Run: 2026-10-27-01M5YEAA0XYVZSZJS0X8VB0VTV

Run Details

Duration:
6m 10s
Cost:
$0.089598
Provider:
Moonshot AI

Model input

System
You are an expert fiction writer. Always keep the following rules in mind: - Write in past tense and use General English spelling, grammar, and colloquialisms/slang. - Write in active voice - Always follow the "show, don't tell" principle. - Avoid adverbs and cliches and overused/commonly used phrases. Aim for fresh and original descriptions. - Convey events and story through dialogue. - Mix short, punchy sentences with long, descriptive ones. Drop fill words to add variety. - Skip "he/she said said" dialogue tags and convey people's actions or face expressions through their speech - Avoid mushy dialog and descriptions, have dialogue always continue the action, never stall or add unnecessary fluff. Vary the descriptions to not repeat yourself. - Put dialogue on its own paragraph to separate scene and action. - Reduce indicators of uncertainty like "trying" or "maybe" When writing text: - NEVER conclude the scene on your own, follow the beat instructions very closely. - NEVER end with foreshadowing. - NEVER write further than what I prompt you with. - AVOID imagining possible endings, NEVER deviate from the instructions. - STOP EARLY if the continuation contains what was required in the instructions. You do not need to fill out the full amount of words possible.
User/Human
Take into account the following glossary of characters/locations/items/lore... when writing your response: <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> Continue the story using the following instructions: <instructions> 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. </instructions>

Model response

AI
Rain stippled the Camden pavement and turned the shutters of the closed shops into dull mirrors. Quinn stood beneath a chemist’s awning, water crawling from her cropped salt-and-pepper hair, and watched Tomás Herrera emerge from a lock-up opposite. He carried a medical bag in his left hand. His sleeve had ridden up, exposing the pale seam of a scar along his forearm. He checked both ends of the street before stepping out. Three hours opposite the Raven’s Nest had earned Quinn wet socks and a numb backside. The bar’s green neon had shimmered on the Soho pavement while people came and went beneath it, none of them doing anything she could put in a report. Then Herrera had slipped through the side door, taken a minicab to Camden and disappeared into the lock-up with a key of his own. Quinn crossed the road. “Tomás Herrera.” He stopped beneath a busted streetlamp. Rain jewelled his dark curls. A silver medallion rested against his chest, Saint Christopher worn smooth by thumbs. “Metropolitan Police. Put the bag down.” His gaze travelled over her warrant card, then to the unmarked car behind her. “You followed me from Soho for a chat?” “The bag.” “There’s a patient waiting.” “Then he’ll be glad of the extra time to describe his symptoms.” Herrera’s warm brown eyes hardened. He set one foot back, weight balanced, and Quinn moved to block the mouth of the alley beside him. “Don’t,” she said. He ran the other way. Quinn snatched the radio from her coat as his trainers struck the pavement. Herrera vaulted a stack of delivery crates, clipped the top with the medical bag and landed without breaking stride. Quinn went through the crates. Plastic split under her boot. Something inside them hissed. “Control, Quinn. Foot pursuit, Camden High Street. Male, twenties, dark curly hair, grey coat, carrying a medical bag. Require units.” Herrera cut between a night bus and a delivery van. The bus swallowed him in a wall of spray. Quinn ran along its flank, one hand raised against the mirror as it passed, and caught sight of him again on the far pavement. “Control, what’s the offence?” She ducked under the wing of a roadside sign. “He’s running.” “That’s not an offence, Quinn.” “Get me a unit.” Herrera glanced back. Not winded. Annoyed. He turned into a lane where restaurant waste steamed in metal bins. Quinn followed. Her shoes lost purchase on something soft; she caught a drainpipe and swung herself upright. Ahead, Herrera dragged a wheelie bin into her path. She put both hands on it and shoved. It rolled back at him, forcing him to dodge. For three seconds she gained. He looked over his shoulder again, closer now, close enough for her to see the medallion bouncing against his coat. “Stop making this worse.” “You followed me here.” “You opened the bag, this ends.” “No. You go home, this ends.” He kicked open a side gate. Quinn reached it as it rebounded and took the full weight on her forearm. Pain jumped to her shoulder. She forced through into a service yard hemmed by brick walls. Herrera was already at the far end, hauling himself over a chain-link fence. The medical bag went over first. He followed with one clean pull. Quinn hit the fence at a run. Her fingers found the wire. At forty-one, she no longer vaulted anything without paying for it, but payment came later. She dropped into the adjoining alley, knees flexed, and ran on. The street beyond held shuttered stalls and boards promising cheap phone repairs. Rain ticked against canvas roofs. A group outside a chicken shop saw Herrera coming and parted with the weary coordination of people who had survived other chases. Quinn barged through after him. “Police. Move.” Someone laughed. Herrera crossed the road towards a stretch of construction hoarding. Behind it rose the tiled flank of a disused Tube station, its upper windows bricked up, its roundel reduced to a faded red ghost. A door stood in the hoarding where no door had been a moment before. Quinn’s radio crackled. “Units four minutes out. Confirm your location.” She gave the street name. Herrera reached the station entrance and pulled something from his pocket. It looked like a coin until the light caught its uneven edge. Bone. He pressed it into a depression in the brickwork. The iron gate beside him shuddered. Rust flaked from its bars as it lifted. Quinn slowed. There were no lights beyond the gate. A staircase descended past the reach of the streetlamps, its walls tiled in green. Warm air breathed up from below, carrying candle smoke, wet stone and a sweetness that made her think of a hospital corridor after the flowers had begun to rot. Herrera stepped under the gate. He could have kept going. Instead, he turned. “You can’t come down there.” “Watch me.” “That’s the problem.” The gate began to descend. Quinn stopped at the threshold. Her radio issued a burst of static, then the dispatcher’s voice. “Quinn, wait for units. Acknowledge.” Her thumb rested on the transmit key. Waiting was sound police work. Four minutes for marked cars, another two to establish a cordon. She could photograph the entrance, record Herrera’s direction of travel and preserve the option of doing any of this again with officers at her shoulder. The gate had sunk to chest height. Herrera’s shoes struck the first stair. DS Morris had waited for a search team three years ago. He had stood outside a rented office in Woolwich, following every instruction Quinn had given him, and something had still killed him before the team arrived. The pathologist’s explanations had grown thinner with each question. Morris’s last transmission remained on Quinn’s old laptop: six seconds of static and Morris whispering that the stairs went the wrong way. She had never found a staircase in the building. Quinn looked at her worn leather watch. The second hand jerked past twelve. She photographed the gate, sent the picture with her location and keyed the radio. “Quinn. Suspect has entered the disused station. I’m maintaining observation.” “Wait for units.” The gate reached waist height. Herrera descended another step. “Detective,” he called. “Don’t.” Quinn dropped into a crouch and went under the gate. It struck the ground behind her. The rain vanished. Her radio died mid-word. Herrera had already disappeared around the bend in the stairs. Quinn followed, one hand skimming the tiled wall. The steps descended farther than the station’s street frontage allowed. A sign pointed towards platforms whose names had been chiselled away. Beneath it, someone had written in white pencil: NO TOKEN, NO ENTRY. The gate had been the token’s work. Quinn had used Herrera’s. She put that fact aside with the others that did not fit. Noise rose to meet her. Not the rumble of trains. Voices. Hundreds of them, packed close, arguing and laughing beneath a canopy of rattling metal. She reached the bottom of the stairs and stopped for half a pace. The old ticket hall had become a market. Stalls crowded between the pillars. Others lined the platforms beyond, their awnings sagging over the tracks. Bottles filled a chemist’s cabinet, each containing a blue flame that bent against the glass as Quinn passed. A woman behind a folding table weighed locks of hair on brass scales. Another stall displayed rows of labelled tins: GRAVE SALT, SECOND SIGHT, WOLFSBANE—ASK. Above an arch hung a chalkboard offering memories bought, debts located, questions answered by the hour. Quinn looked for wires beneath the nearest bottle. Bare wood. No battery pack. The flame inside pressed itself flat as her shadow crossed it. Herrera’s grey coat flashed beyond the ticket barriers. “Herrera.” He shoved through a knot of shoppers. A stallholder seized his arm, then recognised him. “Tommy? Back room’s full. Use the platform.” “Move,” Herrera shouted. “Please, move.” The crowd opened for him. It closed for Quinn. She drove her shoulder between two men in oilskins. One caught her coat. “No token.” Quinn showed him the warrant card. “Metropolitan Police.” He examined the crest without releasing her. “That’s not bone.” She twisted her sleeve from his grip and pushed on. Behind her, something shattered. A stallholder began swearing in a language that seemed to come from beneath the floor. Herrera reached the platform edge and jumped onto the tracks. The medical bag knocked against his hip. Quinn followed, landing among old cables and heaps of blackened glass. There were no rails under her boots, only narrow channels filled with rainwater. A stall on the opposite platform sold knives. The blades turned in their rack as she ran past, following her with their points. Quinn kept her eyes on Herrera. He looked back, and for the first time his face held something besides irritation. “Keep to the middle.” “Worried about my safety?” “Yes.” He vaulted onto the far platform. A vendor pulled a curtain aside for him. Letters hung above it on a length of wire: MEDICAL. EXCHANGE. NO REFUNDS. Quinn climbed after him. Hands reached for her from the crowd. She knocked one aside, ducked another and caught the curtain as it fell. Herrera’s medallion gleamed once in the darkness beyond. She tore the curtain open and went through.
created_at"2026-10-27T10:25:55.383Z" 10/27/2026, 10:25:55 AM
model"moonshotai/kimi-k3.1-pro-20261023"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency2667
moderation_latency(null)
generation_time369908
tokens_prompt1104
tokens_completion10014
native_tokens_prompt1084
native_tokens_completion8743
native_tokens_completion_images(null)
native_tokens_reasoning6670
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"stop"
service_tier(null)
usage0.089598
router(null)
user_agent"langchainjs-openai/1.0.0 ((node/v24.22.1; linux; x64))"
http_referer(null)
request_id"req-1793096755-D3d0Ua4Zo8w76g7M6xjA"
session_id(null)
preset_id(null)
api_type"completions"
id"gen-1793096755-VbOWDlXWoEZkWPnYUjgq"
upstream_id"chatcmpl-6ae07c34d18b3609bec43c40"
provider_responses
0
endpoint_id"a3fafaac-f097-4ef1-86b3-842854dad5c6"
id"chatcmpl-6ae07c34d18b3609bec43c40"
is_byokfalse
latency2667
model_permaslug"moonshotai/kimi-k3.1-pro-20261023"
provider_name"Moonshot AI"
status200
total_cost0.089598
cache_discount(null)
upstream_inference_cost0
provider_name"Moonshot 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
totalTags3
adverbTagCount0
adverbTags(empty)
dialogueSentences36
tagDensity0.083
leniency0.167
rawRatio0
effectiveRatio0
100.00% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount1545
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)
83.82% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount1545
totalAiIsms5
found
0
word"shimmered"
count1
1
word"weight"
count2
2
word"grave"
count1
3
word"shattered"
count1
highlights
0"shimmered"
1"weight"
2"grave"
3"shattered"
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
narrationSentences150
matches(empty)
100.00% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount2
hedgeCount2
narrationSentences150
filterMatches
0"think"
1"watch"
hedgeMatches
0"began to"
1"seemed to"
99.68% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences183
gibberishSentences1
adjustedGibberishSentences1
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount1
repetitionLoopCount0
controlTokenCount0
repeatedSegmentCount0
maxSentenceWordsSeen29
ratio0.005
matches
0"“Control, Quinn. Foot pursuit, Camden High Street. Male, twenties, dark curly hair, grey coat, carrying a medical bag. Require units.”"
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans0
markdownWords0
totalWords1544
ratio0
matches(empty)
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions6
unquotedAttributions0
matches(empty)
52.74% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions65
wordCount1388
uniqueNames13
maxNameDensity1.95
worstName"Quinn"
maxWindowNameDensity3
worstWindowName"Quinn"
discoveredNames
Camden2
Tomás1
Herrera22
Raven1
Nest1
Quinn27
Soho1
Saint1
Christopher1
Tube1
Morris3
Woolwich1
Rain3
persons
0"Tomás"
1"Herrera"
2"Raven"
3"Nest"
4"Quinn"
5"Saint"
6"Christopher"
7"Morris"
8"Rain"
places
0"Camden"
1"Soho"
2"Woolwich"
globalScore0.527
windowScore0.667
100.00% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences102
glossingSentenceCount2
matches
0"looked like a coin until the light caught"
1"language that seemed to come from beneath the floor"
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches0
per1kWords0
wordCount1544
matches(empty)
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount2
totalSentences183
matches
0"whispering that the"
1"put that fact"
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs95
mean16.25
std17.47
cv1.075
sampleLengths
038
134
267
34
42
524
66
714
88
92
104
1112
1224
133
145
1546
1620
1743
184
199
202
215
224
236
2455
255
2620
274
284
296
306
316
3255
3338
3444
352
362
3748
383
397
4028
411
4223
432
4450
4513
465
472
483
495
100.00% Passive voice overuse
Target: ≤2% passive sentences
passiveCount1
totalSentences150
matches
0"been chiselled"
100.00% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount0
totalVerbs250
matches(empty)
100.00% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount1
semicolonCount1
flaggedSentences2
totalSentences183
ratio0.011
matches
0"Her shoes lost purchase on something soft; she caught a drainpipe and swung herself upright."
1"Another stall displayed rows of labelled tins: GRAVE SALT, SECOND SIGHT, WOLFSBANE—ASK."
100.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount1396
adjectiveStacks0
stackExamples(empty)
adverbCount24
adverbRatio0.017191977077363897
lyAdverbCount1
lyAdverbRatio0.0007163323782234957
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences183
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences183
mean8.44
std5.81
cv0.688
sampleLengths
016
122
29
315
410
515
628
724
84
92
106
115
1213
136
1414
158
162
174
1812
195
2019
213
225
2313
2419
255
265
274
2820
2910
309
3124
324
339
342
355
364
373
382
391
4012
412
4215
439
448
459
465
4720
484
494
58.11% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats2
diversityRatio0.3551912568306011
totalSentences183
uniqueOpeners65
48.66% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount2
totalSentences137
matches
0"Then Herrera had slipped through"
1"Instead, he turned."
ratio0.015
100.00% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount41
totalSentences137
matches
0"He carried a medical bag"
1"His sleeve had ridden up,"
2"He checked both ends of"
3"He stopped beneath a busted"
4"His gaze travelled over her"
5"He set one foot back,"
6"He ran the other way."
7"She ducked under the wing"
8"He turned into a lane"
9"Her shoes lost purchase on"
10"She put both hands on"
11"It rolled back at him,"
12"He looked over his shoulder"
13"He kicked open a side"
14"She forced through into a"
15"He followed with one clean"
16"Her fingers found the wire."
17"She dropped into the adjoining"
18"She gave the street name."
19"It looked like a coin"
ratio0.299
25.69% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount119
totalSentences137
matches
0"Rain stippled the Camden pavement"
1"Quinn stood beneath a chemist’s"
2"He carried a medical bag"
3"His sleeve had ridden up,"
4"He checked both ends of"
5"The bar’s green neon had"
6"Quinn crossed the road."
7"He stopped beneath a busted"
8"Rain jewelled his dark curls."
9"A silver medallion rested against"
10"His gaze travelled over her"
11"Herrera’s warm brown eyes hardened."
12"He set one foot back,"
13"He ran the other way."
14"Quinn snatched the radio from"
15"Herrera vaulted a stack of"
16"Quinn went through the crates."
17"Something inside them hissed."
18"Herrera cut between a night"
19"The bus swallowed him in"
ratio0.869
0.00% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount0
totalSentences137
matches(empty)
ratio0
100.00% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences61
technicalSentenceCount2
matches
0"A group outside a chicken shop saw Herrera coming and parted with the weary coordination of people who had survived other chases."
1"Warm air breathed up from below, carrying candle smoke, wet stone and a sweetness that made her think of a hospital corridor after the flowers had begun to rot."
100.00% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags3
uselessAdditionCount0
matches(empty)
100.00% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags3
fancyCount1
fancyTags
0"Herrera shouted (shout)"
dialogueSentences36
tagDensity0.083
leniency0.167
rawRatio0.333
effectiveRatio0.056
88.9566%