Run: 2026-02-17-01KHNEZ0KPNKJ0PE7RJ7X4D4AH

Run Details

Duration:
1m 29s
Cost:
$0.001238
Provider:
SambaNova

Model input

System
You are an expert novelist with a gift for vivid, immersive prose. You write in tight third-person limited point of view with a strong narrative voice. Your prose is clean, precise, and engaging — you favor strong verbs, concrete details, and natural-sounding dialogue. You will be given a story bible (codex) containing canonical details about characters, locations, items, and lore. Use these details to ground your writing in the established world. Stay consistent with the codex. Write only the prose of the scene. Do not include titles, chapter headings, markdown formatting, or any commentary before or after the scene.
User/Human
<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> 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.

Model response

AI
The air in the abandoned Tube station was a thick, cold soup of damp stone, ozone, and something else, something metallic and coppery that Harlow Quinn knew all too well. It was the smell of a life violently spent. The flickering blue-white glow of police emergency lights bounced off tiled walls slick with condensation, turning the cavernous space into a disjointed funhouse of shifting shadows. Her boots echoed with a military precision against the grimy platform as she approached the cordon. A dozen uniforms were milling about, their movements sluggish in the unnatural chill. At the center of it all, a forensic tech in a white bunny suit was on his knees, carefully examining the victim, a man whose throat had been opened in a wide, grisly smile. “Detective Quinn.” A young sergeant, his face pale and pinched, nodded at her as she ducked under the tape. “Nasty one.” “They always are, Collins,” she said, her voice a low rasp. Her sharp jaw was set, her brown eyes already cataloging the scene, missing nothing. She adjusted the worn leather watch on her left wrist, a nervous tick. The stillness was wrong. A murder this brutal should have left a chaotic imprint, a frantic energy. This felt… precise. Ceremonial, even. Eva Kowalski stood a few feet from the body, clutching her worn leather satchel to her chest like a shield. Her curly red hair was a splash of vivid color in the monochrome gloom, her round glasses reflecting the scene back at her. She tucked a stray coil of hair behind her left ear, a nervous habit Quinn had noted the first time they’d met. “Detective,” Eva said, her voice softer than the surroundings warranted. “They let me in. I was researching the… history… of this place for the museum. I heard the commotion.” Quinn gave a curt nod. The British Museum’s ‘restricted archives’ were a convenient cover for the girl’s real expertise, one Quinn was only beginning to grasp. “What’s your take, Kowalski? Before the good doctor here gives me the official cause of death.” Eva’s green eyes darted around the platform, taking in the strange, makeshift stalls shrouded in dark canvas, the sigils scrawled in what looked like chalk on the pillars. This was no ordinary crime scene. This was the Veil Market, or at least, its most recent location. The place ran on bone tokens and moved with the moon. A killing here was a message. “It looks straightforward,” Eva ventured, her freckled complexion looking almost ethereal in the bleached light. “A robbery, perhaps. It’s a market, after all. He was probably a seller. Someone wanted what he had and decided not to pay.” Quinn’s gaze swept over the body again. The man was well-dressed in a fine wool overcoat, now ruined. His hands were clean, his nails manicured. Not a street-level dealer. A facilitator. “Robbery,” Quinn repeated, the word flat. She knelt, ignoring the protesting twinge in her knee, and pointed a gloved finger at the victim’s right hand. It was curled loosely, not in a defensive posture, but as if he had been holding something. “No defensive wounds. No signs of a struggle. He let his killer get close. That’s not a mugging. That’s an execution.” She shifted her attention to the pool of blood. It had seeped into the cracks between the paving stones, a dark, almost black lake. But the flow was wrong. It didn’t radiate out from the body in a perfect circle. It was disturbed. “Look at the spill pattern here,” she said, more to herself than to Eva. “It’s been smudged. Something was dragged through it after he fell. Or someone knelt in it.” Eva leaned closer, her satchel brushing Quinn’s arm. “Or something was taken from beside him. Something that was sitting in the blood.” Quinn’s eyes narrowed. She scanned the immediate vicinity. The forensics team had already laid out numbered evidence markers, but they denoted nothing of interest—a discarded cigarette butt, a scrap of cloth. The killer was careful. Meticulous. Her gaze fell on a patch of disturbed dust a few feet from the body. It was a perfect circle, about the size of a small saucer, with a faint, greasy residue at its center. She’d seen marks like that before. Three years ago, at the scene where they’d found Morris. The memory was a cold knife in her gut. “Collins,” Quinn called out, not taking her eyes off the mark. “Did anyone bag a small item from this location? Brass, maybe? Tarnished green?” The sergeant consulted his clipboard. “No, ma’am. Nothing logged from that grid.” Eva was watching her, a new intensity in her expression. She understood. “A seller of rare items,” she murmured, almost inaudibly. “In a market that sells… unusual things.” Quinn stood up, her mind racing, piecing it together. A high-end seller, executed with cold efficiency. No struggle. He knew his killer, or at least, he didn’t see them as a threat. They took something specific, something small enough to hold in one hand, something that had been placed on the ground, leaving that tell-tale ring in the dust. And they’d been calm victim’s blood to retrieve it. “This wasn’t a robbery,” Quinn stated, her voice cutting through the hum of the generator. “It was a repossession. He had something someone else wanted back. Desperately.” Eva’s hand went to her satchel again, her fingers tracing the worn leather. “A thing of power,” she whispered, so only Quinn could hear. “Something that leaves a trace. Something that can be tracked.” Quinn’s eyes snapped back to the greasy circle in the dust. A residue. An echo. She looked at Eva, at the satchel full of books on things that shouldn’t exist. The girl wasn’t just a researcher; she was a roadmap. “Kowalski,” Quinn said, her tone leaving no room for argument. “That compass you mentioned last week. The one that doesn’t point north. You still have it?” Eva’s eyes widened behind her glasses. She gave a slow, hesitant nod. “Good.” Quinn’s gaze swept over the bizarre, hidden market one last time, seeing not just a crime scene, but the edge of a much deeper, darker world—the same world that had taken Morris. The evidence hadn’t added up because she’d been trying to solve a human crime with human logic. But the faint, verdigris patina of a supernatural signature was now all she could see. “Get it. We’re not looking for a who. We’re following a what.”
created_at"2026-02-17T09:31:37.569867+00:00" 2/17/2026, 9:31:37 AM
model"deepseek/deepseek-chat-v3.1"
app_id182717
external_user(null)
streamedtrue
cancelledfalse
latency2017
moderation_latency(null)
generation_time89365
tokens_prompt940
tokens_completion1681
native_tokens_prompt857
native_tokens_completion1479
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)
origin"https://ncbench.com/"
is_byokfalse
finish_reason"stop"
native_finish_reason"stop"
usage0.0012378
router(null)
provider_responses
0
id"ceac472c-26e6-48d2-b41c-694b72528744"
status200
is_byokfalse
latency1959
endpoint_id"1dda4bb9-c626-4816-bb54-99665323fef0"
provider_name"SambaNova"
model_permaslug"deepseek/deepseek-chat-v3.1"
api_type"completions"
id"gen-1771320607-sXefFHkpuukry4JOyZ8M"
upstream_id"ceac472c-26e6-48d2-b41c-694b72528744"
total_cost0.0012378
cache_discount(null)
upstream_inference_cost0
provider_name"SambaNova"

Evaluation details

Result Evaluator Details Meta Data
100.00% Adverbs in dialogue tags
Target: ≤10% dialogue tags with adverbs
totalTags13
adverbTagCount0
adverbTags(empty)
dialogueSentences26
tagDensity0.5
leniency1
rawRatio0
effectiveRatio0
90.79% AI-ism adverb frequency
Target: <2% AI-ism adverbs (58 tracked)
wordCount1086
totalAiIsmAdverbs2
found
0
adverb"carefully"
count1
1
adverb"loosely"
count1
highlights
0"carefully"
1"loosely"
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)
49.36% AI-ism word frequency
Target: <2% AI-ism words (290 tracked)
wordCount1086
totalAiIsms11
found
0
word"echoed"
count1
1
word"chill"
count1
2
word"chaotic"
count1
3
word"gloom"
count1
4
word"perfect"
count2
5
word"scanned"
count1
6
word"intensity"
count1
7
word"racing"
count1
8
word"tracing"
count1
9
word"echo"
count1
highlights
0"echoed"
1"chill"
2"chaotic"
3"gloom"
4"perfect"
5"scanned"
6"intensity"
7"racing"
8"tracing"
9"echo"
66.67% Cliché density
Target: ≤1 cliche(s) per 800-word window
totalCliches2
maxInWindow2
found
0
label"eyes widened/narrowed"
count2
highlights
0"eyes narrowed"
1"eyes widened"
100.00% Emotion telling (show vs. tell)
Target: ≤3% sentences with emotion telling
emotionTells0
narrationSentences77
matches(empty)
100.00% Filter word density
Target: ≤3% sentences with filter/hedge words
filterCount1
hedgeCount0
narrationSentences77
filterMatches
0"watch"
hedgeMatches(empty)
100.00% Gibberish response detection
Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words)
analyzedSentences91
gibberishSentences0
adjustedGibberishSentences0
longSentenceCount0
runOnParagraphCount0
giantParagraphCount0
wordSaladCount0
repetitionLoopCount0
controlTokenCount0
maxSentenceWordsSeen34
ratio0
matches(empty)
100.00% Markdown formatting overuse
Target: ≤5% words in markdown formatting
markdownSpans0
markdownWords0
totalWords1079
ratio0
matches(empty)
100.00% Missing dialogue indicators (quotation marks)
Target: ≤10% speech attributions without quotation marks
totalAttributions11
unquotedAttributions0
matches(empty)
50.00% Name drop frequency
Target: ≤1.0 per-name mentions per 100 words
totalMentions33
wordCount840
uniqueNames10
maxNameDensity1.67
worstName"Quinn"
maxWindowNameDensity3.5
worstWindowName"Quinn"
discoveredNames
Tube1
Harlow1
Quinn14
Kowalski1
British1
Museum1
Eva10
Veil1
Market1
Morris2
persons
0"Harlow"
1"Quinn"
2"Kowalski"
3"Museum"
4"Eva"
5"Morris"
places(empty)
globalScore0.667
windowScore0.5
100.00% Narrator intent-glossing
Target: ≤2% narration sentences with intent-glossing patterns
analyzedSentences57
glossingSentenceCount1
matches
0"looked like chalk on the pillars"
14.64% "Not X but Y" pattern overuse
Target: ≤1 "not X but Y" per 1000 words
totalMatches2
per1kWords1.854
wordCount1079
matches
0"not in a defensive posture, but as if he had been holding something"
1"not just a crime scene, but the edge of a much deeper, darker world"
100.00% Overuse of "that" (subordinate clause padding)
Target: ≤2% sentences with "that" clauses
thatCount1
totalSentences91
matches
0"leaving that tell"
86.09% Paragraph length variance
Target: CV ≥0.5 for paragraph word counts
totalParagraphs26
mean41.5
std18.73
cv0.451
sampleLengths
065
163
221
360
465
529
642
763
838
931
1063
1143
1230
1322
1436
1560
1624
1712
1828
1968
2027
2134
2240
2326
2412
2577
91.59% Passive voice overuse
Target: ≤2% passive sentences
passiveCount3
totalSentences77
matches
0"been opened"
1"was curled"
2"been placed"
100.00% Past progressive (was/were + -ing) overuse
Target: ≤2% past progressive verbs
pastProgressiveCount2
totalVerbs135
matches
0"were milling"
1"was watching"
48.67% Em-dash & semicolon overuse
Target: ≤2% sentences with em-dashes/semicolons
emDashCount2
semicolonCount1
flaggedSentences3
totalSentences91
ratio0.033
matches
0"The forensics team had already laid out numbered evidence markers, but they denoted nothing of interest—a discarded cigarette butt, a scrap of cloth."
1"The girl wasn’t just a researcher; she was a roadmap."
2"“Good.” Quinn’s gaze swept over the bizarre, hidden market one last time, seeing not just a crime scene, but the edge of a much deeper, darker world—the same world that had taken Morris."
100.00% Purple prose (modifier overload)
Target: <4% adverbs, <2% -ly adverbs, no adj stacking
wordCount865
adjectiveStacks0
stackExamples(empty)
adverbCount30
adverbRatio0.03468208092485549
lyAdverbCount8
lyAdverbRatio0.009248554913294798
100.00% Repeated phrase echo
Target: ≤20% sentences with echoes (window: 2)
totalSentences91
echoCount0
echoWords(empty)
100.00% Sentence length variance
Target: CV ≥0.4 for sentence word counts
totalSentences91
mean11.86
std7.45
cv0.628
sampleLengths
030
19
226
316
413
534
619
72
811
914
1013
114
1213
132
141
152
1620
1723
1822
1910
2019
215
2221
2316
2428
256
2612
2711
286
2915
3023
317
3211
337
344
352
366
3719
3817
3921
409
4115
425
4311
443
4514
4616
478
4814
493
60.81% Sentence opener variety
Target: ≥60% unique sentence openers
consecutiveRepeats3
diversityRatio0.38461538461538464
totalSentences91
uniqueOpeners35
0.00% Adverb-first sentence starts
Target: ≥3% sentences starting with an adverb
adverbCount0
totalSentences68
matches(empty)
ratio0
72.94% Pronoun-first sentence starts
Target: ≤30% sentences starting with a pronoun
pronounCount25
totalSentences68
matches
0"It was the smell of"
1"Her boots echoed with a"
2"she said, her voice a"
3"Her sharp jaw was set,"
4"She adjusted the worn leather"
5"Her curly red hair was"
6"She tucked a stray coil"
7"His hands were clean, his"
8"She knelt, ignoring the protesting"
9"It was curled loosely, not"
10"She shifted her attention to"
11"It had seeped into the"
12"It didn’t radiate out from"
13"It was disturbed."
14"she said, more to herself"
15"She scanned the immediate vicinity."
16"Her gaze fell on a"
17"It was a perfect circle,"
18"She’d seen marks like that"
19"she murmured, almost inaudibly"
ratio0.368
4.12% Subject-first sentence starts
Target: ≤72% sentences starting with a subject
subjectCount62
totalSentences68
matches
0"The air in the abandoned"
1"It was the smell of"
2"The flickering blue-white glow of"
3"Her boots echoed with a"
4"A dozen uniforms were milling"
5"A young sergeant, his face"
6"she said, her voice a"
7"Her sharp jaw was set,"
8"She adjusted the worn leather"
9"The stillness was wrong."
10"A murder this brutal should"
11"Eva Kowalski stood a few"
12"Her curly red hair was"
13"She tucked a stray coil"
14"Eva said, her voice softer"
15"Quinn gave a curt nod."
16"The British Museum’s"
17"Eva’s green eyes darted around"
18"This was no ordinary crime"
19"This was the Veil Market,"
ratio0.912
0.00% Subordinate conjunction sentence starts
Target: ≥2% sentences starting with a subordinating conjunction
subConjCount0
totalSentences68
matches(empty)
ratio0
98.21% Technical jargon density
Target: ≤6% sentences with technical-jargon patterns
analyzedSentences32
technicalSentenceCount2
matches
0"It was curled loosely, not in a defensive posture, but as if he had been holding something."
1"They took something specific, something small enough to hold in one hand, something that had been placed on the ground, leaving that tell-tale ring in the dust."
0.00% Useless dialogue additions
Target: ≤5% dialogue tags with trailing filler fragments
totalTags13
uselessAdditionCount7
matches
0"she said, her voice a low rasp"
1"Eva said, her voice softer than the surroundings warranted"
2"Eva ventured, her freckled complexion looking almost ethereal in the bleached light"
3"she said, more to herself than to Eva"
4"Quinn called out, not taking her eyes off the mark"
5"Quinn stated, her voice cutting through the hum of the generator"
6"Quinn said, her tone leaving no room for argument"
0.00% Dialogue tag variety (said vs. fancy)
Target: ≤10% fancy dialogue tags
totalTags9
fancyCount5
fancyTags
0"Quinn repeated (repeat)"
1"Quinn called out (call out)"
2"she murmured (murmur)"
3"Quinn stated (state)"
4"she whispered (whisper)"
dialogueSentences26
tagDensity0.346
leniency0.692
rawRatio0.556
effectiveRatio0.385
71.1294%