Run: 2026-07-01-01KWE9G9X2SS8VDK3N6PCGVXKQ

Run Details

Duration:
35.6s
Cost:
$0.022728
Provider:
Amazon Bedrock

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 in sheets over Camden, turning the pavement into a black mirror that shattered under Quinn's boots. She'd been running for six minutes by her count, lungs burning, the leather watch on her wrist ticking uselessly against a stopwatch she didn't need. She knew exactly how long she'd been chasing this man because she'd been counting since the moment he bolted from the alley behind the Raven's Nest, since the moment she'd flashed her badge and he'd looked at her the way men look at the police only when they have something worse than a warrant to fear. "Stop! Police!" Her voice cracked against the wet brick, swallowed by the rain. He didn't stop. He never did, the smart ones. He cut left down Bayham Street, then right into a service alley thick with the reek of bins and old fryer oil, and Quinn followed because eighteen years on the force had taught her that hesitation cost more than exhaustion ever would. She'd clocked him three weeks back — a courier, mid-twenties, always moving between the Nest and points unknown with a satchel he guarded like it held his own heartbeat. Tonight she'd finally gotten close enough to see what was stitched into the leather: a symbol she didn't recognize, silver thread on black, something that made her stomach twist the way certain crime scenes had, back when Morris was still breathing beside her. She didn't like coincidences. She liked them less when they had something to do with Silas' bar. The alley spat them both out near the old Camden Town tube entrance, boarded up for years, official notices peeling from the gate in wet strips. He went straight for it, hit the chain-link with both hands, and vaulted the low section where the fence had rusted through. "Are you joking," Quinn muttered, and went after him. Her palms scraped raw on the wire. She dropped down the other side into a stairwell that smelled of ozone and mildew, steps slick with algae, no light except the phone she pulled and thumbed into a weak white beam. Somewhere below, his footsteps slapped against concrete, receding, and she followed the sound down through two dead escalators and a turnstile long since stripped for scrap. At the bottom, where the platform should have been dark and empty and smelling of diesel ghosts, there was light instead — a low amber glow, and voices, and the unmistakable murmur of commerce. Quinn stopped so fast her boots skidded. The platform had become something else. Stalls ran the length of the old track, built from packing crates and drapes of oilcloth, lit by candles in jars and by lanterns that burned with a flame too blue to be ordinary fire. She saw shelves of bottled things that moved on their own, bundles of herbs that smelled like rain and rot together, a woman with silver eyes weighing something wrapped in newspaper on a set of brass scales. The rails themselves had been half-swallowed by moss and pale mushrooms, glowing faintly, like the earth had crept up to reclaim the tunnel and been paid off to make itself decorative instead. Her suspect was thirty feet ahead, shoving through the crowd, and the crowd — God, the crowd. A man with skin like scorched bark. Two women joined at the shoulder by something that wasn't scar tissue. A child, or the size of a child, wearing a fox's skull for a face, who turned to watch Quinn with unblinking sockets as she passed. Every instinct she'd built over eighteen years told her to draw her weapon. Every instinct after that told her a firearm would mean less down here than a strongly worded letter. "Police! Stop where you are!" Nobody stopped. Nobody even looked surprised. A few glanced her way with the mild irritation of people disturbed mid-transaction, and returned to their business. She realized, with a cold drop in her gut, that shouting *police* here was like shouting *weather* — a fact of the upper world that held no particular authority. Her suspect reached a stall draped in violet cloth, exchanged something too fast to see with a figure behind the counter, and looked back at her. Not afraid anymore. Almost pitying. "You shouldn't be down here," he said. "You don't have a token." "I don't need a token to arrest you." "You do, actually." He smiled, and it was the smile that decided her — the specific, terrible calm of a man who knew the ground had shifted permanently in his favor. "You need one to leave." He turned and was gone, swallowed between a stall selling jars of something that looked like captured smoke and another selling knives that hummed faintly on their velvet. Quinn stood at the edge of the platform, rain still dripping off her coat onto stone that had never known rain, and felt eighteen years of procedure screaming at her to fall back, secure the perimeter, request backup that did not exist for this, that had never existed for this. She thought of Morris — the last case, the locked room, the burn marks on the ceiling that no fire investigator could explain, the reports she'd rewritten four times until they said something a coroner would sign. She thought about how she'd promised herself, standing over his body, that she would never again walk into a room without knowing what was in it. She thought about the silver-threaded symbol on that satchel, and how it had made the hair rise on her arms the exact same way, three years apart, in a room with a dead man and a hallway with no visible fire source. Somewhere ahead, laughter — human, definitely human, familiar in its cadence if not its owner — drifted from deeper in the market, past a curve where the tunnel dipped from amber light into shadow thick enough to swallow a person whole. Quinn's watch ticked against her wrist. Six minutes had become nine. Nine would become however long it took to either understand what she was looking at or die not understanding it, and she had spent three years telling herself she could live with the second option if it meant getting close enough to the first. She stepped off the platform's edge, onto the mossy rail, into the market. Behind her, the stairwell light flickered once and went out, sealing the boarded gate above in darkness, and the amber glow of the Veil Market closed gently, hungrily, around Detective Harlow Quinn like water over a stone.
created_at"2026-07-01T07:32:41.515Z" 7/1/2026, 7:32:41 AM
model"anthropic/claude-sonnet-5-20260630"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency2783
moderation_latency(null)
generation_time35609
tokens_prompt914
tokens_completion1612
native_tokens_prompt1264
native_tokens_completion2020
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)
num_fetches(null)
web_search_engine(null)
origin"https://ncbench.com/"
is_byokfalse
finish_reason"stop"
native_finish_reason"end_turn"
service_tier"default"
usage0.022728
router(null)
provider_responses
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endpoint_id"37b16f45-eeae-45f3-9b85-2137f7c6d61b"
id"msg_01Q2wpx6GJ3i35N8jEL7caep"
is_byokfalse
latency2765
model_permaslug"anthropic/claude-sonnet-5-20260630"
provider_name"Amazon Bedrock"
status200
user_agent"langchainjs-openai/1.0.0 ((node/v24.17.0; linux; x64))"
http_referer(null)
request_id"req-1782891161-G96UwRYbSJISttogdBgL"
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api_type"completions"
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upstream_id"msg_01Q2wpx6GJ3i35N8jEL7caep"
total_cost0.022728
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upstream_inference_cost0
provider_name"Amazon Bedrock"
response_cache_source_id(null)
data_region"global"

Evaluation details

Result Evaluator Details Meta Data
100.00% Adverbs in dialogue tags
Target: ≤10% dialogue tags with adverbs
totalTags5
adverbTagCount0
adverbTags(empty)
dialogueSentences8
tagDensity0.625
leniency1
rawRatio0
effectiveRatio0
90.79% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount1086
totalAiIsmAdverbs2
found
0
adverb"gently"
count1
1
adverb"hungrily"
count1
highlights
0"gently"
1"hungrily"
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)
72.38% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount1086
totalAiIsms6
found
0
word"shattered"
count1
1
word"stomach"
count1
2
word"footsteps"
count1
3
word"velvet"
count1
4
word"familiar"
count1
5
word"flickered"
count1
highlights
0"shattered"
1"stomach"
2"footsteps"
3"velvet"
4"familiar"
5"flickered"
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
emotionTells1
narrationSentences49
matches
0"looked surprised"
55.39% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount3
hedgeCount0
narrationSentences49
filterMatches
0"watch"
1"look"
hedgeMatches(empty)
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences53
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
repeatedSegmentCount0
maxSentenceWordsSeen56
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans2
markdownWords2
totalWords1094
ratio0.002
matches
0"police"
1"weather"
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions5
unquotedAttributions0
matches(empty)
100.00% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions23
wordCount1056
uniqueNames13
maxNameDensity0.76
worstName"Quinn"
maxWindowNameDensity1
worstWindowName"Quinn"
discoveredNames
Camden2
Quinn8
Raven1
Nest2
Bayham1
Street1
Morris2
Town1
God1
Veil1
Market1
Detective1
Harlow1
persons
0"Quinn"
1"Raven"
2"Morris"
3"Harlow"
places
0"Camden"
1"Bayham"
2"Street"
3"Town"
globalScore1
windowScore1
28.05% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences41
glossingSentenceCount2
matches
0"smelled like rain and rot together, a woma"
1"looked like captured smoke and another se"
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches0
per1kWords0
wordCount1094
matches(empty)
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount0
totalSentences53
matches(empty)
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs26
mean42.08
std29.84
cv0.709
sampleLengths
0100
113
251
372
417
548
69
766
841
96
10104
1162
1231
135
1453
1531
1612
178
1836
1928
20113
2142
2241
2355
2413
2537
83.78% Passive voice overuse
Target: ≤2% passive sentences
passiveCount3
totalSentences49
matches
0"was stitched"
1"been paid"
2"was gone"
87.01% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount3
totalVerbs177
matches
0"was still breathing"
1"was like shouting"
2"was looking"
0.00% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount8
semicolonCount0
flaggedSentences7
totalSentences53
ratio0.132
matches
0"She'd clocked him three weeks back — a courier, mid-twenties, always moving between the Nest and points unknown with a satchel he guarded like it held his own heartbeat."
1"At the bottom, where the platform should have been dark and empty and smelling of diesel ghosts, there was light instead — a low amber glow, and voices, and the unmistakable murmur of commerce."
2"Her suspect was thirty feet ahead, shoving through the crowd, and the crowd — God, the crowd."
3"She realized, with a cold drop in her gut, that shouting *police* here was like shouting *weather* — a fact of the upper world that held no particular authority."
4"\"You do, actually.\" He smiled, and it was the smile that decided her — the specific, terrible calm of a man who knew the ground had shifted permanently in his favor."
5"She thought of Morris — the last case, the locked room, the burn marks on the ceiling that no fire investigator could explain, the reports she'd rewritten four times until they said something a coroner would sign."
6"Somewhere ahead, laughter — human, definitely human, familiar in its cadence if not its owner — drifted from deeper in the market, past a curve where the tunnel dipped from amber light into shadow thick enough to swallow a person whole."
92.71% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount269
adjectiveStacks0
stackExamples(empty)
adverbCount13
adverbRatio0.048327137546468404
lyAdverbCount4
lyAdverbRatio0.01486988847583643
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences53
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences53
mean20.64
std14.6
cv0.707
sampleLengths
019
125
256
313
43
56
642
729
843
94
1013
1126
1222
139
147
1533
1626
1734
187
196
2035
2137
2232
2317
247
2512
2626
2713
2818
295
302
314
3218
3329
3426
353
362
377
385
398
4031
415
4228
4350
4437
4526
4642
4741
486
495
56.60% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats10
diversityRatio0.4528301886792453
totalSentences53
uniqueOpeners24
100.00% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount2
totalSentences46
matches
0"Somewhere below, his footsteps slapped"
1"Somewhere ahead, laughter — human,"
ratio0.043
28.70% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount22
totalSentences46
matches
0"She'd been running for six"
1"She knew exactly how long"
2"Her voice cracked against the"
3"He didn't stop."
4"He never did, the smart"
5"He cut left down Bayham"
6"She'd clocked him three weeks"
7"She didn't like coincidences."
8"She liked them less when"
9"He went straight for it,"
10"Her palms scraped raw on"
11"She dropped down the other"
12"She saw shelves of bottled"
13"Her suspect was thirty feet"
14"She realized, with a cold"
15"Her suspect reached a stall"
16"He smiled, and it was"
17"He turned and was gone,"
18"She thought of Morris —"
19"She thought about how she'd"
ratio0.478
57.83% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount37
totalSentences46
matches
0"Rain came down in sheets"
1"She'd been running for six"
2"She knew exactly how long"
3"Her voice cracked against the"
4"He didn't stop."
5"He never did, the smart"
6"He cut left down Bayham"
7"She'd clocked him three weeks"
8"Tonight she'd finally gotten close"
9"She didn't like coincidences."
10"She liked them less when"
11"The alley spat them both"
12"He went straight for it,"
13"Quinn muttered, and went after"
14"Her palms scraped raw on"
15"She dropped down the other"
16"Quinn stopped so fast her"
17"The platform had become something"
18"Stalls ran the length of"
19"She saw shelves of bottled"
ratio0.804
0.00% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount0
totalSentences46
matches(empty)
ratio0
0.00% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences31
technicalSentenceCount9
matches
0"Rain came down in sheets over Camden, turning the pavement into a black mirror that shattered under Quinn's boots."
1"She'd been running for six minutes by her count, lungs burning, the leather watch on her wrist ticking uselessly against a stopwatch she didn't need."
2"Tonight she'd finally gotten close enough to see what was stitched into the leather: a symbol she didn't recognize, silver thread on black, something that made …"
3"She dropped down the other side into a stairwell that smelled of ozone and mildew, steps slick with algae, no light except the phone she pulled and thumbed into…"
4"Stalls ran the length of the old track, built from packing crates and drapes of oilcloth, lit by candles in jars and by lanterns that burned with a flame too bl…"
5"She saw shelves of bottled things that moved on their own, bundles of herbs that smelled like rain and rot together, a woman with silver eyes weighing something…"
6"She realized, with a cold drop in her gut, that shouting *police* here was like shouting *weather* — a fact of the upper world that held no particular authority…"
7"He turned and was gone, swallowed between a stall selling jars of something that looked like captured smoke and another selling knives that hummed faintly on th…"
8"Quinn stood at the edge of the platform, rain still dripping off her coat onto stone that had never known rain, and felt eighteen years of procedure screaming a…"
100.00% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags5
uselessAdditionCount0
matches(empty)
25.00% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags2
fancyCount1
fancyTags
0"Quinn muttered (mutter)"
dialogueSentences8
tagDensity0.25
leniency0.5
rawRatio0.5
effectiveRatio0.25
75.9412%