Run: 2026-07-08-01KX1MTDN8RN5PDJD06X5TV9VJ

Run Details

Duration:
1m 1s
Cost:
$0.023798
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 hammered the asphalt of Old Compton Street and bounced in silver arcs. Detective Harlow Quinn drove her boots into the sodden ground and closed the gap on the man ahead. Water sheeted from her closely cropped salt-and-pepper hair and ran into the sharp line of her jaw. The worn leather watch on her left wrist flashed under a dripping traffic light as she pumped her arms. “Thornton Row is warped. Your evidence chain ends here, Herrera.” Tomás Herrera cut left without answer. His short curly dark brown hair matted against his olive skin. The Saint Christopher medallion bounced against his chest. He vaulted a tipped restaurant bin and scattered paper napkins that stuck to the wet bricks like white wounds. Quinn followed at once. Her military bearing held her upright even as rivulets poured from her shoulders. He burst onto Wardour and nearly clipped a black cab. Tyres hissed. The cabbie’s horn blared and then drowned under the downpour. Quinn’s boot found the slick pavement a half-second later. She snatched the door handle of a parked van and used the momentum to sling herself round the corner. Water exploded around her ankles. “You’re done running, Tomás. Bone tokens don’t erase fingerprints.” He glanced back once. Warm brown eyes locked on hers for a flicker, then he ducked into the narrow throat of MoD alley. Steam rose from a basement grate and mixed with the rain into a grey curtain. Quinn plunged through it. The heat kissed her face and vanished. Brick walls closed in, layered with old maps sold by street artists and black-and-white photographs of forgotten Soho faces. Neon bled from upper windows and painted the puddles green and red. Herrera slammed a palm against a fire-escape ladder and hauled himself up two rungs. Quinn closed. She seized the iron and felt the cold bite through her skin. He kicked free and dropped to the far side of a low wall that divided the alley from a private courtyard. She cleared it in one clean vault, landing in a crouch amid sodden cardboard. A cat screamed and fled. Three years earlier rain had run the same way down her partner’s face. She crushed the memory and drove forward. Her lungs burned with iron taste, yet her stride never faltered. Military precision carved each footstep. He reached Frith Street and hammered straight through the outdoor chairs of a late-night café. Metal legs skittered. A waiter cursed in Italian. Quinn vaulted the same tangle without breaking rhythm. Puddles reflected the distinctive green neon of the Raven’s Nest as they ripped past its doorway. The sign hissed and spit sparks where water struck the glass tubes. For a heartbeat the light bathed Herrera’s left forearm and revealed the old scar that ran pale against olive flesh. Knife memory. Quinn logged it and kept chase. “Stop and I let the medics process you clean.” He laughed once, sharp and short, then tore down the hill toward Oxford Street. Buses lumbered past like steel beasts, their headlights carving tunnels through the rain. Herrera slid between them. Horns wailed. Quinn timed the gap and shot through after him. A double-decker’s spray hit her full in the chest and stole half a breath. She spat water and ran harder. Cameras watched from every lamppost, cold glass eyes that recorded nothing of use. London buried its true business far below the footage. She knew that now. She had lost DS Morris to something the reports filed under natural causes while the morgue lights flickered without power. Herrera veered north. They left the neon and nightclubs behind. Residential streets gave way to shuttered shops and the drum of rain on tin roofs. Camden waited ahead, black and wet. Quinn’s legs screamed but her bearing refused surrender. She matched him stride for stride under railway bridges where water poured through rusted seams like open veins. He reached the edge of the locked Camden Market gates and did not slow. Instead he shouldered through a section of temporary hoarding that fronted an abandoned building site. Scaffold poles leaned like drunken skeletons. Quinn followed. Mud sucked at her boots. Rain drummed on plywood sheets overhead. He dropped into a stairwell cut into the old pavement, metal steps singing under his weight. The greasy light of the street vanished. Concrete walls closed round them and the air grew colder, older. Quinn descended three at a time. Her watch face glowed faint in the dark. Below, the abandoned Tube station opened like a throat. Stale wind rose from the platforms and smelled of wet stone and ozone. Faint market murmurs drifted up: voices speaking languages she could not name, the soft clink of glass on stone, a single distant cry that might have been a peacock or a child. Herrera vaulted the rusted ticket barriers. He produced something pale from his pocket and pressed it into the palm of a figure who waited in the deeper shadow. A bone token. The figure melted aside. Light spilled from beyond: stalls lit by jars of phosphor and oil lamps, racks of bottles that glowed like trapped fireflies, cages that held shapes too thin for any animal she recognised. The Veil Market breathed. “Walk away, Detective. Your warrant ends at that step.” Quinn halted on the cracked tile of the old platform. Water dripped from her hair onto the dirt-streaked floor and left dark coins. The worn leather of her watch band creaked as she flexed her fingers. Ahead the tunnel curved and swallowed Herrera’s curly head into the press of bodies and hanging canvases. Stall keepers glanced up then looked away with deliberate calm. A woman with peacock feathers for hair emptied powder into a brass scale. Smoke rose in perfect spheres that drifted against the walls of an old Tube map. She stood at the threshold. Rain still hammered the world above, distant now. Exhaust stink and chip oil faded under sharper scents of crushed herbs, burnt copper, and something sweet that coated the back of the throat. Her badge pressed a hard rectangle against her ribs. Eighteen years of service had never taken her past a normal door into a place that hummed with its own pulse. The figure who had taken the token watched her without expression. He said nothing. Droplets fell from the brick arch and landed on her shoulder with soft taps. Somewhere deeper a stringed instrument struck three notes that hung and then died. Quinn’s right hand brushed the worn leather strap once. She measured the depth of the tunnel, the set of the stalls, the way shadows moved where no bodies walked. Unfamiliar ground. Potentially fatal. Morris had walked into the same kind of dark three years before and the coroner’s report still smelled of lies. The material facts of this chase—the stolen sample from the lab, the Rafaele ledger pages, Herrera’s off-book clinics—all pointed down those steps. She rolled her shoulders once. Water sheeted from her coat. Her brown eyes narrowed against the phosphor glare. The military precision of every joint held her still for three long breaths. Then she took one deliberate step over the threshold and into the Veil Market.
created_at"2026-07-08T19:56:01.583Z" 7/8/2026, 7:56:01 PM
model"x-ai/grok-4.5-20260708"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency458
moderation_latency(null)
generation_time60073
tokens_prompt1140
tokens_completion2556
native_tokens_prompt1186
native_tokens_completion3859
native_tokens_completion_images(null)
native_tokens_reasoning2400
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"
usage0.023798
router(null)
provider_responses
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endpoint_id"0e927811-b1a8-4604-8b86-db5ce6eaa87c"
id"2b8282bc-0ab2-9747-a379-f60ba63e44fe"
is_byokfalse
latency115
model_permaslug"x-ai/grok-4.5-20260708"
provider_name"xAI"
status200
user_agent"langchainjs-openai/1.0.0 ((node/v24.18.0; linux; x64))"
http_referer(null)
request_id"req-1783540561-tCl6ic7rnbqybXTpwAJV"
session_id(null)
preset_id(null)
api_type"completions"
id"gen-1783540561-khIctQMuP7tpq4cjH7za"
upstream_id"2b8282bc-0ab2-9747-a379-f60ba63e44fe"
total_cost0.023798
cache_discount0.001728
upstream_inference_cost0
provider_name"xAI"
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
totalTags0
100.00% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount1198
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)
74.96% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount1198
totalAiIsms6
found
0
word"flicker"
count1
1
word"flickered"
count1
2
word"weight"
count1
3
word"perfect"
count1
4
word"pulse"
count1
5
word"measured"
count1
highlights
0"flicker"
1"flickered"
2"weight"
3"perfect"
4"pulse"
5"measured"
100.00% Cliché density
Target: ≤1 cliche(s) per 800-word window
totalCliches1
maxInWindow1
found
0
label"eyes widened/narrowed"
count1
highlights
0"eyes narrowed"
100.00% Emotion telling (show vs. tell)
Target: ≤3% sentences with emotion telling
emotionTells0
narrationSentences106
matches(empty)
100.00% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount3
hedgeCount0
narrationSentences106
filterMatches
0"watch"
hedgeMatches(empty)
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences110
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
repeatedSegmentCount0
maxSentenceWordsSeen32
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans0
markdownWords0
totalWords1196
ratio0
matches(empty)
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions2
unquotedAttributions0
matches(empty)
93.92% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions56
wordCount1159
uniqueNames24
maxNameDensity1.12
worstName"Quinn"
maxWindowNameDensity2
worstWindowName"Quinn"
discoveredNames
Old1
Compton1
Street3
Harlow1
Quinn13
Herrera8
Saint1
Christopher1
Wardour1
MoD1
Soho1
Frith1
Italian1
Raven1
Nest1
Oxford1
Morris2
Camden2
Market3
Tube2
Veil2
Rafaele1
Rain3
Water4
persons
0"Harlow"
1"Quinn"
2"Herrera"
3"Saint"
4"Christopher"
5"Raven"
6"Morris"
7"Camden"
8"Market"
9"Rain"
10"Water"
places
0"Old"
1"Compton"
2"Street"
3"Soho"
4"Frith"
5"Italian"
6"Oxford"
7"Veil"
globalScore0.939
windowScore1
100.00% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences80
glossingSentenceCount0
matches(empty)
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches0
per1kWords0
wordCount1196
matches(empty)
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount0
totalSentences110
matches(empty)
90.42% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs22
mean54.36
std25.36
cv0.466
sampleLengths
067
110
261
355
49
580
668
736
887
99
1062
1146
1257
1382
1468
1571
169
1791
1867
1941
2075
2145
100.00% Passive voice overuse
Target: ≤2% passive sentences
passiveCount0
totalSentences106
matches(empty)
100.00% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount0
totalVerbs192
matches(empty)
100.00% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount2
semicolonCount0
flaggedSentences1
totalSentences110
ratio0.009
matches
0"The material facts of this chase—the stolen sample from the lab, the Rafaele ledger pages, Herrera’s off-book clinics—all pointed down those steps."
100.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount1171
adjectiveStacks0
stackExamples(empty)
adverbCount30
adverbRatio0.025619128949615714
lyAdverbCount5
lyAdverbRatio0.004269854824935952
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences110
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences110
mean10.87
std6.29
cv0.579
sampleLengths
013
118
217
319
410
56
611
78
819
94
1013
1110
122
1310
149
1519
165
179
184
1919
2015
214
227
2319
2412
2514
262
2712
2821
2914
305
3113
327
3311
345
3515
363
375
388
3916
4012
4120
422
436
449
4514
4613
474
482
499
79.39% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats1
diversityRatio0.4818181818181818
totalSentences110
uniqueOpeners53
100.00% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount3
totalSentences99
matches
0"Instead he shouldered through a"
1"Somewhere deeper a stringed instrument"
2"Then she took one deliberate"
ratio0.03
100.00% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount28
totalSentences99
matches
0"His short curly dark brown"
1"He vaulted a tipped restaurant"
2"Her military bearing held her"
3"He burst onto Wardour and"
4"She snatched the door handle"
5"He glanced back once."
6"She seized the iron and"
7"He kicked free and dropped"
8"She cleared it in one"
9"She crushed the memory and"
10"Her lungs burned with iron"
11"He reached Frith Street and"
12"He laughed once, sharp and"
13"She spat water and ran"
14"She knew that now."
15"She had lost DS Morris"
16"They left the neon and"
17"She matched him stride for"
18"He reached the edge of"
19"He dropped into a stairwell"
ratio0.283
40.81% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount83
totalSentences99
matches
0"Detective Harlow Quinn drove her"
1"Water sheeted from her closely"
2"The worn leather watch on"
3"Tomás Herrera cut left without"
4"His short curly dark brown"
5"The Saint Christopher medallion bounced"
6"He vaulted a tipped restaurant"
7"Quinn followed at once."
8"Her military bearing held her"
9"He burst onto Wardour and"
10"The cabbie’s horn blared and"
11"Quinn’s boot found the slick"
12"She snatched the door handle"
13"Water exploded around her ankles."
14"He glanced back once."
15"Steam rose from a basement"
16"Quinn plunged through it."
17"The heat kissed her face"
18"Brick walls closed in, layered"
19"Neon bled from upper windows"
ratio0.838
0.00% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount0
totalSentences99
matches(empty)
ratio0
67.67% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences57
technicalSentenceCount6
matches
0"He vaulted a tipped restaurant bin and scattered paper napkins that stuck to the wet bricks like white wounds."
1"He kicked free and dropped to the far side of a low wall that divided the alley from a private courtyard."
2"For a heartbeat the light bathed Herrera’s left forearm and revealed the old scar that ran pale against olive flesh."
3"Instead he shouldered through a section of temporary hoarding that fronted an abandoned building site."
4"Faint market murmurs drifted up: voices speaking languages she could not name, the soft clink of glass on stone, a single distant cry that might have been a pea…"
5"Light spilled from beyond: stalls lit by jars of phosphor and oil lamps, racks of bottles that glowed like trapped fireflies, cages that held shapes too thin fo…"
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
91.5721%