Run: 2026-02-17-01KHMPCC36CTCZDSQCBJ60EQXP

Run Details

Duration:
29.4s
Cost:
$0.002105
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 lashed down on the deserted streets of Soho, casting a rhythmic melody that echoed off the towering buildings. Detective Harlow Quinn sprinted down Old Compton Street, her eyes fixed on the fleeting figure of Tomás Herrera, her prime suspect in the string of bizarre occurrences plaguing the city. Quinn's sharp jaw set in a determined line as she pounded the wet pavement, her worn leather watch glinting on her left wrist. Eighteen years on the force had honed her instincts, and every fiber screamed that Herrera was hiding more than just his involvement in the clique. The memory of her fallen partner, DS Morris, flashed in her mind, fueling her relentless pursuit. Ahead, Herrera darted into a narrow alley between two buildings, the neon signs of the surrounding bars and clubs casting an eerie glow on the rain-soaked walls. Quinn followed, her military-honed bearing guiding her through the treacherous terrain with ease. The alley opened into a broader thoroughfare, and for a moment, she lost sight of Herrera in the crowd. Then, a curly dark brown head bobbed above the sea of umbrellas, and Quinn gave chase once more. Herrera wove through the throngs of people, leading her toward the outskirts of Soho. The streetlights grew farther apart, casting long shadows that stretched and twisted in the rain. A faded sign creaked in the wind: "Camden" – they were heading into the depths of North London. As they approached the abandoned Tube station beneath Camden, a shiver ran down Quinn's spine. This was the rumored site of the Veil Market, a clandestine supernatural bazaar hidden from the prying eyes of the law. She had heard whispers, but nothing concrete – until now. Herrera vanished into the Tube station's entrance, a nondescript opening that blended seamlessly into the surrounding urban decay. Quinn slowed, her hand instinctively drifting to her hip, only to remember she'd left her sidearm locked in her desk drawer, a precaution against the unpredictable nature of this case. With a deep breath, she stepped into the unknown, leaving behind the relative safety of the rain-soaked streets. The air inside the abandoned station clung to her like a damp shroud, heavy with the scent of decay and forgotten memories. A narrow corridor stretched before her, the only sound the soft dripping of water somewhere in the darkness. Quinn's eyes adjusted slowly to the dim light, and she spotted a figure in the distance, standing before a rickety wooden stall. Herrera. A sign above the stall read "Madam Zora's Curios" in flickering, candle-lit letters. The vendor, an ageless woman with eyes that seemed to hold a thousand secrets, watched Quinn's approach with an unblinking gaze. To gain entry to the market, Quinn knew she needed a bone token – a macabre currency she didn't possess. Her presence, however, had already attracted attention. Patrons of the Veil Market began to emerge from the shadows, their faces a blur of human and...not. The detective's skin crawled as she realized she was outnumbered, outgunned, and out of her depth. Herrera turned, his warm brown eyes locking onto Quinn's, a spark of challenge dancing within them. He raised his left arm, and for an instant, the Saint Christopher medallion glinted around his neck. The scar running along his forearm seemed to pulse, a grim reminder of the dangers that lurked within this hidden world. With a measured movement, Herrera stepped back, disappearing behind the stall. Madam Zora's smile grew, her eyes glinting with a knowing light. "Welcome, Detective Quinn, to the Veil Market. Leave your world at the door. Here, the only law is the one you're willing to break." Quinn's grip on her bearings faltered for an instant, the weight of the unknown pressing upon her. She could retreat, return with a SWAT team, and risk sparking a catastrophic confrontation. Or, she could follow Herrera, alone and unarmed, into the very heart of the supernatural underworld. The pounding of the rain outside, the faint hum of the market, and the soft whisper of DS Morris's name in her mind merged into a singular, haunting melody. With a resolute breath, Detective Harlow Quinn stepped forward, into the shadows, leaving the familiarity of her world behind. The darkness swallowed her whole, leaving only the echoes of her own resolve: _I will uncover the truth, no matter the cost._
created_at"2026-02-17T02:21:00.81108+00:00" 2/17/2026, 2:21:00 AM
model"nvidia/llama-3.1-nemotron-70b-instruct"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency148
moderation_latency(null)
generation_time29359
tokens_prompt959
tokens_completion1116
native_tokens_prompt817
native_tokens_completion937
native_tokens_completion_images(null)
native_tokens_reasoning0
native_tokens_cached0
num_media_prompt(null)
num_input_audio_prompt(null)
num_media_completion0
num_search_results(null)
origin"https://ncbench.com/"
is_byokfalse
finish_reason"stop"
native_finish_reason"stop"
usage0.0021048
router(null)
provider_responses
0
id"cmpl-6b36338cf9ac456d9d9f94f1c1b7b0a1"
status200
is_byokfalse
latency58
endpoint_id"d2a33d30-5d41-47d3-a816-1cc067b5a7dd"
provider_name"DeepInfra"
model_permaslug"nvidia/llama-3.1-nemotron-70b-instruct"
api_type"completions"
id"gen-1771294830-jvF6sfuzxmFELVhq91iT"
upstream_id"cmpl-6b36338cf9ac456d9d9f94f1c1b7b0a1"
total_cost0.0021048
cache_discount(null)
upstream_inference_cost0
provider_name"DeepInfra"

Evaluation details

Result Evaluator Details Meta Data
100.00% Adverbs in dialogue tags
Target: ≤10% dialogue tags with adverbs
totalTags1
adverbTagCount0
adverbTags(empty)
dialogueSentences3
tagDensity0.333
leniency0.667
rawRatio0
effectiveRatio0
86.13% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount721
totalAiIsmAdverbs2
found
0
adverb"slowly"
count1
1
adverb"very"
count1
highlights
0"slowly"
1"very"
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)
0.00% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount721
totalAiIsms19
found
0
word"rhythmic"
count1
1
word"echoed"
count1
2
word"fleeting"
count1
3
word"determined"
count1
4
word"glinting"
count2
5
word"treacherous"
count1
6
word"depths"
count1
7
word"clandestine"
count1
8
word"macabre"
count1
9
word"dancing"
count1
10
word"pulse"
count1
11
word"reminder"
count1
12
word"measured"
count1
13
word"weight"
count1
14
word"pounding"
count1
15
word"whisper"
count1
16
word"echoes"
count1
17
word"resolve"
count1
highlights
0"rhythmic"
1"echoed"
2"fleeting"
3"determined"
4"glinting"
5"treacherous"
6"depths"
7"clandestine"
8"macabre"
9"dancing"
10"pulse"
11"reminder"
12"measured"
13"weight"
14"pounding"
15"whisper"
16"echoes"
17"resolve"
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
narrationSentences39
matches(empty)
0.00% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount1
hedgeCount4
narrationSentences39
filterMatches
0"watch"
hedgeMatches
0"seemed to"
1"try to"
2"began to"
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences40
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
maxSentenceWordsSeen30
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans1
markdownWords9
totalWords724
ratio0.012
matches
0"I will uncover the truth, no matter the cost."
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions1
unquotedAttributions0
matches(empty)
63.67% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions46
wordCount695
uniqueNames19
maxNameDensity1.73
worstName"Quinn"
maxWindowNameDensity2.5
worstWindowName"Quinn"
discoveredNames
Soho2
Harlow2
Quinn12
Old1
Compton1
Street1
Tomás1
Herrera10
Morris2
North1
London1
Tube2
Camden1
Veil2
Market2
Saint1
Christopher1
Zora1
Detective2
persons
0"Harlow"
1"Quinn"
2"Tomás"
3"Herrera"
4"Morris"
5"Saint"
6"Christopher"
7"Zora"
places
0"Soho"
1"Old"
2"Compton"
3"Street"
4"North"
5"London"
6"Tube"
globalScore0.637
windowScore0.833
84.21% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences38
glossingSentenceCount1
matches
0"eyes that seemed to hold a thousand secrets, watched Quinn's approach with an unblinking gaze"
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches0
per1kWords0
wordCount724
matches(empty)
83.33% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount1
totalSentences40
matches
0"screamed that Herrera"
0.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs13
mean55.69
std7.73
cv0.139
sampleLengths
049
164
259
365
446
548
658
757
861
954
1046
1147
1270
96.27% Passive voice overuse
Target: ≤2% passive sentences
passiveCount1
totalSentences39
matches
0"was outnumbered"
56.63% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount2
totalVerbs93
matches
0"was hiding"
1"were heading"
0.00% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount2
semicolonCount0
flaggedSentences2
totalSentences40
ratio0.05
matches
0"She had heard whispers, but nothing concrete – until now."
1"To gain entry to the market, Quinn knew she needed a bone token – a macabre currency she didn't possess."
100.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount697
adjectiveStacks0
stackExamples(empty)
adverbCount18
adverbRatio0.02582496413199426
lyAdverbCount7
lyAdverbRatio0.010043041606886656
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences40
echoCount0
echoWords(empty)
69.41% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences40
mean18.1
std5.86
cv0.324
sampleLengths
019
130
223
325
416
527
613
719
818
914
1015
1118
1215
1321
1410
1518
1630
1718
1822
1918
2022
211
2213
2321
2420
257
2618
2716
2816
2917
3021
3111
3211
3324
3417
3514
3616
3729
3819
3922
83.33% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats0
diversityRatio0.5
totalSentences40
uniqueOpeners20
87.72% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount1
totalSentences38
matches
0"Then, a curly dark brown"
ratio0.026
100.00% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount4
totalSentences38
matches
0"She had heard whispers, but"
1"Her presence, however, had already"
2"He raised his left arm,"
3"She could retreat, return with"
ratio0.105
78.42% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount29
totalSentences38
matches
0"Rain lashed down on the"
1"Detective Harlow Quinn sprinted down"
2"Quinn's sharp jaw set in"
3"The memory of her fallen"
4"Quinn followed, her military-honed bearing"
5"The alley opened into a"
6"Herrera wove through the throngs"
7"The streetlights grew farther apart,"
8"A faded sign creaked in"
9"This was the rumored site"
10"She had heard whispers, but"
11"Herrera vanished into the Tube"
12"Quinn slowed, her hand instinctively"
13"The air inside the abandoned"
14"A narrow corridor stretched before"
15"Quinn's eyes adjusted slowly to"
16"A sign above the stall"
17"The vendor, an ageless woman"
18"Her presence, however, had already"
19"Patrons of the Veil Market"
ratio0.763
100.00% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount2
totalSentences38
matches
0"To gain entry to the"
1"Or, she could follow Herrera,"
ratio0.053
79.83% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences34
technicalSentenceCount3
matches
0"Rain lashed down on the deserted streets of Soho, casting a rhythmic melody that echoed off the towering buildings."
1"The streetlights grew farther apart, casting long shadows that stretched and twisted in the rain."
2"Herrera vanished into the Tube station's entrance, a nondescript opening that blended seamlessly into the surrounding urban decay."
100.00% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags1
uselessAdditionCount0
matches(empty)
100.00% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags0
78.9652%