Run: 2026-09-02-01M1GX69RA597Y13JRFBN15S1C

Run Details

Duration:
4m 35s
Cost:
$0.035981
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 bled into the gutters, turning the rain the color of pond water. Quinn had been watching it for three weeks, that sign — THE RAVEN'S NEST, humming above a door on a Soho street that most people walked past without slowing — and in three weeks she had learned exactly one useful thing: nobody who went in ever came out in a hurry. At 23:47 by the worn leather watch on her left wrist, that changed. The medic came out fast. She sat up in the driver's seat. Tomás Herrera, twenty-nine, olive-skinned, short curls plastered flat by the rain, a battered leather bag in his fist. He'd been inside for forty minutes. Through the bar's front window she'd watched him do what he always did — sit with his back to the maps and black-and-white photographs covering Silas's walls, drink nothing, talk to no one, leave. Only tonight he hadn't lingered on the doorstep to check the sky. Tonight he walked. Quinn gave him a count of ten, then followed. He walked like a man who had been taught to walk — paramedic, she knew, before the NHS threw him out for treating the wrong patients — and he used every shop window between the bar and Wardour Street as a mirror. She hung back, let a hen party and a knot of smokers pass between them, kept her stride loose. Eighteen years of this. She could tail a man in her sleep. At the corner of Wardour he lifted a hand, and a black cab swallowed him. She ran for her car. The chase went north in the worst way, in traffic, rain hammering the roof while the wipers thumped their metronome and the cab's brake lights bloomed and faded two vehicles ahead. Charing Cross Road. St Giles. The cab ran the amber at the Euston Road junction and she ran it too, and by the time they rolled into Camden High Street the streets had emptied to shuttered market stalls and sodium light and water sheeting off the railway bridge. The cab slowed at the lights by the station. In its rear window, a face turned. Warm brown eyes found hers across fifty yards of rain, and she watched the exact moment Tomás Herrera understood what she was. He was out of the cab before it stopped, banknote flung through the window, running north along the High Street with the leather bag bouncing against his hip. Quinn left her car in the middle of the street with the hazards ticking and went after him. "Tomás Herrera!" Her voice cracked over the rain. "Met Police! Stop!" He didn't stop. He ran the way she'd suspected he would — not like a criminal, not wild, but like a man late for something that mattered, cutting between the market's chained gates and through a gap in the hoarding that she would never have found in daylight. Beyond it, cobbled horse tunnels ran beneath the Stables, low brick throats that funneled the rain into silver ropes off their arches. His footsteps drummed ahead of her, and she tracked them by sound as much as sight, one hand brushing wet brick to keep her bearings. He vaulted a barrier. His sleeve rode up, and in a strobe of sodium light she saw the pale seam of the scar along his left forearm, old and deliberate. Then he was down the steps at Camden Lock and onto the towpath, where the canal lay black and swollen and the rain needled its surface to static. Quinn followed. Her lungs burned in the honest, familiar way. Forty-one years old and she still ran the way the Army had taught her, short strides, shoulders down, breath metered — and he was still pulling away, younger, faster, lighter. He didn't look back now. He'd stopped checking. Whatever door he was running for, he was certain it would be open. Chalk Farm Road. A bus shelter, a late reveller who swore at them both. Then the arches — the great black brick viaduct that carried the railway over Camden, arch after arch of shuttered steel and darkness — and Herrera cut left between two of them, and for four seconds she lost him completely. She pulled up at the mouth of the gap, breath sawing, one hand flat against brick slick with rain. A dead end. Bollards, a dumpster, a wall of London clay held back by a retaining wall a hundred years old. She'd lost him. Three weeks of sitting outside that bar, and she'd lost the first live thread she'd touched since— Light moved at the far end. Not electric light. Warmer. It spilled from a black iron door set into the retaining wall, and above the door, half ghosted by a century of grime, she made out a ring of dirty tiles and a row of letters with gaps where the rest had fallen away. AM EN. She was standing beneath the bones of an Underground station that wasn't on any map she'd ever been issued. Herrera stood at the door with his back to her, head bowed. In his raised fist, something pale caught the light — a chip of carved bone, thumbnail-sized, which he pressed into a brass slot worn smooth by ten thousand hands before his. "Turn around, Tommy," she called. Her voice came out lower than she intended, roughened by the run. "It's a door. That's all it is. We can do this on the pavement instead." He turned. Rain ran off his curls and down the sharp line of his jaw, and the Saint Christopher medallion at his throat threw back the warm light like a struck match. He looked at her the way paramedics looked at casualties they'd already assessed — sorry, and certain. "You don't want what's down here," he said. "Neither do you, apparently, or you'd have been quieter leaving." Something moved behind his eyes — almost a laugh, quickly buried. "Go home, Detective. Whatever you think the Nest's people have done, I just stitch them up. That's all I do." "Three weeks I've watched that bar, and I've never gotten past the front room. Tonight you walk out with a bag at midnight and run four streets from a cab." She took one step closer, boots quiet on the wet stone. "So no. I don't think it's just stitching." "Then hear me on this." He glanced at the door, and when he looked back his voice had changed — flat, and quick, and afraid in a way she didn't think was for himself. "Wait for your backup if you want. It won't matter. This place won't be here tomorrow night. It won't be here in an hour." The door behind him sagged open on complaining hinges, exhaling warm air that smelled of candle tallow and wet stone and, beneath both, something faint and sweet and wrong, like flowers left too long in a vase. Herrera stepped backward into the light. "Last chance to walk away," he said, and was gone. The door began to swing shut. Quinn keyed her radio. "Quinn to Camden control. Require units, railway arches off Chalk Farm Road, near the old station—" Static chewed the reply into something about fifteen minutes, twenty if the roads were bad. Fifteen minutes. She looked at the door, narrowing. Thought of the dispatcher's tone, the way her requests had been answered for three years now, patiently, the way you answer someone you've stopped believing. Three years since Morris. Three years of files with holes in them, of a partner's death written up as cardiac arrest by a coroner who hadn't seen the room, of doors in this city that opened for other people and never for her. She thought: I have spent three years standing outside. She took the small torch from her coat, checked the weight of the canister on her belt, and left the radio squawking on a bollard behind her. The gap in the door was down to a foot. She turned sideways and went through it, iron grazing her shoulder, into a stairwell descending into warm breathing dark. Far below, she could hear it now — a murmur like a market waking, a bell, music from something with strings — and behind her the door met its frame with a soft, deliberate click. Like bone snapping. Quinn switched on her torch and went down the stairs.
created_at"2026-09-02T11:13:43.188Z" 9/2/2026, 11:13:43 AM
model"z-ai/glm-5.3-20260816"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency2067
moderation_latency(null)
generation_time274764
tokens_prompt888
tokens_completion9030
native_tokens_prompt819
native_tokens_completion8116
native_tokens_completion_images(null)
native_tokens_reasoning6365
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)
usage0.03598148
router(null)
user_agent"langchainjs-openai/1.0.0 ((node/v24.19.0; linux; x64))"
http_referer(null)
request_id"req-1788347623-53efIIe64bmEHdLTLA7A"
session_id(null)
preset_id(null)
api_type"completions"
id"gen-1788347623-xetTNBi5HrEkEYn6JaHj"
upstream_id"202609021913438b84284af5114152"
provider_responses
0
endpoint_id"db975786-e7f6-4838-9e56-3e0b77f1bdc2"
id"202609021913438b84284af5114152"
is_byokfalse
latency2067
model_permaslug"z-ai/glm-5.3-20260816"
provider_name"Z.AI"
status200
total_cost0.03598148
cache_discount0.00087552
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
totalTags7
adverbTagCount0
adverbTags(empty)
dialogueSentences13
tagDensity0.538
leniency1
rawRatio0
effectiveRatio0
92.81% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount1391
totalAiIsmAdverbs2
found
0
adverb"completely"
count1
1
adverb"quickly"
count1
highlights
0"completely"
1"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)
85.62% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount1391
totalAiIsms4
found
0
word"footsteps"
count1
1
word"familiar"
count1
2
word"electric"
count1
3
word"weight"
count1
highlights
0"footsteps"
1"familiar"
2"electric"
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
narrationSentences83
matches(empty)
100.00% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount1
hedgeCount1
narrationSentences83
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)
analyzedSentences89
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
repeatedSegmentCount0
maxSentenceWordsSeen49
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans0
markdownWords0
totalWords1406
ratio0
matches(empty)
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions4
unquotedAttributions0
matches(empty)
100.00% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions45
wordCount1259
uniqueNames25
maxNameDensity0.48
worstName"Quinn"
maxWindowNameDensity1.5
worstWindowName"Street"
discoveredNames
Soho1
Herrera5
Silas1
Wardour2
Street3
Cross1
Road3
Giles1
Euston1
Camden3
High2
Tomás2
Stables1
Lock1
Army1
Farm1
London1
Light1
Underground1
Saint1
Christopher1
Fifteen1
Morris1
Quinn6
Three3
persons
0"Herrera"
1"Silas"
2"Tomás"
3"Army"
4"Light"
5"Saint"
6"Christopher"
7"Morris"
8"Quinn"
places
0"Soho"
1"Wardour"
2"Street"
3"Cross"
4"Road"
5"Giles"
6"Euston"
7"Camden"
8"High"
9"Farm"
10"London"
11"Three"
globalScore1
windowScore1
100.00% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences58
glossingSentenceCount0
matches(empty)
57.75% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches2
per1kWords1.422
wordCount1406
matches
0"not like a criminal, not wild, but like a man late for something"
1"not wild, but like a man late for something"
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount1
totalSentences89
matches
0"hoarding that she"
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs38
mean37
std26.56
cv0.718
sampleLengths
066
113
25
380
49
573
615
75
879
99
1029
1128
1218
1311
1495
1558
1661
1754
1860
196
2069
2143
2232
2349
248
2510
2631
2749
2858
2943
3010
316
3268
3352
3427
3564
363
3710
88.35% Passive voice overuse
Target: ≤2% passive sentences
passiveCount4
totalSentences83
matches
0"been taught"
1"been issued"
2"was gone"
3"been answered"
97.96% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount3
totalVerbs196
matches
0"was still pulling"
1"was running"
2"was standing"
0.00% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount16
semicolonCount0
flaggedSentences12
totalSentences89
ratio0.135
matches
0"Quinn had been watching it for three weeks, that sign — THE RAVEN'S NEST, humming above a door on a Soho street that most people walked past without slowing — and in three weeks she had learned exactly one useful thing: nobody who went in ever came out in a hurry."
1"Through the bar's front window she'd watched him do what he always did — sit with his back to the maps and black-and-white photographs covering Silas's walls, drink nothing, talk to no one, leave."
2"He walked like a man who had been taught to walk — paramedic, she knew, before the NHS threw him out for treating the wrong patients — and he used every shop window between the bar and Wardour Street as a mirror."
3"He ran the way she'd suspected he would — not like a criminal, not wild, but like a man late for something that mattered, cutting between the market's chained gates and through a gap in the hoarding that she would never have found in daylight."
4"Forty-one years old and she still ran the way the Army had taught her, short strides, shoulders down, breath metered — and he was still pulling away, younger, faster, lighter."
5"Then the arches — the great black brick viaduct that carried the railway over Camden, arch after arch of shuttered steel and darkness — and Herrera cut left between two of them, and for four seconds she lost him completely."
6"Three weeks of sitting outside that bar, and she'd lost the first live thread she'd touched since—"
7"In his raised fist, something pale caught the light — a chip of carved bone, thumbnail-sized, which he pressed into a brass slot worn smooth by ten thousand hands before his."
8"He looked at her the way paramedics looked at casualties they'd already assessed — sorry, and certain."
9"Something moved behind his eyes — almost a laugh, quickly buried."
10"\"Then hear me on this.\" He glanced at the door, and when he looked back his voice had changed — flat, and quick, and afraid in a way she didn't think was for himself."
11"Far below, she could hear it now — a murmur like a market waking, a bell, music from something with strings — and behind her the door met its frame with a soft, deliberate click."
100.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount1250
adjectiveStacks0
stackExamples(empty)
adverbCount25
adverbRatio0.02
lyAdverbCount6
lyAdverbRatio0.0048
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences89
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences89
mean15.8
std12.86
cv0.814
sampleLengths
015
151
213
35
47
518
66
734
812
93
109
1142
1219
134
148
1515
165
1731
183
192
2043
219
227
2322
2428
2518
268
273
283
2945
3022
3125
324
3326
3428
352
368
3730
385
393
4013
413
4211
4340
4419
453
4618
473
4817
496
75.66% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats6
diversityRatio0.4943820224719101
totalSentences89
uniqueOpeners44
100.00% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount3
totalSentences75
matches
0"Only tonight he hadn't lingered"
1"Then he was down the"
2"Then the arches — the"
ratio0.04
65.33% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount29
totalSentences75
matches
0"She sat up in the"
1"He'd been inside for forty"
2"He walked like a man"
3"She hung back, let a"
4"She could tail a man"
5"She ran for her car."
6"He was out of the"
7"Her voice cracked over the"
8"He didn't stop."
9"He ran the way she'd"
10"His footsteps drummed ahead of"
11"He vaulted a barrier."
12"His sleeve rode up, and"
13"Her lungs burned in the"
14"He didn't look back now."
15"He'd stopped checking."
16"She pulled up at the"
17"She'd lost him."
18"It spilled from a black"
19"She was standing beneath the"
ratio0.387
93.33% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount55
totalSentences75
matches
0"The green neon bled into"
1"Quinn had been watching it"
2"The medic came out fast."
3"She sat up in the"
4"Tomás Herrera, twenty-nine, olive-skinned, short"
5"He'd been inside for forty"
6"Tonight he walked."
7"Quinn gave him a count"
8"He walked like a man"
9"She hung back, let a"
10"She could tail a man"
11"She ran for her car."
12"The chase went north in"
13"The cab ran the amber"
14"The cab slowed at the"
15"He was out of the"
16"Quinn left her car in"
17"Her voice cracked over the"
18"He didn't stop."
19"He ran the way she'd"
ratio0.733
0.00% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount0
totalSentences75
matches(empty)
ratio0
23.81% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences42
technicalSentenceCount7
matches
0"Quinn had been watching it for three weeks, that sign — THE RAVEN'S NEST, humming above a door on a Soho street that most people walked past without slowing — a…"
1"He walked like a man who had been taught to walk — paramedic, she knew, before the NHS threw him out for treating the wrong patients — and he used every shop wi…"
2"He ran the way she'd suspected he would — not like a criminal, not wild, but like a man late for something that mattered, cutting between the market's chained g…"
3"Beyond it, cobbled horse tunnels ran beneath the Stables, low brick throats that funneled the rain into silver ropes off their arches."
4"Then the arches — the great black brick viaduct that carried the railway over Camden, arch after arch of shuttered steel and darkness — and Herrera cut left bet…"
5"The door behind him sagged open on complaining hinges, exhaling warm air that smelled of candle tallow and wet stone and, beneath both, something faint and swee…"
6"Three years of files with holes in them, of a partner's death written up as cardiac arrest by a coroner who hadn't seen the room, of doors in this city that ope…"
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
totalTags3
fancyCount0
fancyTags(empty)
dialogueSentences13
tagDensity0.231
leniency0.462
rawRatio0
effectiveRatio0
86.0210%