Run: 2026-09-02-01M1GSEWJF769AESXQDZQCV326

Run Details

Duration:
3m 20s
Cost:
$0.001295
Provider:
Z.AI

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 green neon of the Raven's Nest bled across the wet pavement like something spilled, and Tomás Herrera came out of the door beneath it moving fast. Harlow Quinn had been watching that door for eleven nights from a borrowed greasy spoon across Dean Street, and she knew the difference between a man leaving a pub and a man running. Herrera had his collar up, a canvas trauma bag slung across his body, and the moment he stepped under the sign his head turned — a small, precise sweep of the street, the kind she did herself — and found her face in the café window. Forty yards of rain between them. His expression didn't change. He simply turned and went. Quinn was through the café door before the chair stopped rocking. "Police! Stop!" Herrera didn't stop. He went left onto Old Compton Street, cutting between a shuttered flower stall and a pack of stumbling partygoers, and Quinn gave chase with the rain already flattening her cropped hair to her skull and the worn leather strap of her watch biting into her wrist. Eleven thirty-two. She'd remember the time the way she remembered all the times that mattered. Eighteen years on the job had taught her the arithmetic of foot chases. He was twenty-nine, a former paramedic, and he ran like someone who'd spent a decade sprinting to cardiac arrests — economical, no wasted motion, head level. She was forty-one and it was pissing down and Soho's pavements were slick as oiled glass. But she'd grown up on these streets too, and she had something he didn't: nothing left to lose that she hadn't already buried. They tore up Wardour Street. A black cab laid on its horn and Herrera skipped around its bumper without breaking stride, and here was the thing Quinn filed away even as her lungs started to burn — he swerved wide around a drunk man slumped in a doorway, one hand grazing the man's shoulder to steady him as he passed. Careful. Even running for his life, he was careful of people. That was a man with a code, and men with codes made mistakes you could follow. He ducked down a service alley behind the restaurants, and in the close dark between the buildings Quinn got her first real look at him. His sleeve had ridden up past the scar on his left forearm, a pale rope of tissue she'd seen in the file photos, and the Saint Christopher medallion bounced free of his collar and threw a small mad light as he ran. But it was the bag that snagged her attention. Rain struck the canvas and ran off it wrong — beading, hissing, sliding away like it didn't want to touch the thing — and through the gap of the half-open zipper she caught a green glow, soft and wet, the exact color of the Raven's Nest sign. Somewhere in the back of her skull, a door she kept double-locked rattled once. Three years. Morris. The case that had no ending. She slammed the door shut and ran faster. "Police! Herrera! You're done running!" He shot across Oxford Street between two buses — she nearly died following him, a taxi's wiper blades an arm's length from her hip — and then he was plunging down the steps into Tottenham Court Road station, tapping through the barriers with a contactless card in one fluid motion. She slapped her warrant card against the reader, heard the chirp, vaulted after him. Instead of going down to the platforms, Herrera shouldered open a grey fire door marked STAFF ONLY — NO ENTRY. It wasn't locked. She noted that too, even as she went through it into darkness and the door swung shut behind her, sealing away the sounds of the living city. Service corridors. Red bulbs in caged fittings. The air tasted of dust and hot rail and something older, mineral, like the inside of a cave. Quinn clicked on her phone torch with her thumb and kept her eyes on the bouncing light of Herrera's heels. To her left, a Northern line train roared past behind a wall, the whole world shuddering, and Herrera didn't even flinch. He knew this dark. That frightened her more than the dark itself. Down a rusted stairwell, along a platform that hadn't seen a passenger in sixty years, and then he dropped onto the track bed and kept running. She followed, gravel crunching underfoot, one hand trailing the damp tunnel wall. Her breath came in blades now. Her knees kept their complaints to themselves out of professional courtesy. Twice he glanced back. Both times, she realized later, he wasn't checking whether she'd quit. He was checking whether she'd kept up. The distance between them never grew. It never shrank, either. He was pacing her — herding her, a cold voice suggested — and she told that voice to shut up and ran. The tunnel bored north. The temperature dropped. The sounds changed. Somewhere behind the brick there were voices, faint and layered, speaking something with no edges she could recognize, and a bell rang once with a sound like a coin dropped down a well, rising away from her instead of falling. Her radio had been dead static since the fire door. She'd given dispatch her location at Oxford Street; that bought her a search starting in the wrong place, hours from now, if anyone thought to look underground at all. Her watch said 11:51 when the tunnel opened out. An abandoned station spread before her, arches of glazed white tile furred with grime, and on the walls the ghost of the station's name remained — the outline where each enamel letter had been pried away, so that the tile remembered the word even if no one else did. Iron barriers sealed the far end of the platform, a turnstile of black metal older than anything the Underground had ever installed, and beyond it she could hear the market. Hundreds of voices. A saw grinding bone. Music played on instruments that made her back teeth ache. Herrera stood at the turnstile. He took something from his pocket and held it up to the light: a small white token, carved, unmistakably bone, warm-looking as a knuckle. He pressed it to the iron. Something deep in the mechanism turned over with a groan, and the barrier swung for him. He paused on the threshold. He looked back at her — rain-soaked, torch shaking slightly in her hand, chest heaving — and there was no triumph in his face. There was something worse. Pity. "You can still go back, Detective," he said. His Sevillian accent curled around the words like smoke. Then he set the bone token on the flat of the turnstile, in reach of the platform, and walked through. The barrier did not close behind him. It waited, patient as a held breath. Quinn stopped ten feet away. Every protocol she had ever obeyed stood at her shoulder in that moment, uniform and sane. Call it in. Withdraw. Establish a perimeter. Let the analysts earn their pay. It was the correct play, and she had watched the correct play carried Morris's coffin. Her radio hissed nothing. The voices beyond the barrier churned. The token sat on the iron, white as a finger, and when she picked it up it was warm — warm as something freshly alive, warm in a way metal and bone in a cold tunnel had no right to be — and the wrongness of it traveled up her arm and settled behind her sternum, in the same place the unanswerable questions about Morris had lived for three years. Herrera's footsteps faded into the roar of the market. Her one lead in three years. The man who knew what her partner had walked into, or knew the people who knew, down in the dark where the rain couldn't follow. Quinn checked her watch. 11:53. She'd remember this time too. She pressed the token to the iron and stepped through.
created_at"2026-09-02T10:08:30.297Z" 9/2/2026, 10:08:30 AM
model"z-ai/glm-5.3-flash-20260826"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency4346
moderation_latency(null)
generation_time199854
tokens_prompt888
tokens_completion5763
native_tokens_prompt819
native_tokens_completion5118
native_tokens_completion_images(null)
native_tokens_reasoning3472
native_tokens_cached768
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"stop"
service_tier(null)
usage0.001294845
router(null)
user_agent"langchainjs-openai/1.0.0 ((node/v24.19.0; linux; x64))"
http_referer(null)
request_id"req-1788343710-TuhXteG9ilJeQSKsl0JX"
session_id(null)
preset_id(null)
api_type"completions"
id"gen-1788343710-GKck8xuJyndKtYnc4lgi"
upstream_id"20260902180830d68788065c6542f8"
provider_responses
0
endpoint_id"8e9fe48b-2f91-41c3-a8a7-e4a93a8c4ff0"
id"20260902180830d68788065c6542f8"
is_byokfalse
latency4346
model_permaslug"z-ai/glm-5.3-flash-20260826"
provider_name"Z.AI"
status200
total_cost0.001294845
cache_discount0.00009216
upstream_inference_cost0
provider_name"Z.AI"
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
totalTags1
adverbTagCount0
adverbTags(empty)
dialogueSentences3
tagDensity0.333
leniency0.667
rawRatio0
effectiveRatio0
96.23% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount1326
totalAiIsmAdverbs1
found
0
adverb"slightly"
count1
highlights
0"slightly"
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)
92.46% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount1326
totalAiIsms2
found
0
word"churned"
count1
1
word"footsteps"
count1
highlights
0"churned"
1"footsteps"
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
narrationSentences93
matches(empty)
81.41% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount3
hedgeCount1
narrationSentences93
filterMatches
0"watch"
hedgeMatches
0"started to"
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences95
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
repeatedSegmentCount0
maxSentenceWordsSeen68
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans0
markdownWords0
totalWords1342
ratio0
matches(empty)
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions3
unquotedAttributions0
matches(empty)
100.00% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions45
wordCount1329
uniqueNames21
maxNameDensity0.68
worstName"Herrera"
maxWindowNameDensity1.5
worstWindowName"Herrera"
discoveredNames
Raven2
Nest2
Tomás1
Herrera9
Quinn8
Dean1
Street5
Old1
Compton1
Soho1
Wardour1
Saint1
Christopher1
Oxford2
Tottenham1
Court1
Road1
Northern1
Underground1
Sevillian1
Morris3
persons
0"Raven"
1"Nest"
2"Tomás"
3"Herrera"
4"Quinn"
5"Saint"
6"Christopher"
7"Underground"
8"Morris"
places
0"Dean"
1"Street"
2"Old"
3"Compton"
4"Soho"
5"Wardour"
6"Oxford"
7"Tottenham"
8"Court"
9"Road"
globalScore1
windowScore1
100.00% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences61
glossingSentenceCount0
matches(empty)
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches0
per1kWords0
wordCount1342
matches(empty)
61.40% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount3
totalSentences95
matches
0"watching that door"
1"lose that she"
2"told that voice"
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs26
mean51.62
std32.04
cv0.621
sampleLengths
027
194
213
364
478
587
6123
731
85
964
1050
1178
1255
1354
1489
159
1696
1751
1834
1951
205
2144
2280
2340
2410
2510
100.00% Passive voice overuse
Target: ≤2% passive sentences
passiveCount1
totalSentences93
matches
0"been pried"
48.48% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount5
totalVerbs220
matches
0"was pissing"
1"was plunging"
2"wasn't checking"
3"was checking"
4"was pacing"
0.00% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount16
semicolonCount1
flaggedSentences11
totalSentences95
ratio0.116
matches
0"Herrera had his collar up, a canvas trauma bag slung across his body, and the moment he stepped under the sign his head turned — a small, precise sweep of the street, the kind she did herself — and found her face in the café window."
1"He was twenty-nine, a former paramedic, and he ran like someone who'd spent a decade sprinting to cardiac arrests — economical, no wasted motion, head level."
2"A black cab laid on its horn and Herrera skipped around its bumper without breaking stride, and here was the thing Quinn filed away even as her lungs started to burn — he swerved wide around a drunk man slumped in a doorway, one hand grazing the man's shoulder to steady him as he passed."
3"Rain struck the canvas and ran off it wrong — beading, hissing, sliding away like it didn't want to touch the thing — and through the gap of the half-open zipper she caught a green glow, soft and wet, the exact color of the Raven's Nest sign."
4"He shot across Oxford Street between two buses — she nearly died following him, a taxi's wiper blades an arm's length from her hip — and then he was plunging down the steps into Tottenham Court Road station, tapping through the barriers with a contactless card in one fluid motion."
5"Instead of going down to the platforms, Herrera shouldered open a grey fire door marked STAFF ONLY — NO ENTRY."
6"He was pacing her — herding her, a cold voice suggested — and she told that voice to shut up and ran."
7"She'd given dispatch her location at Oxford Street; that bought her a search starting in the wrong place, hours from now, if anyone thought to look underground at all."
8"An abandoned station spread before her, arches of glazed white tile furred with grime, and on the walls the ghost of the station's name remained — the outline where each enamel letter had been pried away, so that the tile remembered the word even if no one else did."
9"He looked back at her — rain-soaked, torch shaking slightly in her hand, chest heaving — and there was no triumph in his face."
10"The token sat on the iron, white as a finger, and when she picked it up it was warm — warm as something freshly alive, warm in a way metal and bone in a cold tunnel had no right to be — and the wrongness of it traveled up her arm and settled behind her sternum, in the same place the unanswerable questions about Morris had lived for three years."
100.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount1320
adjectiveStacks0
stackExamples(empty)
adverbCount38
adverbRatio0.02878787878787879
lyAdverbCount6
lyAdverbRatio0.004545454545454545
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences95
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences95
mean14.13
std14.13
cv1
sampleLengths
027
133
246
36
44
55
611
72
83
946
102
1113
1213
1326
1416
1523
165
1755
181
1910
2016
2125
2242
239
2447
2514
262
271
286
298
305
3150
3214
3320
343
3527
362
375
3818
3920
4021
414
428
4326
4412
456
4611
474
4811
497
70.57% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats7
diversityRatio0.46808510638297873
totalSentences94
uniqueOpeners44
100.00% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount6
totalSentences84
matches
0"Even running for his life,"
1"Somewhere in the back of"
2"Instead of going down to"
3"Twice he glanced back."
4"Somewhere behind the brick there"
5"Then he set the bone"
ratio0.071
53.33% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount35
totalSentences84
matches
0"His expression didn't change."
1"He simply turned and went."
2"He went left onto Old"
3"She'd remember the time the"
4"He was twenty-nine, a former"
5"She was forty-one and it"
6"They tore up Wardour Street."
7"He ducked down a service"
8"His sleeve had ridden up"
9"She slammed the door shut"
10"He shot across Oxford Street"
11"She slapped her warrant card"
12"It wasn't locked."
13"She noted that too, even"
14"He knew this dark."
15"She followed, gravel crunching underfoot,"
16"Her breath came in blades"
17"Her knees kept their complaints"
18"He was checking whether she'd"
19"It never shrank, either."
ratio0.417
61.19% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount67
totalSentences84
matches
0"The green neon of the"
1"Harlow Quinn had been watching"
2"Herrera had his collar up,"
3"His expression didn't change."
4"He simply turned and went."
5"Quinn was through the café"
6"Herrera didn't stop."
7"He went left onto Old"
8"She'd remember the time the"
9"He was twenty-nine, a former"
10"She was forty-one and it"
11"They tore up Wardour Street."
12"A black cab laid on"
13"That was a man with"
14"He ducked down a service"
15"His sleeve had ridden up"
16"Rain struck the canvas and"
17"The case that had no"
18"She slammed the door shut"
19"He shot across Oxford Street"
ratio0.798
59.52% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount1
totalSentences84
matches
0"To her left, a Northern"
ratio0.012
77.92% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences44
technicalSentenceCount4
matches
0"She'd remember the time the way she remembered all the times that mattered."
1"He was twenty-nine, a former paramedic, and he ran like someone who'd spent a decade sprinting to cardiac arrests — economical, no wasted motion, head level."
2"She'd given dispatch her location at Oxford Street; that bought her a search starting in the wrong place, hours from now, if anyone thought to look underground …"
3"Music played on instruments that made her back teeth ache."
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
totalTags1
fancyCount0
fancyTags(empty)
dialogueSentences3
tagDensity0.333
leniency0.667
rawRatio0
effectiveRatio0
86.7509%