Run: 2026-09-29-01M3P2EZ6AM52BMY6VVBWTA063

Run Details

Duration:
35.8s
Cost:
$0.036212
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
Rain came down on Camden like it had a grudge. Quinn ran through it with her coat flapping open and her shoes slapping black water out of the gutters, and she kept her eyes on the man forty yards ahead. Tomás Herrera ran well for someone carrying a medical bag. He kept it tucked against his ribs the way a rugby player carries a ball, and he took the corners wide and smooth. Twice she saw the gleam of the Saint Christopher medallion swing free of his collar and bounce against his chest. She had followed him from Soho. She had sat across from the Raven's Nest for two hours, watching the green neon bleed into the puddles, until Herrera came out of the door with the bag and a look on his face she recognized from her own mirror. It was the look of someone on the way to a job he wished he didn't have. She'd tailed the cab, then the Tube, then the long walk up Chalk Farm Road. He hadn't spotted her until a bus threw its headlights across the street and lit her up like a stage. He'd looked straight at her. Then he ran. "Mr. Herrera!" Her voice cracked off the shuttered shopfronts. "Police! Stop!" He didn't. She hadn't expected him to. He cut left down a service road behind a row of shuttered stalls, and she followed, her lungs burning. Eighteen years of service, and her knees had started keeping their own opinions. She fixed her attention the way she'd been trained to, narrowing everything to the next ten feet. Wet cobbles. A stack of crates. The pale flash of his sleeve, and beneath it, when he threw out an arm for balance, the long ridged scar on his forearm. He vaulted a low wall. She hit it with her palm and swung over, landing hard. Ahead, the service road dead-ended in a brick arch. Iron gates hung across it, chained and rusted, a city council notice zip-tied to the bars: DANGER. NO ENTRY. STATION CLOSED. It had been closed since before she joined the Met. Herrera slowed at the gates, and for one bright, hungry second she thought she had him. Then a figure stepped out of the shadow beside the arch. He was a big man in a waxed coat with the hood up, and he held something in one open hand that he didn't need to hold up. Herrera pressed his own palm against it. Something pale flashed. The big man nodded and hauled the gate inward on hinges that made no noise at all, and Herrera slipped through. Quinn caught one glimpse of a stairwell going down, lit orange and wavering, like a fire seen through water. The gate swung shut. She stopped ten feet away, chest heaving, rain running off the sharp line of her jaw. The doorman turned his hooded face toward her. Behind him, faint but unmistakable, came the sound of voices. Hundreds of them. Laughter, haggling, and under it a low hum that she felt in her back teeth. "Evening, officer," the man said pleasantly. She hadn't shown him a badge. She hadn't said a word. "A man just went through that gate," Quinn said. "I want to speak to him." "Lots of men go through lots of gates." He smiled. There was something wrong with his teeth, too even, too pale. "Token?" "I don't have a token." "Then you don't have a gate." He said it kindly, the way one might explain a bus timetable. Quinn stood in the rain and made herself think. Every rule she'd lived by said to stop here. Call it in. Get a warrant, get backup, get a team with vests and a battering ram. But she knew what she would say on the radio. *Suspect entered a disused Underground station via a gate that isn't there, guarded by a man who knew I was a police officer without being told.* She could hear the silence on the other end. She could hear what the superintendent would say afterward, in that reasonable voice, over that reasonable desk. And this wasn't the first door she'd been shut out of. Three years ago, Detective Sergeant Morris had walked through one, in a different rain, in a different part of the city. Quinn had been forty seconds behind him. She'd found the room empty, the window locked from inside, and Morris's coat on the floor with the pockets turned out. No body. No blood. No explanation she could put in a report without ending her career. She'd put in a different report, a careful one, and she had been lying by omission ever since. She'd spent three years pressing on that memory like a bruise. Herrera and his friends were the first thread she'd found that ran the same direction. Her left hand drifted to her wrist, and she found the worn leather strap of her watch and rubbed her thumb over it. It was a habit. It was the only one she allowed herself. The second hand ticked steadily under her thumb, unbothered by anything. If she walked away, the gate would close and stay closed. Herrera would go about his business in whatever world lay down those stairs, and she would go home to a flat with a single mug on the draining board and a case file she knew by heart. If she went down, no one knew where she was. *Forty seconds,* she thought. *Always forty seconds.* She reached into the inside pocket of her coat. The doorman's eyebrows lifted a fraction. Her fingers closed on the small, smooth disc she had carried there for three years, a piece of pale carved bone the size of a two-pence coin. She had found it in the drawer of Morris's desk, under a stack of takeaway menus, and had never shown it to anyone. Not to forensics, not to her superiors. It had a spiral scratched into one face and it was always cool to the touch, even now, even against her body heat. She held it up. The doorman looked at it for a long moment. The pleasantness slid off his face and left something older behind. "Where did you get that?" "Does it work?" "It's not yours." "That's not what I asked." He studied her, and the rain drummed on the brick above them. Somewhere below, a bell rang once, low and slow. At last he stepped aside, and the gate opened again without a sound. "It works," he said. "Doesn't mean you'll like what it opens." "I don't expect to." "Whoever gave you that," he said, "didn't give it to you for a visit." Quinn didn't answer. She put the bone back in her pocket, where it settled against her ribs like a second, colder heartbeat. She squared her shoulders in the old drill-hall way, chin level, spine straight, and stepped through. The air changed at once. The rain cut off behind her as if a hand had closed over it, and warmth rose up the stairwell, thick with smells she couldn't sort: woodsmoke, hot sugar, wet iron, something like lightning. The orange light came from lanterns hung along the tiled walls, and the old station signs were still there, cracked and yellowed. CAMDEN TOWN. MIND THE GAP. Someone had painted over half the letters with symbols she didn't recognize. At the bottom of the stairs the tunnel opened onto a platform, and the platform was full. Stalls crowded the old tracks. Cloaked figures haggled over jars that glowed. A woman sold vials of something dark from a tray hung round her neck, and a child with eyes too old for her face sat cross-legged beside a cage of birds that were not quite birds. Overhead, strings of lights swung in a wind that had no business in a tunnel. Every head that turned toward Quinn turned away again just a little too quickly. She didn't see Herrera. Then she did: forty yards down the platform, his dark curls bright under a lantern, the bag clutched to his chest as he slid between two stalls. He glanced back once. Their eyes met across the crowd, and what she saw in his face wasn't guilt. It was fear, and it wasn't fear of her. *Run,* his mouth said. Or maybe, *Don't.* Quinn drew a breath of that strange, smoky air, set her hand on the cold bone in her pocket, and walked into the Market.
created_at"2026-09-29T07:53:25.968Z" 9/29/2026, 7:53:25 AM
model"anthropic/claude-sonnet-5.5-20260928"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency3600
moderation_latency(null)
generation_time35737
tokens_prompt888
tokens_completion2111
native_tokens_prompt1266
native_tokens_completion3368
native_tokens_completion_images(null)
native_tokens_reasoning739
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"
usage0.036212
router(null)
user_agent"langchainjs-openai/1.0.0 ((node/v24.21.0; linux; x64))"
http_referer(null)
request_id"req-1790668405-emT9imLBOEnI8LVP6hft"
session_id(null)
preset_id(null)
api_type"completions"
id"gen-1790668405-hETddCkH0CufrjyhlNR6"
upstream_id"msg_011CfXNNEf3VFg7yfUSdZjbA"
provider_responses
0
endpoint_id"99aaad94-923b-4fc1-b763-271ed5486f7a"
id"msg_011CfXNNEf3VFg7yfUSdZjbA"
is_byokfalse
latency690
model_permaslug"anthropic/claude-sonnet-5.5-20260928"
provider_name"Claude Platform on AWS"
status200
total_cost0.036212
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
82.35% Adverbs in dialogue tags
Target: ≤10% dialogue tags with adverbs
totalTags7
adverbTagCount1
adverbTags
0"the man said pleasantly [pleasantly]"
dialogueSentences17
tagDensity0.412
leniency0.824
rawRatio0.143
effectiveRatio0.118
96.47% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount1417
totalAiIsmAdverbs1
found
0
adverb"quickly"
count1
highlights
0"quickly"
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)
89.41% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount1417
totalAiIsms3
found
0
word"wavering"
count1
1
word"silence"
count1
2
word"warmth"
count1
highlights
0"wavering"
1"silence"
2"warmth"
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
narrationSentences111
matches(empty)
100.00% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount3
hedgeCount0
narrationSentences111
filterMatches
0"notice"
1"think"
2"watch"
hedgeMatches(empty)
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences121
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
repeatedSegmentCount0
maxSentenceWordsSeen41
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans5
markdownWords33
totalWords1417
ratio0.023
matches
0"Suspect entered a disused Underground station via a gate that isn't there, guarded by a man who knew I was a police officer without being told."
1"Forty seconds,"
2"Always forty seconds."
3"Run,"
4"Don't."
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions12
unquotedAttributions0
matches(empty)
100.00% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions34
wordCount1337
uniqueNames18
maxNameDensity0.6
worstName"Herrera"
maxWindowNameDensity1.5
worstWindowName"Herrera"
discoveredNames
Camden1
Herrera8
Saint1
Christopher1
Soho1
Raven1
Nest1
Tube1
Chalk1
Farm1
Road1
Met1
Quinn8
Underground1
Detective1
Sergeant1
Morris3
Market1
persons
0"Herrera"
1"Saint"
2"Christopher"
3"Quinn"
4"Sergeant"
5"Morris"
places
0"Soho"
1"Raven"
2"Chalk"
3"Farm"
4"Road"
5"Market"
globalScore1
windowScore1
85.06% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences77
glossingSentenceCount2
matches
0"something like lightning"
1"not quite birds"
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches0
per1kWords0
wordCount1417
matches(empty)
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount1
totalSentences121
matches
0"on that memory"
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs44
mean32.2
std29.98
cv0.931
sampleLengths
040
153
299
38
411
57
679
716
856
911
1078
114
1252
136
1411
1515
1622
175
1818
199
2088
2194
2226
2346
2448
2510
267
2795
284
2925
303
313
325
3334
3411
354
3614
3738
3878
3917
4077
4159
427
4324
95.78% Passive voice overuse
Target: ≤2% passive sentences
passiveCount3
totalSentences111
matches
0"been trained"
1"been closed"
2"being told"
100.00% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount0
totalVerbs221
matches(empty)
100.00% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount0
semicolonCount0
flaggedSentences0
totalSentences121
ratio0
matches(empty)
100.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount1342
adjectiveStacks0
stackExamples(empty)
adverbCount37
adverbRatio0.027570789865871834
lyAdverbCount5
lyAdverbRatio0.0037257824143070045
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences121
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences121
mean11.71
std8.64
cv0.738
sampleLengths
010
130
210
323
420
56
641
717
815
920
105
113
129
132
142
155
1619
1713
1817
192
204
2124
225
2311
249
2517
262
272
2810
2916
3011
3128
327
333
3421
3519
364
3716
388
3910
403
4115
426
436
445
459
466
4710
4811
491
68.04% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats11
diversityRatio0.4628099173553719
totalSentences121
uniqueOpeners56
100.00% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount6
totalSentences100
matches
0"Twice she saw the gleam"
1"Then he ran."
2"Then a figure stepped out"
3"*Always forty seconds.*"
4"Somewhere below, a bell rang"
5"Then she did: forty yards"
ratio0.06
68.00% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount38
totalSentences100
matches
0"He kept it tucked against"
1"She had followed him from"
2"She had sat across from"
3"It was the look of"
4"She'd tailed the cab, then"
5"He hadn't spotted her until"
6"He'd looked straight at her."
7"Her voice cracked off the"
8"She hadn't expected him to."
9"He cut left down a"
10"She fixed her attention the"
11"He vaulted a low wall."
12"She hit it with her"
13"It had been closed since"
14"He was a big man"
15"She stopped ten feet away,"
16"She hadn't shown him a"
17"She hadn't said a word."
18"He said it kindly, the"
19"She could hear what the"
ratio0.38
100.00% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount71
totalSentences100
matches
0"Rain came down on Camden"
1"Quinn ran through it with"
2"Tomás Herrera ran well for"
3"He kept it tucked against"
4"She had followed him from"
5"She had sat across from"
6"It was the look of"
7"She'd tailed the cab, then"
8"He hadn't spotted her until"
9"He'd looked straight at her."
10"Her voice cracked off the"
11"She hadn't expected him to."
12"He cut left down a"
13"She fixed her attention the"
14"A stack of crates."
15"The pale flash of his"
16"He vaulted a low wall."
17"She hit it with her"
18"It had been closed since"
19"Herrera slowed at the gates,"
ratio0.71
100.00% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount2
totalSentences100
matches
0"If she walked away, the"
1"If she went down, no"
ratio0.02
95.24% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences60
technicalSentenceCount4
matches
0"Quinn ran through it with her coat flapping open and her shoes slapping black water out of the gutters, and she kept her eyes on the man forty yards ahead."
1"*Suspect entered a disused Underground station via a gate that isn't there, guarded by a man who knew I was a police officer without being told.* She could hear…"
2"The rain cut off behind her as if a hand had closed over it, and warmth rose up the stairwell, thick with smells she couldn't sort: woodsmoke, hot sugar, wet ir…"
3"A woman sold vials of something dark from a tray hung round her neck, and a child with eyes too old for her face sat cross-legged beside a cage of birds that we…"
100.00% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags7
uselessAdditionCount0
matches(empty)
100.00% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags5
fancyCount0
fancyTags(empty)
dialogueSentences17
tagDensity0.294
leniency0.588
rawRatio0
effectiveRatio0
96.0122%