Run: 2026-10-08-01M4DACKP8TE4EGDPWSX7KT0JR

Run Details

Duration:
11.9s
Cost:
$0.000954
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 turned Camden Road into a river of sodium light, and every reflection shattered when a car passed. Quinn kept her eyes on the grey coat ahead of her, forty yards off and moving with the unhurried stride of someone who knew he was not in danger of being caught. Twice he had glanced back. Twice he had not hurried. Her left wrist ached under the worn leather strap of her watch. Eleven minutes past one. She had told the desk sergeant she was going home. She had not told anyone about the photographs in the file, the ones of a man who looked like he had walked out of a Victorian engraving, or about the way the last witness had stopped mid-sentence and stared at the window as if someone were standing outside it. The man turned left off the main road into a service lane that smelled of wet brick and diesel. Quinn slowed at the mouth of it, her shoes loud on the pavement, then made herself go quieter. Her breath clouded and vanished. The lane narrowed between a shuttered betting shop and a wall plastered with gig posters bleeding in the rain. At the far end stood a railway arch with a rusted iron gate. Beyond the gate, steps descended into darkness. Above the gate hung a sign, its paint so faded she had to lean closer to read it. *Camden Town Station, Northern Line. Closed.* Someone had scratched a crude symbol beneath the word, three curved lines like a stylized ribcage. The grey coat stopped at the gate. He reached into his pocket and held something up to the lock. It was small and pale, and even at this distance Quinn could see it was not plastic or metal. The lock clicked open without a key. The man slipped through, and the gate swung back on its hinges with a long, complaining groan. Quinn stood still. Her pulse hammered in her throat, and she was aware of how loud it was, how easily it would carry down those stairs. Eighteen years in the Metropolitan Police had taught her procedure. Call it in. Secure the perimeter. Wait for backup. Do not enter an unlit space alone when you have no idea what is on the other side of it. Every instinct she had drilled into her over those years said the same thing. But procedure had not saved Morris. Three years ago, Dan Morris had walked into a basement in Hackney on a routine tip, and when Quinn reached the bottom of the stairs there had been nothing there but him, kneeling on the concrete, staring at his own hands as though they belonged to someone else. He had not been able to tell her what happened. Within a month he was dead, and the coroner had written the words *undetermined* and *unexplained* in neat type. Quinn had read the report nine times. She had not believed a word of it, and she had never found anyone who could tell her what was true. Now there was a man who carried a token that opened locks no one had made, and he had walked down those steps as if he owned them. She pulled out her phone. No signal, only a small bar that flickered and died. She tried the radio clipped to her coat. Static, then nothing. The rain pattered on the iron roof of the arch and ran in thin streams down the gate. She thought of Morris's hands. Quinn stepped forward and pushed the gate. It moved under her palm with almost no resistance, as if it had been waiting. Cold air rose from the stairwell, damp and metallic, carrying a scent she could not name. Beneath it was something sweeter, like lilies left too long in a vase, and something sharper, like the air after a lightning strike. She took out her torch, then hesitated and switched it off. If the man below had a reason to keep the light off, perhaps she should too. Her eyes would adjust. Her hand found the cold rail. Somewhere far beneath her, a bell rang once, low and clear, and then a murmur of voices rose and fell like a tide. Quinn drew a breath, settled her weight on the first step, and began to descend.
created_at"2026-10-08T08:34:29.201Z" 10/8/2026, 8:34:29 AM
model"anthropic/claude-haiku-5.5-20261007"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency2771
moderation_latency(null)
generation_time11820
tokens_prompt888
tokens_completion1216
native_tokens_prompt1266
native_tokens_completion1655
native_tokens_completion_images(null)
native_tokens_reasoning382
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"
usage0.0009541
router(null)
user_agent"langchainjs-openai/1.0.0 ((node/v24.21.0; linux; x64))"
http_referer(null)
request_id"req-1791448469-Cd6KUqAIjVIe3vdJT0Qy"
session_id(null)
preset_id(null)
api_type"completions"
id"gen-1791448469-JYJ3lwvfQp6Zf04T2KWH"
upstream_id"msg_011CfpTn59cgWh12epjqjJJ5"
provider_responses
0
endpoint_id"b6cdf493-3a61-441f-a134-e7944fddb980"
id"msg_011CfpTn59cgWh12epjqjJJ5"
is_byokfalse
latency1004
model_permaslug"anthropic/claude-haiku-5.5-20261007"
provider_name"Claude Platform on AWS"
status200
total_cost0.0009541
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
100.00% Adverbs in dialogue tags
Target: ≤10% dialogue tags with adverbs
totalTags0
100.00% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount723
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)
72.34% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount723
totalAiIsms4
found
0
word"shattered"
count1
1
word"pulse"
count1
2
word"flickered"
count1
3
word"weight"
count1
highlights
0"shattered"
1"pulse"
2"flickered"
3"weight"
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
narrationSentences53
matches(empty)
88.95% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount1
hedgeCount1
narrationSentences53
filterMatches
0"watch"
hedgeMatches
0"began to"
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
maxSentenceWordsSeen50
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans3
markdownWords8
totalWords723
ratio0.011
matches
0"Camden Town Station, Northern Line. Closed."
1"undetermined"
2"unexplained"
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions0
unquotedAttributions0
matches(empty)
94.67% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions23
wordCount723
uniqueNames13
maxNameDensity1.11
worstName"Quinn"
maxWindowNameDensity2
worstWindowName"Quinn"
discoveredNames
Camden2
Road1
Victorian1
Town1
Station1
Northern1
Line1
Quinn8
Metropolitan1
Police1
Morris3
Dan1
Hackney1
persons
0"Victorian"
1"Quinn"
2"Police"
3"Morris"
4"Dan"
places
0"Camden"
1"Road"
2"Metropolitan"
3"Hackney"
globalScore0.947
windowScore1
87.50% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences40
glossingSentenceCount1
matches
0"looked like he had walked out of a Victor"
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches0
per1kWords0
wordCount723
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
totalParagraphs16
mean45.19
std26.34
cv0.583
sampleLengths
062
175
261
360
462
526
653
76
8105
928
1044
115
1261
1337
1423
1515
98.64% Passive voice overuse
Target: ≤2% passive sentences
passiveCount1
totalSentences53
matches
0"being caught"
91.60% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount2
totalVerbs123
matches
0"was going"
1"were standing"
100.00% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount0
semicolonCount0
flaggedSentences0
totalSentences53
ratio0
matches(empty)
100.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount724
adjectiveStacks0
stackExamples(empty)
adverbCount20
adverbRatio0.027624309392265192
lyAdverbCount2
lyAdverbRatio0.0027624309392265192
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
mean13.64
std9.92
cv0.727
sampleLengths
020
132
25
35
412
54
610
749
819
918
105
1119
1213
137
1418
155
1617
177
1812
1919
207
2117
223
2323
2410
253
263
273
2820
2914
306
3148
3210
3319
347
3521
3628
375
3810
398
403
4118
425
437
4415
4516
4623
4711
4816
494
83.65% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats4
diversityRatio0.5471698113207547
totalSentences53
uniqueOpeners29
100.00% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount3
totalSentences53
matches
0"Twice he had glanced back."
1"Twice he had not hurried."
2"Somewhere far beneath her, a"
ratio0.057
99.25% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount16
totalSentences53
matches
0"Her left wrist ached under"
1"She had told the desk"
2"She had not told anyone"
3"Her breath clouded and vanished."
4"He reached into his pocket"
5"It was small and pale,"
6"Her pulse hammered in her"
7"He had not been able"
8"She had not believed a"
9"She pulled out her phone."
10"She tried the radio clipped"
11"She thought of Morris's hands."
12"It moved under her palm"
13"She took out her torch,"
14"Her eyes would adjust."
15"Her hand found the cold"
ratio0.302
100.00% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount32
totalSentences53
matches
0"The rain had turned Camden"
1"Quinn kept her eyes on"
2"Her left wrist ached under"
3"She had told the desk"
4"She had not told anyone"
5"The man turned left off"
6"Quinn slowed at the mouth"
7"Her breath clouded and vanished."
8"The lane narrowed between a"
9"*Camden Town Station, Northern Line."
10"The grey coat stopped at"
11"He reached into his pocket"
12"It was small and pale,"
13"The lock clicked open without"
14"The man slipped through, and"
15"Quinn stood still."
16"Her pulse hammered in her"
17"Every instinct she had drilled"
18"He had not been able"
19"Quinn had read the report"
ratio0.604
100.00% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount2
totalSentences53
matches
0"Now there was a man"
1"If the man below had"
ratio0.038
75.89% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences32
technicalSentenceCount3
matches
0"Quinn kept her eyes on the grey coat ahead of her, forty yards off and moving with the unhurried stride of someone who knew he was not in danger of being caught…"
1"She had not told anyone about the photographs in the file, the ones of a man who looked like he had walked out of a Victorian engraving, or about the way the la…"
2"Three years ago, Dan Morris had walked into a basement in Hackney on a routine tip, and when Quinn reached the bottom of the stairs there had been nothing there…"
100.00% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags0
uselessAdditionCount0
matches(empty)
100.00% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags0
96.4163%