
totalSentences107
matches(empty)
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs34
mean35.26
std28.93
cv0.82
sampleLengths
044
196
23
363
42
5127
621
73
845
99
1047
118
1250
1350
1421
154
1660
1788
183
1950
2049
2152
2214
2316
2420
2518
2658
2737
286
2924
3013
3142
3238
3318
81.65% Passive voice overuse
Target: ≤2% passive sentences
passiveCount7
totalSentences104
matches
0"is emptied"
1"been nudged"
2"been shut"
3"was rumored"
4"been traced"
5"been painted"
6"been killed"
7"been redacted"
27.29% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount5
totalVerbs193
matches
0"wasn't panicking"
1"was checking"
2"wasn't running"
3"was negotiating"
4"was holding"
100.00% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount0
semicolonCount0
flaggedSentences0
totalSentences107
ratio0
matches(empty)
100.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount1160
adjectiveStacks0
stackExamples(empty)
adverbCount25
adverbRatio0.021551724137931036
lyAdverbCount2
lyAdverbRatio0.0017241379310344827
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences107
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences107
mean11.21
std8.62
cv0.769
sampleLengths
018
126
213
39
48
532
65
729
83
92
1022
1121
125
1313
142
154
1615
1727
1823
199
2028
218
2213
234
246
253
263
275
283
2917
3014
315
329
336
343
352
3619
377
3819
398
408
4120
4211
437
444
459
4636
475
485
4912
36.76% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats19
diversityRatio0.32710280373831774
totalSentences107
uniqueOpeners35
67.34% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount2
totalSentences99
matches
0"Just a single glass left"
1"Somewhere far below, a bell"
ratio0.02
46.26% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount43
totalSentences99
matches
0"She had him."
1"She didn't want a uniform"
2"He knew the streets."
3"He cut down a narrow"
4"She still didn't know what"
5"She just knew she wasn't"
6"He wasn't panicking."
7"He was checking the gap."
8"She closed it."
9"He hit Camden Lock Road"
10"Her sharp jaw was set."
11"He didn't go for a"
12"He went down."
13"It carried a faint metallic"
14"She could hear water dripping,"
15"Her radio was silent in"
16"She had a warrant for"
17"She had nothing for this."
18"She should call it in."
19"She should wait for forensics,"
ratio0.434
35.76% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount84
totalSentences99
matches
0"Rain came down hard off"
1"Detective Harlow Quinn kept her"
2"The Raven's Nest had been"
3"She had him."
4"The scar on his left"
5"Quinn didn't call it in."
6"She didn't want a uniform"
7"He knew the streets."
8"Soho at night was a"
9"He cut down a narrow"
10"Quinn's leather watch on her"
11"She still didn't know what"
12"She just knew she wasn't"
13"Tomás looked back once."
14"That was worse."
15"He wasn't panicking."
16"He was checking the gap."
17"She closed it."
18"He hit Camden Lock Road"
19"Rain plastered her hair to"
ratio0.848
0.00% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount0
totalSentences99
matches(empty)
ratio0
61.69% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences44
technicalSentenceCount5
matches
0"She had a warrant for the Nest, for questioning Herrera about off-the-books medical care, for the clique he was rumored to run with, for missing persons who'd b…"
1"The walls were damp brick, covered in old graffiti that had been painted over and painted over again until the surface looked bruised."
2"She could see the glint of glass vials filled with liquid that moved on its own, a stack of bound ledgers with wax seals, a woman holding out a bone token the s…"
3"The black-and-white photographs had been of people who had never been in the papers."
4"She thought of Morris, of the bruising around his neck that the pathologist had called inconsistent, of the file that had been redacted line by line."
0.00% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags4
uselessAdditionCount1
matches
0"she said, voice low and even,"
100.00% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags4
fancyCount0
fancyTags(empty)
dialogueSentences7
tagDensity0.571
leniency1
rawRatio0
effectiveRatio0
80.5155%