Run: 2026-09-01-01M1EMZ25CSYV4F6YC0JXABG0A

Run Details

Duration:
1m 42s
Cost:
$0.025478
Provider:
xAI

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 turned Camden High Street into a black mirror. Detective Harlow Quinn drove her boots through the puddles and kept the man in the dark coat in her sights. Neon from a kebab shop smeared green and gold across the wet tarmac. A bus hissed at the kerb and threw a sheet of water at her shins. She did not break stride. The coat ahead cut left into Inverness Street. Quinn followed. Her closely cropped salt-and-pepper hair lay flat against her skull, rain tracking the sharp line of her jaw. The worn leather watch on her left wrist ticked past midnight. Eighteen years of this. Her bearing stayed military even as her lungs started to burn. “Stop. Metropolitan Police.” The man did not stop. He vaulted a stack of collapsed market crates and slipped between two vans parked nose to tail. Quinn took the crates at a run, one hand on the top edge, and landed in a crouch that sent water spraying up her trousers. A cat shot from under a wheelie bin and vanished. She was already moving. He was five-ten, lean, dark hair plastered to his neck. She had picked him up outside a Soho doorway an hour earlier, the green neon of The Raven’s Nest still in her peripheral vision when he clocked her and ran. He knew the streets. She knew the work. A woman with a pushchair blocked the alley mouth. Quinn angled her body, palm out. “Police. Move.” The woman yanked the pushchair against the brick. Quinn passed close enough to smell damp wool and baby milk. Ahead, the coat flared as the man took another corner, this one tighter, down toward the canal. Her radio crackled against her hip. She keyed it without slowing. “Quinn. Foot pursuit. Male, dark coat, heading toward Camden Lock. No backup yet. Keep the channel open.” Static answered her. Then a dispatcher’s voice, thin through the rain. “Units are ten minutes out, Detective. Weather’s a mess. Do you have an ID?” “Negative. He ran from the Nest. I want him in a room.” She released the button. Ten minutes was a lifetime. The canal path opened on her left, iron railings, black water beyond. The man ignored it and cut right, up a flight of slick stone steps that climbed back toward the high street. Quinn took them two at a time. Her thighs protested. She ignored that too. At the top he was already across the road, weaving through the last of the night traffic. A black cab braked. Horn. The man slapped the bonnet and kept going. Quinn stepped into the same gap, palm raised at the cabbie, and heard a string of curses fade behind her. She hit the far pavement and saw the coat disappear down a service alley between a shuttered record shop and a tattoo parlour whose window still glowed a sickly red. The alley stank of piss and old grease. Puddles hid potholes. She splashed through them. The man reached a chain-link fence at the far end, scrambled, and dropped the other side. Quinn hit the fence a second later. The metal bit her palms. She hauled herself over, landed, rolled her shoulder, and came up running. A staircase yawned in the ground. Old Tube signage hung crooked above it, the enamel chipped, the station name long since painted out. No lights. The man went down it without hesitation, coat swallowed by the dark. Quinn stopped at the lip. Water streamed off her collar and pattered on the first step. She drew her torch and thumbed it on. The beam found wet concrete, a handrail furred with rust, and the receding slap of shoes. She went down. The stairwell turned twice. The air changed. Surface rain-noise faded and a different sound rose to meet her: a low murmur, many voices, the clink of glass, something that might have been a bell. Her torch picked out a landing, then another flight, then a stretch of tiled corridor that belonged to a station abandoned decades ago. Posters peeled from the walls in damp curls. A rat watched her from the tracks beyond a broken barrier and did not run. The corridor opened onto a platform. Quinn killed the torch. The Veil Market occupied the old westbound platform and spilled into the tunnel mouth. Paraffin lamps and jars of something that was not fire hung from the curved ceiling and threw a dirty gold light over stalls built from scaffolding, old doors, and cloth. The air tasted of metal, incense, and wet earth. People moved between the stalls with the unhurried purpose of those who did not expect interruption. A woman with too many joints in her fingers arranged bottles of dark liquid. A man in a butcher’s apron sharpened a knife that caught the light wrong. Somewhere deeper in, a generator coughed. The man in the dark coat was already among them. He glanced back once. Their eyes met across twenty yards of platform. Then he slipped between two canvas walls and was gone. Quinn stepped onto the platform. A figure blocked her at once. Broad, bald, a coat sewn with small white objects that resolved, as she looked, into bones. Fingers. Vertebrae. He held out a palm. “Token.” She kept her warrant card in her pocket. This was not a place that respected it. She had heard rumours of this market in the three years since Morris died, fragments from informants who went quiet when she pressed, a name that moved with the moon. She had never stood in it. The bone-sewn man did not move. “I don’t have one.” “Then you don’t come in.” Behind him the market breathed. She caught a flash of the dark coat near a stall selling what looked like maps drawn on skin. The suspect was putting distance between them with every second she stood here. Her radio would not work this far under. Backup was still in the rain, still ten minutes from a staircase they did not know existed. The bone-sewn man waited. His eyes were pale and uninterested. Quinn’s hand hovered near her hip, not quite at her baton, not quite at her phone. The leather watch sat heavy on her wrist. Morris had died in a basement that smelled like this, metal and earth and something that did not belong to London. She had never found the thing that killed him. She had never stopped looking. A laugh rose from a stall to her left, too high, cut off. The woman with too many joints corked a bottle and looked straight at Quinn, then away. The generator coughed again. In the tunnel mouth, shadows moved that did not match the lamps. The man in the dark coat would be at the far end by now, or into a passage she could not see, or among people who would hide him for a coin or a favour. If she turned around and climbed back to the street, she would file the pursuit as lost, wait for the units, and spend the rest of the night chasing a name through CCTV that this place did not appear on. If she went forward, she went without a token, without backup, into a market that sold things her training had no language for. The bone-sewn man shifted his weight. “Last chance. You walk away, or you bleed for the token like everyone else who forgets.” Quinn looked past his shoulder. Between the stalls, a gap. The dark coat, or a coat like it, turning a corner of hanging rugs. Her jaw tightened. Rainwater still dripped from her hair onto the platform tiles, each drop a small dark coin. She weighed the stairs behind her against the tunnel ahead. She weighed ten minutes of backup against a suspect who had run from The Raven’s Nest as if the Nest itself could not protect him. She weighed the unexplained hole in a case file three years old against a platform full of people who did not belong in any report she had ever written. Her hand left her hip. She took one step toward the bone-sewn man.
created_at"2026-09-01T14:11:28.564Z" 9/1/2026, 2:11:28 PM
model"x-ai/grok-4.6-20260810"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency588
moderation_latency(null)
generation_time101672
tokens_prompt1104
tokens_completion2659
native_tokens_prompt1186
native_tokens_completion4139
native_tokens_completion_images(null)
native_tokens_reasoning2467
native_tokens_cached1152
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"completed"
service_tier"default"
usage0.025478
router(null)
user_agent"langchainjs-openai/1.0.0 ((node/v24.19.0; linux; x64))"
http_referer(null)
request_id"req-1788271888-gkNIcBMALWPBeNN5eKoa"
session_id(null)
preset_id(null)
api_type"completions"
id"gen-1788271888-bJhmBzKYHaQ7E44AQpcv"
upstream_id"8d1f586f-0dd3-9aa5-83a0-e59af1fdd6cb"
provider_responses
0
endpoint_id"0d0536e3-7eb1-4acb-8249-c8813365c2d8"
id"8d1f586f-0dd3-9aa5-83a0-e59af1fdd6cb"
is_byokfalse
latency149
model_permaslug"x-ai/grok-4.6-20260810"
provider_name"xAI"
status200
total_cost0.025478
cache_discount0.001728
upstream_inference_cost0
provider_name"xAI"
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
totalTags0
100.00% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount1360
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)
92.65% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount1360
totalAiIsms2
found
0
word"resolved"
count1
1
word"weight"
count1
highlights
0"resolved"
1"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
narrationSentences118
matches(empty)
100.00% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount2
hedgeCount1
narrationSentences118
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)
analyzedSentences127
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
repeatedSegmentCount0
maxSentenceWordsSeen40
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans0
markdownWords0
totalWords1360
ratio0
matches(empty)
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions0
unquotedAttributions0
matches(empty)
95.57% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions32
wordCount1286
uniqueNames14
maxNameDensity1.09
worstName"Quinn"
maxWindowNameDensity2
worstWindowName"Quinn"
discoveredNames
Camden1
High1
Street2
Harlow1
Quinn14
Inverness1
Soho1
Raven2
Nest3
Tube1
Veil1
Market1
Morris2
London1
persons
0"Harlow"
1"Quinn"
2"Raven"
3"Market"
4"Morris"
places
0"Camden"
1"High"
2"Street"
3"Inverness"
4"Soho"
5"London"
globalScore0.956
windowScore1
57.41% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences81
glossingSentenceCount3
matches
0"looked like maps drawn on skin"
1"not quite at her baton, not quite at her phone"
2"not quite at her phone"
3"smelled like this, metal and earth and som"
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches0
per1kWords0
wordCount1360
matches(empty)
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount0
totalSentences127
matches(empty)
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs39
mean34.87
std30.94
cv0.887
sampleLengths
062
154
23
361
448
515
62
747
817
911
1014
1112
1256
1380
1455
1537
1640
173
1880
196
204
21103
2232
235
2429
251
2658
274
285
2962
3010
3159
3245
3398
346
3516
36107
375
388
100.00% Passive voice overuse
Target: ≤2% passive sentences
passiveCount1
totalSentences118
matches
0"was gone"
100.00% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount2
totalVerbs210
matches
0"was already moving"
1"was putting"
100.00% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount0
semicolonCount0
flaggedSentences0
totalSentences127
ratio0
matches(empty)
100.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount1295
adjectiveStacks0
stackExamples(empty)
adverbCount40
adverbRatio0.03088803088803089
lyAdverbCount2
lyAdverbRatio0.0015444015444015444
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences127
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences127
mean10.71
std7.84
cv0.732
sampleLengths
09
120
213
315
45
58
62
718
811
94
1011
113
125
1317
1425
1510
164
1710
1830
194
204
219
226
232
248
2511
2617
276
285
2917
303
318
3214
3312
344
355
3612
3721
387
393
404
4117
424
431
448
4520
4630
478
483
494
51.97% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats9
diversityRatio0.3543307086614173
totalSentences127
uniqueOpeners45
88.50% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount3
totalSentences113
matches
0"Then a dispatcher’s voice, thin"
1"Somewhere deeper in, a generator"
2"Then he slipped between two"
ratio0.027
89.03% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount37
totalSentences113
matches
0"She did not break stride."
1"Her closely cropped salt-and-pepper hair"
2"Her bearing stayed military even"
3"He vaulted a stack of"
4"She was already moving."
5"He was five-ten, lean, dark"
6"She had picked him up"
7"He knew the streets."
8"She knew the work."
9"Her radio crackled against her"
10"She keyed it without slowing."
11"She released the button."
12"Her thighs protested."
13"She ignored that too."
14"She hit the far pavement"
15"She splashed through them."
16"She hauled herself over, landed,"
17"She drew her torch and"
18"She went down."
19"Her torch picked out a"
ratio0.327
30.80% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount97
totalSentences113
matches
0"Detective Harlow Quinn drove her"
1"Neon from a kebab shop"
2"A bus hissed at the"
3"She did not break stride."
4"The coat ahead cut left"
5"Her closely cropped salt-and-pepper hair"
6"The worn leather watch on"
7"Her bearing stayed military even"
8"The man did not stop."
9"He vaulted a stack of"
10"Quinn took the crates at"
11"A cat shot from under"
12"She was already moving."
13"He was five-ten, lean, dark"
14"She had picked him up"
15"He knew the streets."
16"She knew the work."
17"A woman with a pushchair"
18"Quinn angled her body, palm"
19"The woman yanked the pushchair"
ratio0.858
88.50% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount2
totalSentences113
matches
0"If she turned around and"
1"If she went forward, she"
ratio0.018
74.18% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences52
technicalSentenceCount5
matches
0"Surface rain-noise faded and a different sound rose to meet her: a low murmur, many voices, the clink of glass, something that might have been a bell."
1"Paraffin lamps and jars of something that was not fire hung from the curved ceiling and threw a dirty gold light over stalls built from scaffolding, old doors, …"
2"Broad, bald, a coat sewn with small white objects that resolved, as she looked, into bones."
3"If she went forward, she went without a token, without backup, into a market that sold things her training had no language for."
4"She weighed the unexplained hole in a case file three years old against a platform full of people who did not belong in any report she had ever written."
100.00% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags0
uselessAdditionCount0
matches(empty)
100.00% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags0
92.2860%