Run: 2026-07-25-01KYD73RJEBAG4AD446945D3NM

Run Details

Duration:
1m 1s
Cost:
$0.025105
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 hammered the neon green sign above the Raven's Nest, turning its glow into a smear across the wet pavement. Detective Harlow Quinn pressed her shoulder against the alley wall opposite and watched the door for the third night running. Her informant had been specific. Herrera left through the side door, carrying a case he didn't want anyone to see. The side door opened. Tomás Herrera stepped out beneath the awning, olive skin washed pale under the streetlight, a steel medical case gripped in his right hand. He checked the street both ways. His Saint Christopher medallion swung free of his collar as he moved. Quinn pushed off the wall. "Mr Herrera. Metropolitan Police. I'd like a word." He froze. One heartbeat. Two. Then he ran. Quinn sprinted after him, boots slapping the flooded gutter. "Herrera! Stop!" He cut left through Soho's warren of lanes, dodging a delivery scooter, the case banging against his hip. Eighteen years of service had taught Quinn how men ran when they were guilty of paperwork versus guilty of blood. Herrera ran like a man carrying blood. "You're making this worse for yourself," she shouted. He glanced back, rain streaming down his face. "You don't know what you're walking into, Detective." "Then stop and explain it." "I can't." They burst onto Shaftesbury Avenue. Traffic hissed through standing water. Herrera weaved between a black cab and a bus, forcing Quinn to mount the pavement and cut the corner to keep pace. Her worn leather watch dug into her wrist with every stride. She'd lost DS Morris on a night like this. Rain, dark, a suspect who shouldn't have been able to do what he did. The report said accident. Her memory said otherwise. Herrera vaulted a low wall into Camden's backstreets. She followed, her knee barking at the landing, sharp jaw clenched against the pain. He was fast but she was relentless, and the gap closed to twenty metres, then fifteen. "You're a paramedic, Herrera," she called out. "Or you were. You help people. Whatever's in that case—" "Is exactly why you should go home." He ducked beneath a rusted archway and down a flight of steps toward an abandoned Tube station entrance, its roundel long faded to a ghost on the tiling. Quinn took the steps two at a time. The rain's roar fell away behind her, replaced by dripping water and something else. A hum, low and wrong, coming up from below like a struck wire. The ticket hall yawned dark ahead. Herrera paused at a rusted gate where a figure in a grey hood stood sentinel. He produced something small and pale from his pocket. A token. Bone-white, catching light that shouldn't exist down here. The figure stepped aside. Quinn reached the bottom of the stairs. "That's far enough." Herrera turned. Rainwater dripped from his dark curls. The scar along his left forearm showed where his sleeve had ridden up, a pale seam against his skin. "Detective Quinn." He said her name like he'd known it for weeks. "You've been watching the Nest for three days. I know who you are. I know about Morris." Her blood went cold. "What did you say?" "Your partner didn't die in an accident. You know that. You've always known that." He shifted the case to his other hand. "What's through that gate answers questions you've been asking for three years. But once you go through, you can't unsee it. And people like you don't last long down there without protection." "Then you'll be relieved to hear I'm armed." "Not with anything that matters down there." He stepped backward through the gate. "Make your choice, Detective. But make it quick. The Market doesn't wait." He vanished into the dark of the tunnel. Quinn stood at the threshold. The hum rose from below, threading through her teeth. Beyond the gate, faint light flickered—too warm for electricity, shifting like flame or something pretending to be flame. Shapes moved along the platform. Voices layered over one another, some speaking words she almost recognised and others that made her ear ache. The hooded figure turned toward her. Where its face should have been, shadow sat too thick, too deliberate. "Token," it said. The voice arrived from two directions at once. She reached for her warrant card. Stopped. Nothing in her career had prepared her to identify what stood in front of her, and every instinct screamed that showing a badge to it would be a joke in poor taste. "I don't have a token. I'm pursuing a suspect." "Then you don't enter." "He's carrying medical supplies into an unlicensed operation. That's my jurisdiction." Something shifted beneath the hood. "Your jurisdiction ends at the rain." Quinn's hand rested near her sidearm. Morris had followed something into a place the report couldn't describe, and she'd spent three years pretending the official story made sense. It never had. The gaps in the timeline, the way the body had been found, the witnesses who recanted within hours. Here, beneath Camden, the truth had a doorway and Herrera had walked through it. She thought of the case in his hand. Of Morris's empty chair. Of the quiet way the Met had closed the file. "I can wait," she said. "He has to come out sometime." The figure tilted its head. "The Market moves with the full moon. Tonight it moves. What goes in does not come out here." Quinn looked down at her watch. Past midnight. The rain above would be easing. The sensible choice waited in that street: call it in, log the location, write a report that no one would believe and everyone would bury. She stepped through the gate. The hooded figure didn't move to stop her. "No token, no protection. The Market will notice you, Detective." "It won't be the first place that has." She descended toward the platform. The air thickened with scents that had no business mixing—incense and blood, copper and jasmine. Stalls lined the old tracks, lit by jars of slow-moving light. A woman with mirrored eyes sold vials of silver liquid. Something with too many joints haggled over a stack of what Quinn's brain insisted on calling fur until it moved on its own. Maps of nowhere she knew covered the tiled walls, pinned with red thread. Herrera stood thirty metres ahead at a stall of brass instruments, handing the steel case to a figure wrapped in bandages. He looked up. Saw her. His face did something complicated—not fear, not quite resignation. "You actually followed," he said as she approached. "You told me the truth was down here." "I told you it was dangerous." "So was Morris's case." She stopped an arm's length away, close enough that her voice stayed under the Market's hum. "You're going to tell me everything, Herrera. Who killed my partner, what this place is, and what's in that case. Then I'm deciding what happens to you." The bandaged figure slid the case beneath its stall. Its head rotated toward Quinn with a sound like wet rope. "Fresh arrival," it rasped. "No token. No mark. No protection." The hum of the Market changed pitch. Stalls went quiet. Heads turned—human ones and otherwise—toward the detective standing alone on the platform in her rain-dark coat, her warrant card useless in her pocket, and the last train out of the world she'd known already gone.
created_at"2026-07-25T18:03:02.614Z" 7/25/2026, 6:03:02 PM
model"moonshotai/kimi-k3-20260715"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency3318
moderation_latency(null)
generation_time61071
tokens_prompt1104
tokens_completion1886
native_tokens_prompt1085
native_tokens_completion1641
native_tokens_completion_images(null)
native_tokens_reasoning50
native_tokens_cached1024
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)
usage0.0251052
router(null)
provider_responses
0
endpoint_id"650c9b12-7b6d-444d-8d92-df8daef84d7a"
id"chatcmpl-6a64fa435f4f33d6ae6c8be9"
is_byokfalse
latency3318
model_permaslug"moonshotai/kimi-k3-20260715"
provider_name"Moonshot AI"
status200
user_agent"langchainjs-openai/1.0.0 ((node/v24.18.0; linux; x64))"
http_referer(null)
request_id"req-1785002582-Z4FsBiNMc5D1AQfq6yqi"
session_id(null)
preset_id(null)
api_type"completions"
id"gen-1785002582-Fbjv0wQecxPUbQkCAZd8"
upstream_id"chatcmpl-6a64fa435f4f33d6ae6c8be9"
total_cost0.0251052
cache_discount0.0027648
upstream_inference_cost0
provider_name"Moonshot AI"
response_cache_source_id(null)
data_region"global"

Evaluation details

Result Evaluator Details Meta Data
100.00% Adverbs in dialogue tags
Target: ≤10% dialogue tags with adverbs
totalTags10
adverbTagCount1
adverbTags
0"He stepped backward [backward]"
dialogueSentences35
tagDensity0.286
leniency0.571
rawRatio0.1
effectiveRatio0.057
100.00% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount1233
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)
83.78% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount1233
totalAiIsms4
found
0
word"streaming"
count1
1
word"jaw clenched"
count1
2
word"sentinel"
count1
3
word"flickered"
count1
highlights
0"streaming"
1"jaw clenched"
2"sentinel"
3"flickered"
66.67% Cliché density
Target: ≤1 cliche(s) per 800-word window
totalCliches2
maxInWindow2
found
0
label"blood ran cold"
count1
1
label"jaw/fists clenched"
count1
highlights
0"blood went cold"
1"jaw clenched"
100.00% Emotion telling (show vs. tell)
Target: ≤3% sentences with emotion telling
emotionTells0
narrationSentences97
matches(empty)
100.00% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount2
hedgeCount0
narrationSentences97
filterMatches
0"watch"
hedgeMatches(empty)
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences122
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
repeatedSegmentCount0
maxSentenceWordsSeen38
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans0
markdownWords0
totalWords1228
ratio0
matches(empty)
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions14
unquotedAttributions0
matches(empty)
83.33% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions38
wordCount945
uniqueNames15
maxNameDensity1.27
worstName"Quinn"
maxWindowNameDensity2.5
worstWindowName"Quinn"
discoveredNames
Raven1
Nest1
Harlow1
Quinn12
Herrera9
Saint1
Christopher1
Soho1
Shaftesbury1
Avenue1
Morris3
Camden2
Tube1
Met1
Market2
persons
0"Raven"
1"Nest"
2"Harlow"
3"Quinn"
4"Herrera"
5"Saint"
6"Christopher"
7"Morris"
8"Met"
9"Market"
places
0"Soho"
1"Shaftesbury"
2"Avenue"
3"Camden"
globalScore0.865
windowScore0.833
100.00% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences63
glossingSentenceCount1
matches
0"not quite resignation"
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches0
per1kWords0
wordCount1228
matches(empty)
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount0
totalSentences122
matches(empty)
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs51
mean24.08
std19.85
cv0.824
sampleLengths
040
120
245
35
48
58
611
745
88
916
105
112
1274
1338
1417
157
1663
1744
1810
1927
2029
218
2254
238
2425
258
2655
2718
2811
2939
309
314
3211
3311
3463
3522
3611
3723
3839
395
4018
418
4277
4335
448
458
466
4747
4820
4910
100.00% Passive voice overuse
Target: ≤2% passive sentences
passiveCount1
totalSentences97
matches
0"been found"
100.00% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount0
totalVerbs175
matches(empty)
49.18% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount5
semicolonCount0
flaggedSentences4
totalSentences122
ratio0.033
matches
0"Beyond the gate, faint light flickered—too warm for electricity, shifting like flame or something pretending to be flame."
1"The air thickened with scents that had no business mixing—incense and blood, copper and jasmine."
2"His face did something complicated—not fear, not quite resignation."
3"Heads turned—human ones and otherwise—toward the detective standing alone on the platform in her rain-dark coat, her warrant card useless in her pocket, and the last train out of the world she'd known already gone."
100.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount953
adjectiveStacks0
stackExamples(empty)
adverbCount21
adverbRatio0.022035676810073453
lyAdverbCount0
lyAdverbRatio0
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences122
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences122
mean10.07
std7.18
cv0.713
sampleLengths
020
120
25
315
44
523
66
712
85
98
102
112
121
133
149
152
1618
1720
187
198
208
218
225
232
245
255
2622
2711
289
2914
304
314
328
3314
3416
357
3610
377
3828
398
4014
4113
426
4315
449
452
468
474
487
493
65.03% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats4
diversityRatio0.4098360655737705
totalSentences122
uniqueOpeners50
39.22% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount1
totalSentences85
matches
0"Then he ran."
ratio0.012
83.53% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount29
totalSentences85
matches
0"Her informant had been specific."
1"He checked the street both"
2"His Saint Christopher medallion swung"
3"He cut left through Soho's"
4"He glanced back, rain streaming"
5"They burst onto Shaftesbury Avenue."
6"Her worn leather watch dug"
7"She'd lost DS Morris on"
8"Her memory said otherwise."
9"She followed, her knee barking"
10"He was fast but she"
11"she called out"
12"He ducked beneath a rusted"
13"He produced something small and"
14"He said her name like"
15"Her blood went cold."
16"He shifted the case to"
17"He stepped backward through the"
18"He vanished into the dark"
19"She reached for her warrant"
ratio0.341
12.94% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount76
totalSentences85
matches
0"Detective Harlow Quinn pressed her"
1"Her informant had been specific."
2"Herrera left through the side"
3"The side door opened."
4"Tomás Herrera stepped out beneath"
5"He checked the street both"
6"His Saint Christopher medallion swung"
7"Quinn pushed off the wall."
8"Quinn sprinted after him, boots"
9"He cut left through Soho's"
10"Herrera ran like a man"
11"He glanced back, rain streaming"
12"They burst onto Shaftesbury Avenue."
13"Traffic hissed through standing water."
14"Herrera weaved between a black"
15"Her worn leather watch dug"
16"She'd lost DS Morris on"
17"The report said accident."
18"Her memory said otherwise."
19"Herrera vaulted a low wall"
ratio0.894
0.00% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount0
totalSentences85
matches(empty)
ratio0
100.00% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences35
technicalSentenceCount2
matches
0"Voices layered over one another, some speaking words she almost recognised and others that made her ear ache."
1"The air thickened with scents that had no business mixing—incense and blood, copper and jasmine."
100.00% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags10
uselessAdditionCount0
matches(empty)
100.00% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags5
fancyCount1
fancyTags
0"she shouted (shout)"
dialogueSentences35
tagDensity0.143
leniency0.286
rawRatio0.2
effectiveRatio0.057
86.1224%