Run: 2026-09-23-01M37P766VQQMQ4MG7ZDQS0Y5Q

Run Details

Duration:
57.5s
Cost:
$0.080344
Provider:
Claude Platform on AWS

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
The rain had been falling since Soho, and by Camden it had stopped pretending to be anything but a deluge. Harlow Quinn stood in the doorway of a shuttered kebab shop on Chalk Farm Road and watched the man across the street through a curtain of water sheeting off the awning. Forty minutes she'd been on him. Out the door of the Raven's Nest under that sickly green neon, north on foot, then the Northern line, and she'd stood two carriages down and watched his reflection in the black glass the whole way. Now he was here, loitering outside a locked gate beside a boarded-up entrance to nothing, checking his phone like a man with an appointment. Tomás Herrera. Twenty-nine. Former paramedic, struck off by the Health and Care Professions Council eighteen months ago for "administering unapproved substances to patients without consent or clinical justification." The file was thin in the places that mattered. The patients, for instance. Four of them, and not one had a name the NHS could verify. Quinn checked her watch. The leather strap was dark with rain, the face fogged at the edges. 11:52. He'd been at the Nest for two hours. So had half the people she'd been circling for six months, the ones who drank in Silas's bar and went in through the back and didn't come out the front. Three disappearances in Westminster since spring. Two bodies that the coroner had signed off with a shrug. Every thread she pulled came back to that bar and its maps and its photographs of dead Londoners staring out of the walls. And Herrera was the one who patched them up afterward. She was sure of it. Across the street, he looked up. Not at her. Past her, at the sky, like he was checking the weather. Then his head came down and turned, and for one long second his eyes found the kebab shop doorway, and Quinn knew she'd been made. He ran. She was already moving. Eighteen years had taught her the first step mattered more than the fastest one. She came off the kerb into ankle-deep water in the gutter, and a night bus blared at her and threw up a wall of spray, and she went round the back of it and saw him cutting left down an alley between a vintage shop and a shuttered market stall. "Police! Tomás Herrera, stop!" He didn't stop. They never did. But he looked back, and that cost him half a step on the wet cobbles. The alley stank of wet cardboard and old frying oil. Quinn's shoes skidded, found purchase. Ahead of her Herrera vaulted a stack of pallets, one hand braced on top, and she saw the pale line of the scar along his left forearm where his sleeve had ridden up. Knife wound, according to an A&E record from Whitechapel. He'd treated himself and discharged himself before anyone could ask how. She took the pallets at a scramble. Her knee cracked against a slat, and she swallowed the pain and kept going. The alley spat them out onto a service road behind the old railway arches. Brick vaulting overhead, water pouring off the edges in ropes. Herrera sprinted beneath them, and his footfalls echoed back doubled, tripled, until it sounded like a crowd was running. Quinn followed the real ones. She'd always been able to tell. He darted right, towards a chain-link fence she'd walked past a dozen times in daylight and never looked at twice. Behind it was a squat brick structure with the ghost of a roundel painted over in grey municipal paint. A disused station entrance. There were dozens across London, sealed up when the lines were rerouted, forgotten by everyone but trainspotters and urban explorers. The fence had a gap. Herrera went through it sideways without breaking stride, as though he'd done it a hundred times. Quinn hit the fence a second later and felt the cut ends of the wire snag her coat. She tore free. Beyond the fence, a steel door that should have been welded shut stood ajar, and a thin, amber light leaked from the crack like something alive. Herrera hauled it wider and plunged through. She reached it three strides behind him and caught the door before it closed. Stairs went down, steep and tiled, the old cream-and-maroon of Edwardian stations, cracked and stained with a century of damp. The light came from below. So did the noise, and it wasn't the dripping silence of an abandoned tunnel. It was voices. Hundreds of them. Music, something reedy and wrong, in no key she recognised. The smell hit her next, woodsmoke and spice and under it something sharp and chemical that clawed at the back of her throat. She knew that smell. It stopped her on the top step as surely as a hand on her chest. Three years ago, in a flat above a laundrette in Deptford, she had smelled exactly this. She had kicked in the door with Morris beside her. She remembered the heat of the room, the strange sweet-burnt air, Morris saying *Harlow, get back*, in a voice she had never heard him use. And then the light going out, and when it came back on he was gone. Not dead. Not injured. Gone. They'd never found so much as a shoe. The official report said he had left through a rear window. There was no rear window. Quinn's heart was going hard, and not from the running. Below, Herrera's footsteps clattered down the stairs. She shook herself and followed. The stairwell turned once, twice. The tiles grew older as she went, and then they weren't tiles at all but something carved, symbols scratched into the plaster in no alphabet she'd ever seen. The amber light brightened. At the bottom was a long passage leading to what must once have been the ticket hall, and across its mouth stood an iron turnstile of the old kind, waist-high, with a figure beside it. Herrera reached the turnstile and slapped something into a slot on top. Quinn lunged the last few feet and closed her hand on his sleeve. He twisted. For a moment they were face to face, close enough that she could see the rain dripping from his dark curls, the gold Saint Christopher medallion swinging free of his collar. His warm brown eyes weren't frightened, not quite. They were something closer to pity. "Detective," he said, breathless, his accent softening the edges of the word. "You don't want to come in here. Please. Go home." "Where's Morris?" It came out of her before she could stop it. She hadn't meant to say it. She hadn't said his name aloud in a year. Something shifted in Herrera's face. Recognition, maybe. Or just surprise. "I don't know who that is," he said. And then, quieter: "But if he came down here, I'm sorry." He wrenched his arm, and her wet grip slid. He was through the turnstile and gone into the amber haze before she could grab again. The iron arms clanked back into place behind him. Quinn slammed against the bar. It didn't move. The figure beside the turnstile turned its head. It was tall and hooded, and it had been perfectly still until now, so still she'd taken it for a statue. Beneath the hood she saw only a jaw, grey and finely lined as old paper, and a mouth that didn't open when it spoke. "Token." The voice was dry. It came from everywhere at once. "Metropolitan Police." She held up her warrant card with a hand that she was relieved to find steady. "I'm in pursuit of a suspect. Open this gate." The hooded thing regarded the card for a long moment. Then it looked back at her. "Token," it said again, with no more inflection than before. Beyond the turnstile, the old ticket hall opened into something vast. The platform and tracks were gone beneath a sprawl of stalls lit by lanterns and jars of cold, floating light. Stalls selling glass vials that pulsed like heartbeats. Stalls hung with dried things she didn't want to name. A woman with too-long fingers weighed out silver dust on a scale. Two men argued over a cage draped in black silk, and whatever was in it was singing. Everywhere, people moved and haggled and laughed, and not all of them walked the way people were supposed to. She had eighteen years of service and a chest of commendations. She had pulled bodies out of the Thames and talked a man off a parapet on Waterloo Bridge. She had never once in her life felt so thoroughly that she was standing on the wrong side of a line. She looked down. On the floor at her feet, half-submerged in a puddle of rainwater she'd dragged in herself, lay a small, pale object. It must have come free when she'd grabbed Herrera's sleeve. She crouched and picked it up. A disc of bone, no bigger than a fifty-pence piece, carved with one of those symbols from the stairwell. It was warm. Warmer than it should have been, like it had been held in a closed fist for hours. She turned it over in her fingers. She thought about the radio in her pocket, dead since the second landing. She thought about the protocol she knew by heart, the one that said *withdraw, report, request backup.* She thought about how that report would read to her superintendent, and how it would read to the psychologist he'd send her to afterwards. She thought about Morris saying *Harlow, get back.* She hadn't gotten back. She'd gone in after him, and she'd been too slow, and the light had gone out. The hooded figure watched her without eyes. Beyond it, far down the crowded platform, she caught a flash of dark curls moving away through the throng, not quite running now. Herrera looked back once. He didn't look afraid for himself. He looked afraid for her. Quinn stood. She squared her shoulders, the old parade-ground habit, and wiped the rain from her face with the back of her wrist. Her watch read 11:58. Two minutes to midnight, in a place where she doubted midnight meant anything at all. She set the bone token into the slot. The turnstile turned.
created_at"2026-09-23T17:50:06.066Z" 9/23/2026, 5:50:06 PM
model"anthropic/claude-opus-5.5-20260921"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency5109
moderation_latency(null)
generation_time57449
tokens_prompt888
tokens_completion2659
native_tokens_prompt1266
native_tokens_completion3764
native_tokens_completion_images(null)
native_tokens_reasoning532
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"
usage0.080344
router(null)
user_agent"langchainjs-openai/1.0.0 ((node/v24.20.0; linux; x64))"
http_referer(null)
request_id"req-1790185806-HsXbqIJYvdJoJytEhDgV"
session_id(null)
preset_id(null)
api_type"completions"
id"gen-1790185806-YMa9DepwLqeCf4s69rrA"
upstream_id"msg_011CfLo1j67YvvzksvuRjJHk"
provider_responses
0
endpoint_id"3a2388bc-3740-4e64-a1f5-4e301726b6b9"
id"msg_011CfLo1j67YvvzksvuRjJHk"
is_byokfalse
latency1197
model_permaslug"anthropic/claude-opus-5.5-20260921"
provider_name"Claude Platform on AWS"
status200
total_cost0.080344
cache_discount(null)
upstream_inference_cost0
provider_name"Claude Platform on AWS"
response_cache_source_id(null)
data_region"global"
workspace_id"97e315e5-d303-487d-83c1-83180e8a13d4"

Evaluation details

Result Evaluator Details Meta Data
18.18% Adverbs in dialogue tags
Target: ≤10% dialogue tags with adverbs
totalTags4
adverbTagCount1
adverbTags
0"it said again [again]"
dialogueSentences11
tagDensity0.364
leniency0.727
rawRatio0.25
effectiveRatio0.182
97.10% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount1725
totalAiIsmAdverbs1
found
0
adverb"perfectly"
count1
highlights
0"perfectly"
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)
82.61% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount1725
totalAiIsms6
found
0
word"echoed"
count1
1
word"structure"
count1
2
word"silence"
count1
3
word"footsteps"
count1
4
word"pulsed"
count1
5
word"silk"
count1
highlights
0"echoed"
1"structure"
2"silence"
3"footsteps"
4"pulsed"
5"silk"
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
narrationSentences143
matches
0"was relieved"
1"looked afraid"
100.00% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount2
hedgeCount0
narrationSentences143
filterMatches
0"watch"
hedgeMatches(empty)
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences148
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
repeatedSegmentCount0
maxSentenceWordsSeen51
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans3
markdownWords10
totalWords1725
ratio0.006
matches
0"Harlow, get back"
1"withdraw, report, request backup."
2"Harlow, get back."
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions10
unquotedAttributions1
matches
0"She remembered the heat of the room, the strange sweet-burnt air, Morris saying *Harlow, get back*, in a voice she had n…"
100.00% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions52
wordCount1671
uniqueNames28
maxNameDensity0.66
worstName"Herrera"
maxWindowNameDensity1.5
worstWindowName"Herrera"
discoveredNames
Soho1
Camden1
Quinn10
Chalk1
Farm1
Road1
Raven1
Nest2
Northern1
Herrera11
Health1
Care1
Professions1
Council1
Silas1
Westminster1
Londoners1
Whitechapel1
London1
Edwardian1
Deptford1
Morris3
Saint1
Christopher1
Thames1
Waterloo1
Bridge1
Two3
persons
0"Quinn"
1"Raven"
2"Herrera"
3"Silas"
4"Londoners"
5"Morris"
6"Saint"
7"Christopher"
places
0"Soho"
1"Chalk"
2"Farm"
3"Road"
4"Nest"
5"Westminster"
6"Whitechapel"
7"London"
8"Deptford"
9"Thames"
10"Waterloo"
11"Bridge"
globalScore1
windowScore1
74.24% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences99
glossingSentenceCount3
matches
0"sounded like a crowd was running"
1"not quite"
2"not quite running now"
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches0
per1kWords0
wordCount1725
matches(empty)
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount1
totalSentences148
matches
0"knew that smell"
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs55
mean31.36
std26.72
cv0.852
sampleLengths
020
197
254
318
478
515
66
739
82
968
104
1121
1268
1321
1454
1563
1621
1747
187
1992
204
2115
2279
2316
2410
2512
2672
2712
2813
2947
3022
312
3225
3310
3419
3534
368
3753
381
3910
4027
4126
4297
4350
443
4537
4639
4761
488
4920
85.63% Passive voice overuse
Target: ≤2% passive sentences
passiveCount8
totalSentences143
matches
0"been made"
1"were rerouted"
2"been welded"
3"was gone"
4"was relieved"
5"were gone"
6"were supposed"
7"been held"
55.60% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount6
totalVerbs277
matches
0"was checking"
1"was already moving"
2"was running"
3"was going"
4"was singing"
5"was standing"
100.00% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount0
semicolonCount0
flaggedSentences0
totalSentences148
ratio0
matches(empty)
94.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount1683
adjectiveStacks1
stackExamples
0"strange sweet-burnt air,"
adverbCount49
adverbRatio0.029114676173499703
lyAdverbCount7
lyAdverbRatio0.0041592394533571005
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences148
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences148
mean11.66
std9.02
cv0.774
sampleLengths
020
131
26
336
424
52
61
734
84
913
104
1113
121
138
1430
156
1611
1723
1810
195
206
213
2211
2325
242
254
2614
2750
284
293
303
3115
3210
335
3433
359
3611
377
3814
3914
4010
4119
425
436
4420
4519
464
4720
485
4916
53.74% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats16
diversityRatio0.3877551020408163
totalSentences147
uniqueOpeners57
75.76% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount3
totalSentences132
matches
0"Then his head came down"
1"Then it looked back at"
2"Everywhere, people moved and haggled"
ratio0.023
65.45% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount51
totalSentences132
matches
0"He'd been at the Nest"
1"She was sure of it."
2"She was already moving."
3"She came off the kerb"
4"He didn't stop."
5"They never did."
6"He'd treated himself and discharged"
7"She took the pallets at"
8"Her knee cracked against a"
9"She'd always been able to"
10"He darted right, towards a"
11"She tore free."
12"She reached it three strides"
13"It was voices."
14"She knew that smell."
15"It stopped her on the"
16"She had kicked in the"
17"She remembered the heat of"
18"They'd never found so much"
19"She shook herself and followed."
ratio0.386
100.00% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount95
totalSentences132
matches
0"The rain had been falling"
1"Harlow Quinn stood in the"
2"The patients, for instance."
3"Quinn checked her watch."
4"The leather strap was dark"
5"He'd been at the Nest"
6"Every thread she pulled came"
7"She was sure of it."
8"She was already moving."
9"She came off the kerb"
10"He didn't stop."
11"They never did."
12"The alley stank of wet"
13"Quinn's shoes skidded, found purchase."
14"Knife wound, according to an"
15"He'd treated himself and discharged"
16"She took the pallets at"
17"Her knee cracked against a"
18"The alley spat them out"
19"Brick vaulting overhead, water pouring"
ratio0.72
37.88% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount1
totalSentences132
matches
0"Now he was here, loitering"
ratio0.008
100.00% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences69
technicalSentenceCount1
matches
0"Beyond the fence, a steel door that should have been welded shut stood ajar, and a thin, amber light leaked from the crack like something alive."
100.00% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags4
uselessAdditionCount0
matches(empty)
100.00% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags3
fancyCount0
fancyTags(empty)
dialogueSentences11
tagDensity0.273
leniency0.545
rawRatio0
effectiveRatio0
88.0065%