Run: 2026-05-10-01KR8XKXB7PDTVTPDZWJ43V25M

Run Details

Model:
Grok 4.3
Duration:
31.8s
Cost:
$0.006123
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="4414" name="Eva Kowalski" aliases="Eva, Evie" pronouns="she/her" species="Human" storyRole="Best Friend"> <eyeColor>green</eyeColor> <hair>curly red</hair> <height>5'4"</height> <age>26</age> <glasses>round glasses</glasses> <satchel>worn leather satchel full of books</satchel> <freckles>freckled complexion</freckles> <nervousHabit>tucking hair behind her left ear</nervousHabit> <description>Aurora's childhood friend and an occult researcher.</description> <backstory>Moved to London two years before Aurora and works as a research assistant at the British Museum's restricted archives. She holds a master's degree in Ancient History from Oxford.</backstory> </character> <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> <item id="2004" name="Veil Compass" aliases="the Compass, shadow compass" type="Tool" origin="The Veil Market"> <casingMaterial>small brass compass</casingMaterial> <faceMarkings>face etched with protective sigils</faceMarkings> <needle>points toward the nearest supernatural rift or portal</needle> <patina>casing has a patina of verdigris</patina> <creator>crafted by a Shade artisan</creator> <description>A compass attuned to supernatural energy.</description> </item> </codex> Continue the story using the following instructions: <instructions> Write a fully fleshed out scene of at least 1000 words in the mystery genre. A detective arrives at a crime scene in an unusual location. Something is wrong — the evidence doesn't add up. A colleague is present, offering a different interpretation. Through careful observation and deduction, the detective begins to see what others have missed. 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 abandoned Tube station beneath Camden swallowed the crime scene in damp stone and flickering emergency lights. Floodlamps had been set up on tripods along the disused platform, their beams cutting through mist that rose from puddles of pooled rainwater and worse. Detective Harlow Quinn stepped off the last rung of the maintenance ladder, boots striking wet concrete with a firm sound that echoed twice before the silence reclaimed it. Her leather watch sat tight against her left wrist. She adjusted it once, squared her shoulders, and moved forward with the measured stride she had learned in uniform. A yellow sheet covered the body. It lay near the old northbound rail, arms tucked close to the ribs, legs bent at awkward angles. The smell reached her before the details did: copper, earth, and something sharper like burning leaves. Two uniformed constables stood at the tape line. One held a clipboard. The other stared at the third rail as though it might still carry current. Eva Kowalski waited beside the forensics van, satchel straps crossing her chest, round glasses catching the lamplight. Curly red hair escaped in strands at her temples. She noticed Quinn and tucked a lock behind her left ear, then nodded toward the covered form. “Detective. They called you in early.” Quinn stopped two paces short of the sheet. “First officers on scene said it looked personal. Where’s the team lead?” “Called away to another body in King’s Cross. They left me to photograph the preliminaries until someone senior arrived.” Quinn lifted the sheet with two gloved fingers. The victim lay on his back, mid-thirties, dark jacket torn across the chest in three parallel slashes. The wounds ran deep but blood had pooled beneath him rather than sprayed outward. No defensive cuts on the hands. No bruising around the throat. Quinn leaned closer. The skin along each cut had puckered inward as though pressure had drawn the edges together after the blade left. She lowered the sheet. “When did dispatch log the call?” “Half past two. Patrol found him exactly like this. No camera footage from above ground. The council shut these tunnels off in 2003.” Quinn walked the length of the platform, counting her steps. Twenty-seven. She turned and studied the ground. Footprints showed multiple sets, some clearer than others, all heading toward the north end where the tunnel mouth yawned black. One set stopped a meter short of the body and doubled back. She crouched, tracing the edge of a heel print with her pen. The sole had left a fine dusting of white powder that did not match the soot on the rails. “Witness statements?” she asked without looking up. “None yet. The couple who reported it heard shouting around one forty-five. They were on the street level, heard it through a grate. When they went down the service stairs the shouting had stopped. They saw the body and phoned it in. Uniforms took their details.” Quinn rose and circled the body again. She noted the position of the arms, palms up, fingers slightly curled. Kidney puncture usually left the victim curled on the side. She checked the jacket again through the sheet. The lining was torn at the inner pocket in a manner that suggested something had been pulled free rather than fallen out. She straightened and glanced toward Eva. “Did you photograph the lining before they moved anything?” Eva opened her satchel and produced a small tablet. She scrolled, angled the screen toward Quinn, then handed it over. The close-up showed the pocket turned inside out, threads pulled loose at the seam. “Looks like it was searched,” Eva said. “But the report said no wallet, no phone, nothing on him worth taking. Robbery that wasn’t finished?” Quinn returned the tablet. She walked to the north tunnel mouth and shone her torch along the lower brickwork. Fresh scuff marks ran at knee height, as though someone had braced a knee there. She moved the beam higher. Chalky residue clung to a protruding rivet, the same white dust that had marked the heel print. She scraped a sample onto a card and sealed it. “Give me the light spectrum overlay from the photographs.” Eva tapped the tablet again and passed it. Quinn studied the image. Under alternate lighting the wounds showed faint halos of green-blue luminescence along the edges, something the naked eye missed under the sodium lamps. The color matched the white residue on her card. She looked at Eva. “You’ve seen this before?” “Similar signature in the archives. Certain alchemical mixtures leave that glow when they interact with body heat. It fades after an hour or two. That’s why they had us come out before dawn.” Quinn stepped closer to the rail. A second set of prints, narrower, had crossed the body line twice, moving from the left wall to the right and back. The second set never reached the blood pool. She followed the track until it ended at a rusted maintenance door set into the far wall. The door stood ajar by six centimeters. She pulled it wider with her pen. Inside, the small alcove held an empty crate and a coil of copper wire, both undisturbed except for a single palm print on the wire’s outer loop. She pressed a lift kit against the print and lifted it. “Two people came in,” she said. “One killed him, the other watched or helped. But the watcher never stepped in the blood. They avoided it like they knew exactly where it would flow.” Eva folded her arms, satchel shifting against her hip. “He could have been killed somewhere else and carried here. That would explain no arterial spray.” Quinn shook her head. “Livor mortis has already set along the back and the right side. He died here. The blood stayed where gravity put it.” She returned to the body and lifted the sheet once more. The jacket collar was folded inward at the left shoulder, the way it would if someone had grabbed the material to turn the victim over after death. Quinn pressed the fabric flat again. She examined the right sleeve. A small tear at the cuff revealed a loop of thread that did not match the jacket’s stitching. She pulled gently and freed a single strand of red wool. Eva leaned in. “Not his clothing then.” Quinn placed the thread into an evidence bag and sealed it. She studied the platform ceiling where old ventilation shafts opened like black squares. One shaft showed a recent scrape along its lower lip, metal bright against the rust. She pointed. “Whoever ran touched that on the way out. The height matches someone climbing a service ladder to street level through the old vent.” A forensics tech approached with a body bag. Quinn held up a hand. “Not yet. I need the wound angles documented in situ first.” The tech retreated. Quinn circled once more, observing the way the mist from the puddles rose slightly higher around the blood pool than elsewhere on the platform. She faced Eva directly. “Tell me what you see that’s off.” Eva adjusted her glasses with one finger. “The wounds are too clean for a street fight. No hesitation marks. The lack of blood trail suggests whoever did this cleaned up as they went, which is unusual for panic. And the door print looks deliberate. Most people wouldn’t touch the wire if they were running.” Quinn nodded once. “That matches what I see. But there’s more. The white dust on the prints is the same compound lighting up under the spectrum. It wasn’t on the victim’s hands, so he wasn’t the one who carried it in. The killer brought it. And he knew the timing of when it would glow. He waited for the body to cool before he left.” She crossed to the crate inside the alcove and tilted it with her boot. The bottom held a faint rectangular impression the size of a small book or compact device. She photographed it, then returned to the platform and measured the distance from the print on the wire to the nearest rail. Two point four meters. Far enough that a person standing there would not have been splashed if the victim fell forward. Quinn lowered the torch. She watched the mist curl around her ankles. “Whoever they were, they staged the scene to look like a robbery gone wrong. They wanted us to think the victim fought back and lost his belongings. But they missed the fact that the blood settled in two directions instead of one. That shows the body was moved after the first bleed stopped. They lifted him to search the back pockets, then put him down again. That’s not panic. That’s method.” Eva shifted her weight. “You’re saying this wasn’t a street crime at all. It was planned for this tunnel.” Quinn met her gaze. “Exactly. And whoever planned it used something from the market to hide the evidence. The glow tells us that much. Now we need to find out what they carried the residue in.” She turned once more to the north tunnel. Torchlight picked out fresh scrape marks on the brick, matching the size of the brass casing already forming an image in her mind. The compass. Someone had used it to navigate the dark, left in a hurry, and dropped the thread in their retreat. Quinn bagged a second sample of the white dust from the brick. She spoke without turning. “Call the archives. Tell them we have a case that needs their restricted files on alchemical traces. And keep the press away until we decide what this really is. The streets above don’t need to know the tunnels talk back.”
created_at"2026-05-10T12:25:57.36Z" 5/10/2026, 12:25:57 PM
model"x-ai/grok-4.3-20260430"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency546
moderation_latency(null)
generation_time31699
tokens_prompt1149
tokens_completion2443
native_tokens_prompt1100
native_tokens_completion1926
native_tokens_completion_images(null)
native_tokens_reasoning0
native_tokens_cached64
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"
usage0.0061228
router(null)
provider_responses
0
endpoint_id"45623cb8-18e5-4b32-8fc4-85d05439982d"
id"00020dc3-caca-9d14-b9f4-4093895cbd6a"
is_byokfalse
latency244
model_permaslug"x-ai/grok-4.3-20260430"
provider_name"xAI"
status200
user_agent"langchainjs-openai/1.0.0 ((node/v24.14.1; linux; x64))"
http_referer(null)
request_id"req-1778415957-ZHCoPBjEqDREd7GH9pPl"
session_id(null)
api_type"completions"
id"gen-1778415957-nXrZhHpdrnXzkAimiJe2"
upstream_id"00020dc3-caca-9d14-b9f4-4093895cbd6a"
total_cost0.0061228
cache_discount0.0000672
upstream_inference_cost0
provider_name"xAI"
response_cache_source_id(null)

Evaluation details

Result Evaluator Details Meta Data
100.00% Adverbs in dialogue tags
Target: ≤10% dialogue tags with adverbs
totalTags4
adverbTagCount0
adverbTags(empty)
dialogueSentences27
tagDensity0.148
leniency0.296
rawRatio0
effectiveRatio0
87.66% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount1621
totalAiIsmAdverbs4
found
0
adverb"slightly"
count2
1
adverb"gently"
count1
2
adverb"really"
count1
highlights
0"slightly"
1"gently"
2"really"
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)
78.41% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount1621
totalAiIsms7
found
0
word"echoed"
count1
1
word"silence"
count1
2
word"measured"
count2
3
word"tracing"
count1
4
word"weight"
count1
5
word"navigate"
count1
highlights
0"echoed"
1"silence"
2"measured"
3"tracing"
4"weight"
5"navigate"
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
narrationSentences96
matches(empty)
100.00% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount1
hedgeCount0
narrationSentences96
filterMatches
0"watch"
hedgeMatches(empty)
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences119
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
repeatedSegmentCount0
maxSentenceWordsSeen71
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans0
markdownWords0
totalWords1621
ratio0
matches(empty)
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions15
unquotedAttributions0
matches(empty)
54.67% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions38
wordCount1049
uniqueNames7
maxNameDensity1.91
worstName"Quinn"
maxWindowNameDensity3
worstWindowName"Quinn"
discoveredNames
Tube1
Camden1
Harlow1
Quinn20
Kowalski1
Eva11
One3
persons
0"Camden"
1"Harlow"
2"Quinn"
3"Kowalski"
4"Eva"
5"One"
places(empty)
globalScore0.547
windowScore0.667
100.00% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences70
glossingSentenceCount0
matches(empty)
100.00% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches0
per1kWords0
wordCount1621
matches(empty)
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount0
totalSentences119
matches(empty)
100.00% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs39
mean41.56
std27.2
cv0.654
sampleLengths
098
166
243
36
420
519
673
710
823
980
107
1146
1265
139
1434
1524
1666
179
1844
198
2033
21105
2233
2325
2426
2578
267
2741
2823
2951
3011
3154
3265
3373
3483
3519
3636
3764
3844
94.30% Passive voice overuse
Target: ≤2% passive sentences
passiveCount3
totalSentences96
matches
0"was torn"
1"been pulled"
2"was folded"
3"been splashed"
100.00% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount0
totalVerbs172
matches(empty)
100.00% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount0
semicolonCount0
flaggedSentences0
totalSentences119
ratio0
matches(empty)
100.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount1053
adjectiveStacks0
stackExamples(empty)
adverbCount35
adverbRatio0.03323836657169991
lyAdverbCount6
lyAdverbRatio0.005698005698005698
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences119
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences119
mean13.62
std11.18
cv0.821
sampleLengths
017
125
228
39
419
56
618
716
88
94
1014
1117
129
1317
146
158
1612
1719
188
1917
2014
216
225
233
2420
254
266
2723
2810
291
306
3120
3212
3312
3419
357
3646
377
3812
3910
408
4122
426
439
449
4511
4614
477
4817
494
58.54% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats2
diversityRatio0.36134453781512604
totalSentences119
uniqueOpeners43
0.00% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount0
totalSentences91
matches(empty)
ratio0
92.53% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount29
totalSentences91
matches
0"Her leather watch sat tight"
1"She adjusted it once, squared"
2"It lay near the old"
3"She noticed Quinn and tucked"
4"She lowered the sheet."
5"She turned and studied the"
6"She crouched, tracing the edge"
7"she asked without looking up"
8"She noted the position of"
9"She checked the jacket again"
10"She straightened and glanced toward"
11"She scrolled, angled the screen"
12"She walked to the north"
13"She moved the beam higher."
14"She scraped a sample onto"
15"She looked at Eva."
16"She followed the track until"
17"She pulled it wider with"
18"She pressed a lift kit"
19"She returned to the body"
ratio0.319
31.43% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount78
totalSentences91
matches
0"The abandoned Tube station beneath"
1"Floodlamps had been set up"
2"Detective Harlow Quinn stepped off"
3"Her leather watch sat tight"
4"She adjusted it once, squared"
5"A yellow sheet covered the"
6"It lay near the old"
7"The smell reached her before"
8"The other stared at the"
9"Eva Kowalski waited beside the"
10"She noticed Quinn and tucked"
11"Quinn stopped two paces short"
12"Quinn lifted the sheet with"
13"The victim lay on his"
14"The wounds ran deep but"
15"Quinn leaned closer."
16"The skin along each cut"
17"She lowered the sheet."
18"Quinn walked the length of"
19"She turned and studied the"
ratio0.857
0.00% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount0
totalSentences91
matches(empty)
ratio0
100.00% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences46
technicalSentenceCount2
matches
0"Detective Harlow Quinn stepped off the last rung of the maintenance ladder, boots striking wet concrete with a firm sound that echoed twice before the silence r…"
1"Chalky residue clung to a protruding rivet, the same white dust that had marked the heel print."
100.00% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags4
uselessAdditionCount0
matches(empty)
100.00% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags3
fancyCount0
fancyTags(empty)
dialogueSentences27
tagDensity0.111
leniency0.222
rawRatio0
effectiveRatio0
86.5846%