Run: 2026-10-07-01M4AVGQEBHHDKB2XFMJGZDQVF

Run Details

Duration:
12.3s
Cost:
$0.009734
Provider:
Mistral

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
The rain hammered the pavement, turning Soho’s cobbles into a slick mirror of neon and shadow. Detective Harlow Quinn’s boots splashed through puddles, her breath sharp in the cold air. The green glow of The Raven’s Nest’s sign flickered ahead, but she didn’t slow. Her target—a lanky figure in a dark coat—dodged between a delivery lorry and a stack of crates, vanishing into the alley beside the bar. She took the corner hard, her leather watch strap biting into her wrist as she caught herself against the brickwork. The alley reeked of damp and stale beer, the narrow passage barely wide enough for her shoulders. Ahead, the suspect’s silhouette flickered under a broken streetlamp before dropping into a manhole, the iron cover clanging shut behind him. Quinn cursed. Of course. The city’s underbelly always had a way of swallowing the guilty. She yanked the cover up, the rusted hinges groaning. A ladder descended into blackness, the rungs slick with moisture. No time to hesitate. She swung down, her grip sure despite the rainwater dripping into her eyes. The ladder ended in a puddle, her boots sinking into the muck as she stepped onto a narrow ledge. The tunnel stretched ahead, the walls lined with ancient tiles, the air thick with the scent of wet stone and something older—something that prickled the hairs on her neck. A distant clatter echoed. Footsteps. She moved, her torch cutting a beam through the dark. The tunnel split, but the sound came from the left, where the ceiling dipped lower, forcing her to duck. The beam caught movement—a flash of coat, then nothing. She broke into a jog, her pulse thudding in her ears. Then the tunnel opened into a cavern. The Veil Market sprawled before her, a labyrinth of stalls under the flicker of gas lamps and floating orbs of blue fire. The air hummed with murmurs, the clink of coins, the scent of spices and something metallic, like blood. Figures moved in the shadows—some human, some not. A woman with too many eyes watched her from a stall of glass vials. A man with a face like cracked porcelain turned away. Quinn’s hand went to her sidearm. This wasn’t a place for cops. The suspect was gone, swallowed by the crowd. She scanned the sea of faces, her jaw tight. Then she saw him—ducking behind a stall of blackened bones, his coat flapping. She pushed forward, shouldering past a man in a long coat who hissed at her in a language she didn’t know. The stallholders’ eyes followed her, some curious, some hostile. A woman with silver hair and a necklace of teeth blocked her path. “You’re not one of us,” the woman said, her voice like dry leaves. Quinn didn’t break stride. “Out of my way.” The woman smirked, stepping aside just enough for Quinn to squeeze past. The suspect was closer now, weaving toward a curtained-off section of the market. She followed, her torch beam bouncing over jars of things that writhed in the light. A hand grabbed her arm. She spun, her gun half-drawn, but it was just a man—olive skin, dark curls, a scar running down his forearm. Tomás Herrera. His Saint Christopher medallion glinted in the torchlight. “Detective,” he said, low and urgent. “You shouldn’t be here.” “Herrera.” She yanked her arm free. “You know where he’s going?” Tomás glanced toward the curtains. “That’s the Black Bazaar. No cops. No rules.” “Then why are you here?” “I work here.” His jaw tightened. “But you? They’ll tear you apart.” The suspect vanished behind the curtain. Quinn’s fingers twitched on her gun. Every instinct screamed at her to turn back. But the case—the deaths, the whispers of something unnatural—led here. And DS Morris had died chasing the same shadows. She stepped toward the curtain. Tomás grabbed her wrist. “Harlow. Think.” She met his gaze. “I’m not leaving.” A growl rumbled from the darkness behind the curtain. Not human. Tomás exhaled sharply. “Then don’t get yourself killed.” He pulled a small bone token from his pocket and pressed it into her hand. “For the way back.” She didn’t ask what he meant. The curtain swayed, and she pushed through, the torch beam cutting into the black. The air turned colder. The stalls here were different—cages of things that skittered, jars of things that pulsed. The suspect stood at the far end, talking to a figure draped in shadows, their voice a whisper that made Quinn’s skin crawl. She advanced, her boots silent on the damp stone. The suspect turned. His face was wrong—too smooth, too still. Then he smiled, and his mouth split wider than it should. Quinn’s torch flickered. The decision was made. She raised her gun. And the shadows moved.
created_at"2026-10-07T09:36:06.616Z" 10/7/2026, 9:36:06 AM
model"mistralai/mistral-medium-3.5-20260430"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency634
moderation_latency(null)
generation_time12312
tokens_prompt1104
tokens_completion1223
native_tokens_prompt1039
native_tokens_completion1090
native_tokens_completion_images(null)
native_tokens_reasoning0
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"default"
usage0.0097335
router(null)
user_agent"langchainjs-openai/1.0.0 ((node/v24.21.0; linux; x64))"
http_referer(null)
request_id"req-1791365766-cMS1Vtwclir7ygSTOo1x"
session_id(null)
preset_id(null)
api_type"completions"
id"gen-1791365766-kR4q7ZPrfl4TBPW6weho"
upstream_id"64277f5c899b49dd9a2614e20360e8e0"
provider_responses
0
endpoint_id"d21d316f-d540-4718-b36e-3beff85d0cf9"
id"64277f5c899b49dd9a2614e20360e8e0"
is_byokfalse
latency634
model_permaslug"mistralai/mistral-medium-3.5-20260430"
provider_name"Mistral"
status200
total_cost0.0097335
cache_discount(null)
upstream_inference_cost0
provider_name"Mistral"
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
totalTags5
adverbTagCount0
adverbTags(empty)
dialogueSentences14
tagDensity0.357
leniency0.714
rawRatio0
effectiveRatio0
93.77% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount802
totalAiIsmAdverbs1
found
0
adverb"sharply"
count1
highlights
0"sharply"
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)
31.42% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount802
totalAiIsms11
found
0
word"flickered"
count3
1
word"echoed"
count1
2
word"footsteps"
count1
3
word"pulse"
count1
4
word"flicker"
count1
5
word"porcelain"
count1
6
word"scanned"
count1
7
word"pulsed"
count1
8
word"whisper"
count1
highlights
0"flickered"
1"echoed"
2"footsteps"
3"pulse"
4"flicker"
5"porcelain"
6"scanned"
7"pulsed"
8"whisper"
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
narrationSentences74
matches(empty)
100.00% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount1
hedgeCount0
narrationSentences74
filterMatches
0"watch"
hedgeMatches(empty)
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences83
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
repeatedSegmentCount0
maxSentenceWordsSeen30
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans0
markdownWords0
totalWords791
ratio0
matches(empty)
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions5
unquotedAttributions0
matches(empty)
94.98% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions22
wordCount727
uniqueNames12
maxNameDensity1.1
worstName"Quinn"
maxWindowNameDensity2
worstWindowName"Quinn"
discoveredNames
Soho1
Harlow1
Quinn8
Raven1
Nest1
Veil1
Market1
Herrera1
Saint1
Christopher1
Tomás4
Morris1
persons
0"Harlow"
1"Quinn"
2"Raven"
3"Nest"
4"Market"
5"Herrera"
6"Saint"
7"Christopher"
8"Tomás"
9"Morris"
places
0"Soho"
globalScore0.95
windowScore1
100.00% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences50
glossingSentenceCount0
matches(empty)
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches0
per1kWords0
wordCount791
matches(empty)
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount0
totalSentences83
matches(empty)
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs35
mean22.6
std21.41
cv0.947
sampleLengths
068
158
215
384
45
549
67
772
812
930
1043
1113
128
1340
145
1530
1610
1711
1813
195
2012
216
2233
235
246
257
2611
2727
2820
2941
309
3121
323
338
344
95.78% Passive voice overuse
Target: ≤2% passive sentences
passiveCount2
totalSentences74
matches
0"was gone"
1"was made"
100.00% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount0
totalVerbs117
matches(empty)
0.00% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount11
semicolonCount0
flaggedSentences9
totalSentences83
ratio0.108
matches
0"Her target—a lanky figure in a dark coat—dodged between a delivery lorry and a stack of crates, vanishing into the alley beside the bar."
1"The tunnel stretched ahead, the walls lined with ancient tiles, the air thick with the scent of wet stone and something older—something that prickled the hairs on her neck."
2"The beam caught movement—a flash of coat, then nothing."
3"Figures moved in the shadows—some human, some not."
4"Then she saw him—ducking behind a stall of blackened bones, his coat flapping."
5"She spun, her gun half-drawn, but it was just a man—olive skin, dark curls, a scar running down his forearm."
6"But the case—the deaths, the whispers of something unnatural—led here."
7"The stalls here were different—cages of things that skittered, jars of things that pulsed."
8"His face was wrong—too smooth, too still."
100.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount458
adjectiveStacks0
stackExamples(empty)
adverbCount11
adverbRatio0.024017467248908297
lyAdverbCount2
lyAdverbRatio0.004366812227074236
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences83
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences83
mean9.53
std6.21
cv0.652
sampleLengths
016
114
214
324
420
517
621
72
82
911
109
1110
124
1313
1419
1529
164
171
1810
1919
209
2111
227
2322
2418
258
2614
2710
286
296
308
319
3213
3321
349
3513
3613
374
384
3912
4013
4115
425
4320
442
458
466
474
486
495
42.57% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats8
diversityRatio0.3132530120481928
totalSentences83
uniqueOpeners26
100.00% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount3
totalSentences68
matches
0"Then the tunnel opened into"
1"Then she saw him—ducking behind"
2"Then he smiled, and his"
ratio0.044
96.47% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount21
totalSentences68
matches
0"Her target—a lanky figure in"
1"She took the corner hard,"
2"She yanked the cover up,"
3"She swung down, her grip"
4"She moved, her torch cutting"
5"She broke into a jog,"
6"She scanned the sea of"
7"She pushed forward, shouldering past"
8"She followed, her torch beam"
9"She spun, her gun half-drawn,"
10"His Saint Christopher medallion glinted"
11"he said, low and urgent"
12"She yanked her arm free"
13"His jaw tightened"
14"She stepped toward the curtain."
15"She met his gaze."
16"He pulled a small bone"
17"She didn’t ask what he"
18"She advanced, her boots silent"
19"His face was wrong—too smooth,"
ratio0.309
18.82% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount60
totalSentences68
matches
0"The rain hammered the pavement,"
1"Detective Harlow Quinn’s boots splashed"
2"The green glow of The"
3"Her target—a lanky figure in"
4"She took the corner hard,"
5"The alley reeked of damp"
6"The city’s underbelly always had"
7"She yanked the cover up,"
8"A ladder descended into blackness,"
9"She swung down, her grip"
10"The ladder ended in a"
11"The tunnel stretched ahead, the"
12"A distant clatter echoed."
13"She moved, her torch cutting"
14"The tunnel split, but the"
15"The beam caught movement—a flash"
16"She broke into a jog,"
17"The Veil Market sprawled before"
18"The air hummed with murmurs,"
19"Figures moved in the shadows—some"
ratio0.882
0.00% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount0
totalSentences68
matches(empty)
ratio0
75.89% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences32
technicalSentenceCount3
matches
0"The tunnel stretched ahead, the walls lined with ancient tiles, the air thick with the scent of wet stone and something older—something that prickled the hairs …"
1"Then she saw him—ducking behind a stall of blackened bones, his coat flapping."
2"The stalls here were different—cages of things that skittered, jars of things that pulsed."
100.00% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags5
uselessAdditionCount0
matches(empty)
100.00% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags2
fancyCount0
fancyTags(empty)
dialogueSentences14
tagDensity0.143
leniency0.286
rawRatio0
effectiveRatio0
84.9901%